52

CHAPTER-II

REVIEW OF LITERATURE AND RESEARCH METHODOLOGY

Review of Literature is the process of identifying previous studies and going through those

studies to ascertain the level of research already conducted relating to the field of study It

provides an idea about the research problems research methodology applied and attainment

of research objectives by previous researches It also helps in identification of potential areas

of research describing research objectives defining research methodology and developing

research report Research methodology is the process of conducting research for research

problem under investigation As the title of the chapter suggests the chapter has been divided

in to two sections Section I provides information about the literature on life insurance

industry whereas Section II deals with methodology applied in the research

SECTION-I

REVIEW OF LITERATURE

The literature on Indian life insurance industry includes books theses dissertations study

reports and articles published by researchers and academicians in different periodicals The

available literature for the present study is given below

Stowe D John (1978) examined several hypotheses derived from a simple chance-

constrained model of life insurance company portfolio using a cross-sectional time

series panel of fifteen annual observations for ninety two large US life insurance

companies Usual yield variables and non yield variables such as the relative amount of

surplus and the cost of reserve liabilities were significant determinants of the composition

of life insurance company portfolios It was observed that portfolio adjustments occurred

more rapidly than previously reported i n the literature

Buser Stephen A Smith Michael L (1983) applied Mean Variance Model expressing the

optimal amount of insurance in terms of two components the expected value of the

wage claim and the risk return characteristics of the insurance contract The model

thus offered an appealing way to formulate the life insurance problem in a portfolio

context Implications of the model for the functioning of a life insurance market were

examined along with explanation of existing accidental death contracts It was

summarized that the accidental death contract appeals to the risk-tolerant policy owner but

53

has characteristics similar to a gambling contract because the amount of coverage does not

depend on the value of the wage claim

Mary A Weiss (1986) illustrated a method for measuring productivity for life insurers

New techniques for measuring output of life insurers were developed and it was developed

using total factor productivity approach for two sample insurers ie stock and mutual

insurer for five year intervals The applicability of the output and productivity

measurement methodologies developed is not limited to the specific insurers studied but

rather can be used as a guide in measuring the productivity of any life insurer or the life

insurance industry in general

Martin F Grace and S t eph en G Timme (1992) reported estimates of overall

a n d product specific scale economies using sample of four hundred and twenty three U S

life insurers The study suggested that the magnitude of scale economies and cost

complementarities may vary with the scale and mix of outputs In contrast previous

studies only provide a single point estimate of industry cost characteristics us in g the

sample mean output vector This study therefore provides a more complete

representation of the industryrsquos cost characteristic and in turn new insights into decisions

related to the optimal scale and mix of outputs

Duane B Graddy Ghassem Homaifar Kenneth W Hollman (1992)

analyzed the market response of stock returns of insurers to the formulation debate and

enactment of the Tax Reform Act of 1986 Provisions of the Tax Reform Act showed

increases in the effective tax rates of insurers despite the proposed lowering of

marginal rates The stock prices of insurers reacted negatively in the formulation Debate

and Committee mark up phases of the legislative process Significant abnormal returns

were not evidenced in the enactment phase

Mayers David and C l i f f o rd W Smith Jr (1992) found that the compensation of

mutual executives and mutual subsidiary executives is lower than that of stock executives

and stock subsidiary executives in life insurance industry Moreover the compensation of

mutual executives is less responsive to firm performance than that of stock executives

This evidence is consistent with the existence of differences in corporate investment

opportunity sets and resulting differences in required managerial discretion between

mutual and stock life insurance companies

54

Akhigbe Aigbe Stephen FBorde Jeff Madura (1993) measured the share price response

of insurers to increase in the dividend and matched control samples of banks and industrial

firms that are similarly assessed It was found that the share price response for insurers is

positive and significant The magnitude of the response for life insurers is smaller than that

of other types of insurers or industrial companies but is greater than that of banks This

result may be due to the relatively low level of capital maintained by life insurers A cross-

sectional analysis also suggested that the share price responses across insurers are not

related to firm-specific characteristics

Adams Mike (1997) examined empirically the determinants of audit committee formulation

in life insurance firms The study tested six hypotheses namely whether the existence of

audit committees is related to organizational form firm size leverage asset in place

reinsurance and total monitoring costs using pooled 1991-1993 data from New Zealandrsquos life

insurance industry Fixed effects regression was used to arrive at parametric estimates The

results indicated that consistent with expectations audit committees appear to be positively

associated with large entities high leverage companies and firms with high total monitoring

expenditures However the variables such as organizational form assets in place and

reinsurance were not found statistically significant Thus the study provides mixed empirical

results

Hirofumi Fukuyama (1997) investigates productive efficiency and productivity changes

of Japanese life insurance companies by focusing primarily on the ownership structures

(mutual and stock) and economic conditions (expansion and recession) The study indicates

that mutual and stock companies possess identical technologies despite differences in

incentives of managers and in legal form but productive efficiency and productivity

performances differ from time to time across the two ownership types under different

economic conditions

Adams Mike Hossain Mahmud (1998) explained differences in the level of information

which is being disclosed voluntarily by life insurance companies in their annual reports The

study thus specified the relation between voluntary disclosure and eight explanatory variables

representing major construct of the managerial discretion hypothesis in the form of fixed

effects regression model The data for the year 1988 to 1993 was drawn from New Zealandrsquos

55

life insurance industry It was found that the organizational form firm size product diversity

and distribution system are positively related to the level of voluntary disclosure as implied

by the managerial discretion hypothesis Non executive directors and reinsurers are those two

independent variables which were observed to be significant in opposite direction

Ranade Ajit and Rajeev Ahuja (1999 presented an overview of life insurance

operations in India and identified the emerging strategic issues in the light of

liberalization and the impending private sector entry into insurance The need for

private sector entry has been justified on the basis of enhancing the efficiency of

operations achieving a greater density and penetration of life insurance in the

country and for greater mobilization of long terms savings for long gestation

infrastructure projects In the wake of such coming competition the LIC with its 40

years of experience and wide reach is at an advantageous position However unless it

addresses strategic issues such as changing demography and demand for pensions

demand for a wider variety of products and having greater freedom in its investments

LIC may find it difficult to adapt to liberalized scenario

Pant Niranjan (1999) by considering the impact of liberalization and Insurance Bill 1999 on

insurance sector stated that this would result in increasing involvement of the large and

powerful insurance companies of the world in the Indian insurance industry The effect was

uncertain as this could work as an opportunity as well as a challenge for the life insurers So

it was stressed that it is essential to take this in an encouraging manner for turning this

involvement of private sector players into a positive factor of overall growth It was

also mentioned that such an effort would however require the support of a clearer and

more cogent legislation than the Insurance Regulation and Development Bill 1999

Rao D Tripati (1999) developed a proper perspective of the ongoing debates on the

privatisation and globalisation of the insurance sector A systematic study of the structure

and pattern of growth of the Indian insurance industry is essential An analysis of

pattern of growth of life insurance industry since its nationalisation in 1956 has been

carried out This article goes into the operating results of the Life Insurance Corporation

and their macro economic importance The study highlighted the pattern and growth of

life insurance business in India Specifically it deals with the analysis of growth of new

business business in force income and outgo (financial outflow) Life Fund ie

56

institutionalisation of savings and business by different zones of LIC Finally these

indicators a re compared with the related macro variables The analysis reveals that average

sum assured per policy has declined in real terms The increase in the rural business might

involve higher transaction costs in the absence of adequate infrastructure facilities in rural

areas But income and outgo has shown that even with lower sum assured and increase in

rural business the LIC has succeeded in converting a growing amount of annual premium

income in to life insurance fund The outgo as a proportion of income declined partly due to

the decline in death benefits and expense in management

Yates Jo Anne (1999) examined the early adoption and use of computers by life insurance

companies in 1950rsquos using Anthony Giddens Structuration Theory as theoretical lens It

helped to know how pre computer punched card tabulating technology was used in

insurance operations and use of computers in early computer era Most of the times it leads

to expect the reinforcement of existing structures It is also helpful in understanding the new

ways and innovative uses of computer technology in insurance

Grosen Anders Peter Lochte Jorgensen (1999) analyzed one of the most common life

insurance products ie participating (or with profits) policy and showed that the typical

participating policy can be decomposed into a risk free bond element a bonus option and a

surrender option A dynamic model was constructed in which these elements can be valued

separately using contingent claims analysis The impact of various bonus policies and various

levels of the guaranteed interest rate was analyzed numerically and it was found that values

of participating policies were highly sensitive to the bonus policy that surrender options can

be quite valuable and that LIC solvency can be quickly jeopardized if earning opportunities

deteriorate in a situation where bonus reserves are low and promised returns are high

Cummins J David Sharon Tennyson and Mary A Weiss (1999) examined the

relationship between mergers and acquisitions efficiency and scale economies in the US life

insurance industry Cost and revenue efficiency was estimated for the period of 1988-1995

using data envelopment analysis (DEA) The Malmquist methodology is used to measure

changes in efficiency over time It was found that acquired firms achieve greater efficiency

gains than firms that have not been involved in mergers and acquisitions Firms operating

with non decreasing returns to scale and financially vulnerable firms are more likely to be

acquisition targets Overall mergers and acquisitions in the life insurance industry have had

57

a beneficial effect on efficiency

Segal Dan (2000) estimated the acquisition and maintenance costs associated with life

policies as a function of the amount of insurance and number of policies of an insurer by

estimating a cost function The final sample consists of 448 firms and the study period

includes years from 1995 to 1998 Several statistical characteristics of the costs such as

mean and median of the sample were examined The data indicates that there is a large

variation among life insurance companies It was found that the costs associated with life

policies of the largest insurers are much higher than the corresponding costs of other firms

Comparing the costs between ldquobranch firmsrdquo and non-branch firmsrdquo it was revealed that the

costs of branch firms are generally higher than that of non branch firms

Rao D Tripati (2000) explained the macroeconomic implications of privatization and

foreign participation in the insurance sector It was obtained that the Life Insurance

Corporation (LIC) of India is dominant in the overall industry in two aspects pooling

and redistributing risks across millions of policyholders and in performance of financial

intermediation Therefore the issue of privatization and foreign participation must be

approached cautiously with a step by step approach and should be preceded by

microeconomic institutional and legal reforms

Sinha Tapen (2002) examined the institution of insurance in India Over the past century

Indian insurance industry has experienced big changes It started as a fully private system

with no restriction on foreign participation After the independence the industry went to the

other extreme It became a state owned monopoly In 1991 when rapid economic changes

took place in many parts of the Indian economy nothing happened to the institutional

structure of insurance it remained a monopoly Only in 1999 a new legislation came into

effect signaling a change in the insurance industry structure It was examined that what might

happen in the future when the domestic private insurance companies are allowed to compete

with some foreign participation Because of the time dependence of insurance contracts it is

highly unlikely that these erstwhile monopolies are going to disappear

Baranoff Etti G Sager Thomas W (2002) explained the impact of life risk based capital

(RBC) regulation on relation between capital and risk in the life insurance industry To

examine this issue simultaneous equation partial adjustment model was used Three

equations which express the interrelations among capital and two measures of risk (product

58

risk and asset risk) were used The asset-risk measure used in this paper reflects credit or

solvency risk as in RBC Product risk assessment for life insurance products is rationalized

by transaction cost economics contractual uncertainty A significant finding is that for life

insurers the relation between capital and asset risk is positive This agrees with prior studies

for the propertycasualty insurance industry and some banking studies But the relation

between capital and product risk is negative This is consistent with the hypothesized impact

of guarantee funds in other studies The contrast between the positive relation of capital to

asset risk and the negative relation of capital to product risk underscores the importance of

distinguishing these two components of risk

Adams Mike and Philip Hardwick (2003) stated that the insurance industry claims tend to

constitute the major proportion of total annual outgoings across almost all product lines The

study develops a cost function of insurance claims and applies the model to 1988-93 data

from the United Kingdom and New Zealand life insurance industry It found a similar set of

results for the two countries In general the results support the hypothesis that larger life

insurance firms on average face bigger claims to premium ratios than smaller life

insurance firms The evidence concerning the relationships between claims the

composition of output between claims and the degree of reinsurance is mixed but there is

clear support for the view that stock firms have a less severe claims experience than

mutuals It was concluded that the model provides intuitive insights into the determinants

of insurance claims which could help to stimulate and direct further research

Hautcoer Pierre Cyrille (2004) revealed that the French life insurance industry remained

underdeveloped in comparison with other countries of similar financial development during

the period between 1870 and 1939 The study explained that the wide fluctuations in the

insurance industry are the outcomes of technical peculiarities and their interaction with

macroeconomic fluctuations Nevertheless these fluctuations are not sufficient to explain

the industryrsquos long term stagnation Low returns to clients were mainly due to their

conservative investment strategy It was suggested to impose regulations and barriers to

access of competitors to the market This will lead to maintaining a hold on a small but very

profitable market

Paul J M Klumpes (2004) applied performance benchmarking to measure the profit

and cost efficiency of UK life insurance products These products are required to be

59

distributed through either independent financial advisers (IFA) or appointed andor company

representatives (ARCR) as per polarization regulations Relative profit and cost efficiencies

are assessed using the fourier flexible form of econometric procedure and are based on

detailed product level disclosure information United Kingdom life insurance firms

employing IFA distribution systems are found to be more cost and profit inefficient than

ARCR firms

Ennsfellner Karl C Danielle Lewis Randy L Anderson (2004) examines the

developments in the production efficiency of the Austrian insurance market for the

period 1994-1999 using firm-specific data on lifehealth and non-life insurers obtained

from the Austrian Insurance Regulatory Authority The article uses a Bayesian stochastic

frontier to obtain aggregate and firm specific estimates of production efficiency The

study provides strong evidence that the process of deregulation had positive effects on the

production efficiency of Austrian insurers The lifehealth and non-life firms showed

similar patterns of development in that they were less efficient during the years 1994-

1996 and significantly more efficient in 1997-1999 If the Austrian experience is

representative similar benefits from deregulation may be expected for the Central and

Eastern European countries that prepare for the accession to the European Union

Tone Kaoru Biresh K Sahoo (2005) applies a new variant of data envelopment

analysis model to examine the performance of Life Insurance Corporation (LIC) of India

for a period of nineteen years The findings show significant heterogeneity in the cost

efficiency scores over the observation period A decline in performance after 1994ndash1995

may be due to the huge initial fixed cost undertaken by LIC in modernizing its

operations A significant increase in cost efficiency in 2000ndash2001 may prove to be a

cause for optimism that LIC may now be realizing a benefit from such modernization

James CJ Hao Lin Yhi Chou (2005) estimated the translog cost function for twenty-six

life insurance companies using data for twenty three years (1977ndash1999) The distribution

free approach (DFA) and Battese and Coelli (DFP) model was employed to estimate

inefficiency Then the constants or residuals were tested to see the relation of so called X

efficiencies with market share diversified product strategy scale efficiency and market

growth ratio and in the results efficiency was found to be related with the occurrence of

market share diversification products strategy and scale efficiency

60

Palli Madhuka (2006) measured a life assurance security gap to examine the extent of

underinsured people This gap is computed as the mean ratio of recommended insurance and

actual insurance to household earnings The research provides estimates of the life insurance

gap to maintain living standards of dependents after death of the primary wage earner It is

because inadequate protected families put burden of their welfare on public resources The

primary drivers of demand for risk security are age income affordability wealth and desire

to protect income from inflation Though aggregate demand is driven by these factors various

researches have shown that there is little correlation between a specific familys need for security

and its actual purchase of insurance According to one estimate mentioned in sigma in the

event of a spouses death nearly one third of secondary earners between the ages of twenty two

to thirty nine would suffer at least a decline of forty percent in their standard of living

Sherries Micheal (2006) explains the linkage between solvency capital allocation and fair

rate of return in insurance A method to allocate capital in insurance business is developed

based on an economic definition of solvency and the market value of the insurer balance

sheet Solvency and its financial impact are determined by the value of the insolvency

exchange option The allocation of capital is determined using a complete markets arbitrage

free model and consistency in allocated capital with the economic value of the balance sheet

assets and liabilities is observed as a result

Yang Zijiang (2006) conducted a study in order to know how to achieve efficiency

systematically for the Canadian life and health insurance industry For this purpose an

integrated approach of production and investment performance for the insurers was used

which provided management overall performance evaluation A two stage data envelopment

analysis model was created to provide valuable managerial insights when assessing the dual

impacts of operating and business strategies for the industry The results showed that the

Canadian life and health insurance industry operated fairly efficiently during the period

examined (the year 1998) In addition the scale efficiency was also found in this study

Sinha Ram Pratap (2007) compared thirteen life insurance companies in respect of

technical efficiency for the period 2002-2003 to 2005- 2006 using the assurance region

approach of DEA The comparison of mean technical efficiency scores reveal that mean

technical efficiency has improved in 2003-2004 relative to 2002-2003 remained on the same

level in 2004-2005 and declined in 2005-2006 This is likely because of divergence in the

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

53

has characteristics similar to a gambling contract because the amount of coverage does not

depend on the value of the wage claim

Mary A Weiss (1986) illustrated a method for measuring productivity for life insurers

New techniques for measuring output of life insurers were developed and it was developed

using total factor productivity approach for two sample insurers ie stock and mutual

insurer for five year intervals The applicability of the output and productivity

measurement methodologies developed is not limited to the specific insurers studied but

rather can be used as a guide in measuring the productivity of any life insurer or the life

insurance industry in general

Martin F Grace and S t eph en G Timme (1992) reported estimates of overall

a n d product specific scale economies using sample of four hundred and twenty three U S

life insurers The study suggested that the magnitude of scale economies and cost

complementarities may vary with the scale and mix of outputs In contrast previous

studies only provide a single point estimate of industry cost characteristics us in g the

sample mean output vector This study therefore provides a more complete

representation of the industryrsquos cost characteristic and in turn new insights into decisions

related to the optimal scale and mix of outputs

Duane B Graddy Ghassem Homaifar Kenneth W Hollman (1992)

analyzed the market response of stock returns of insurers to the formulation debate and

enactment of the Tax Reform Act of 1986 Provisions of the Tax Reform Act showed

increases in the effective tax rates of insurers despite the proposed lowering of

marginal rates The stock prices of insurers reacted negatively in the formulation Debate

and Committee mark up phases of the legislative process Significant abnormal returns

were not evidenced in the enactment phase

Mayers David and C l i f f o rd W Smith Jr (1992) found that the compensation of

mutual executives and mutual subsidiary executives is lower than that of stock executives

and stock subsidiary executives in life insurance industry Moreover the compensation of

mutual executives is less responsive to firm performance than that of stock executives

This evidence is consistent with the existence of differences in corporate investment

opportunity sets and resulting differences in required managerial discretion between

mutual and stock life insurance companies

54

Akhigbe Aigbe Stephen FBorde Jeff Madura (1993) measured the share price response

of insurers to increase in the dividend and matched control samples of banks and industrial

firms that are similarly assessed It was found that the share price response for insurers is

positive and significant The magnitude of the response for life insurers is smaller than that

of other types of insurers or industrial companies but is greater than that of banks This

result may be due to the relatively low level of capital maintained by life insurers A cross-

sectional analysis also suggested that the share price responses across insurers are not

related to firm-specific characteristics

Adams Mike (1997) examined empirically the determinants of audit committee formulation

in life insurance firms The study tested six hypotheses namely whether the existence of

audit committees is related to organizational form firm size leverage asset in place

reinsurance and total monitoring costs using pooled 1991-1993 data from New Zealandrsquos life

insurance industry Fixed effects regression was used to arrive at parametric estimates The

results indicated that consistent with expectations audit committees appear to be positively

associated with large entities high leverage companies and firms with high total monitoring

expenditures However the variables such as organizational form assets in place and

reinsurance were not found statistically significant Thus the study provides mixed empirical

results

Hirofumi Fukuyama (1997) investigates productive efficiency and productivity changes

of Japanese life insurance companies by focusing primarily on the ownership structures

(mutual and stock) and economic conditions (expansion and recession) The study indicates

that mutual and stock companies possess identical technologies despite differences in

incentives of managers and in legal form but productive efficiency and productivity

performances differ from time to time across the two ownership types under different

economic conditions

Adams Mike Hossain Mahmud (1998) explained differences in the level of information

which is being disclosed voluntarily by life insurance companies in their annual reports The

study thus specified the relation between voluntary disclosure and eight explanatory variables

representing major construct of the managerial discretion hypothesis in the form of fixed

effects regression model The data for the year 1988 to 1993 was drawn from New Zealandrsquos

55

life insurance industry It was found that the organizational form firm size product diversity

and distribution system are positively related to the level of voluntary disclosure as implied

by the managerial discretion hypothesis Non executive directors and reinsurers are those two

independent variables which were observed to be significant in opposite direction

Ranade Ajit and Rajeev Ahuja (1999 presented an overview of life insurance

operations in India and identified the emerging strategic issues in the light of

liberalization and the impending private sector entry into insurance The need for

private sector entry has been justified on the basis of enhancing the efficiency of

operations achieving a greater density and penetration of life insurance in the

country and for greater mobilization of long terms savings for long gestation

infrastructure projects In the wake of such coming competition the LIC with its 40

years of experience and wide reach is at an advantageous position However unless it

addresses strategic issues such as changing demography and demand for pensions

demand for a wider variety of products and having greater freedom in its investments

LIC may find it difficult to adapt to liberalized scenario

Pant Niranjan (1999) by considering the impact of liberalization and Insurance Bill 1999 on

insurance sector stated that this would result in increasing involvement of the large and

powerful insurance companies of the world in the Indian insurance industry The effect was

uncertain as this could work as an opportunity as well as a challenge for the life insurers So

it was stressed that it is essential to take this in an encouraging manner for turning this

involvement of private sector players into a positive factor of overall growth It was

also mentioned that such an effort would however require the support of a clearer and

more cogent legislation than the Insurance Regulation and Development Bill 1999

Rao D Tripati (1999) developed a proper perspective of the ongoing debates on the

privatisation and globalisation of the insurance sector A systematic study of the structure

and pattern of growth of the Indian insurance industry is essential An analysis of

pattern of growth of life insurance industry since its nationalisation in 1956 has been

carried out This article goes into the operating results of the Life Insurance Corporation

and their macro economic importance The study highlighted the pattern and growth of

life insurance business in India Specifically it deals with the analysis of growth of new

business business in force income and outgo (financial outflow) Life Fund ie

56

institutionalisation of savings and business by different zones of LIC Finally these

indicators a re compared with the related macro variables The analysis reveals that average

sum assured per policy has declined in real terms The increase in the rural business might

involve higher transaction costs in the absence of adequate infrastructure facilities in rural

areas But income and outgo has shown that even with lower sum assured and increase in

rural business the LIC has succeeded in converting a growing amount of annual premium

income in to life insurance fund The outgo as a proportion of income declined partly due to

the decline in death benefits and expense in management

Yates Jo Anne (1999) examined the early adoption and use of computers by life insurance

companies in 1950rsquos using Anthony Giddens Structuration Theory as theoretical lens It

helped to know how pre computer punched card tabulating technology was used in

insurance operations and use of computers in early computer era Most of the times it leads

to expect the reinforcement of existing structures It is also helpful in understanding the new

ways and innovative uses of computer technology in insurance

Grosen Anders Peter Lochte Jorgensen (1999) analyzed one of the most common life

insurance products ie participating (or with profits) policy and showed that the typical

participating policy can be decomposed into a risk free bond element a bonus option and a

surrender option A dynamic model was constructed in which these elements can be valued

separately using contingent claims analysis The impact of various bonus policies and various

levels of the guaranteed interest rate was analyzed numerically and it was found that values

of participating policies were highly sensitive to the bonus policy that surrender options can

be quite valuable and that LIC solvency can be quickly jeopardized if earning opportunities

deteriorate in a situation where bonus reserves are low and promised returns are high

Cummins J David Sharon Tennyson and Mary A Weiss (1999) examined the

relationship between mergers and acquisitions efficiency and scale economies in the US life

insurance industry Cost and revenue efficiency was estimated for the period of 1988-1995

using data envelopment analysis (DEA) The Malmquist methodology is used to measure

changes in efficiency over time It was found that acquired firms achieve greater efficiency

gains than firms that have not been involved in mergers and acquisitions Firms operating

with non decreasing returns to scale and financially vulnerable firms are more likely to be

acquisition targets Overall mergers and acquisitions in the life insurance industry have had

57

a beneficial effect on efficiency

Segal Dan (2000) estimated the acquisition and maintenance costs associated with life

policies as a function of the amount of insurance and number of policies of an insurer by

estimating a cost function The final sample consists of 448 firms and the study period

includes years from 1995 to 1998 Several statistical characteristics of the costs such as

mean and median of the sample were examined The data indicates that there is a large

variation among life insurance companies It was found that the costs associated with life

policies of the largest insurers are much higher than the corresponding costs of other firms

Comparing the costs between ldquobranch firmsrdquo and non-branch firmsrdquo it was revealed that the

costs of branch firms are generally higher than that of non branch firms

Rao D Tripati (2000) explained the macroeconomic implications of privatization and

foreign participation in the insurance sector It was obtained that the Life Insurance

Corporation (LIC) of India is dominant in the overall industry in two aspects pooling

and redistributing risks across millions of policyholders and in performance of financial

intermediation Therefore the issue of privatization and foreign participation must be

approached cautiously with a step by step approach and should be preceded by

microeconomic institutional and legal reforms

Sinha Tapen (2002) examined the institution of insurance in India Over the past century

Indian insurance industry has experienced big changes It started as a fully private system

with no restriction on foreign participation After the independence the industry went to the

other extreme It became a state owned monopoly In 1991 when rapid economic changes

took place in many parts of the Indian economy nothing happened to the institutional

structure of insurance it remained a monopoly Only in 1999 a new legislation came into

effect signaling a change in the insurance industry structure It was examined that what might

happen in the future when the domestic private insurance companies are allowed to compete

with some foreign participation Because of the time dependence of insurance contracts it is

highly unlikely that these erstwhile monopolies are going to disappear

Baranoff Etti G Sager Thomas W (2002) explained the impact of life risk based capital

(RBC) regulation on relation between capital and risk in the life insurance industry To

examine this issue simultaneous equation partial adjustment model was used Three

equations which express the interrelations among capital and two measures of risk (product

58

risk and asset risk) were used The asset-risk measure used in this paper reflects credit or

solvency risk as in RBC Product risk assessment for life insurance products is rationalized

by transaction cost economics contractual uncertainty A significant finding is that for life

insurers the relation between capital and asset risk is positive This agrees with prior studies

for the propertycasualty insurance industry and some banking studies But the relation

between capital and product risk is negative This is consistent with the hypothesized impact

of guarantee funds in other studies The contrast between the positive relation of capital to

asset risk and the negative relation of capital to product risk underscores the importance of

distinguishing these two components of risk

Adams Mike and Philip Hardwick (2003) stated that the insurance industry claims tend to

constitute the major proportion of total annual outgoings across almost all product lines The

study develops a cost function of insurance claims and applies the model to 1988-93 data

from the United Kingdom and New Zealand life insurance industry It found a similar set of

results for the two countries In general the results support the hypothesis that larger life

insurance firms on average face bigger claims to premium ratios than smaller life

insurance firms The evidence concerning the relationships between claims the

composition of output between claims and the degree of reinsurance is mixed but there is

clear support for the view that stock firms have a less severe claims experience than

mutuals It was concluded that the model provides intuitive insights into the determinants

of insurance claims which could help to stimulate and direct further research

Hautcoer Pierre Cyrille (2004) revealed that the French life insurance industry remained

underdeveloped in comparison with other countries of similar financial development during

the period between 1870 and 1939 The study explained that the wide fluctuations in the

insurance industry are the outcomes of technical peculiarities and their interaction with

macroeconomic fluctuations Nevertheless these fluctuations are not sufficient to explain

the industryrsquos long term stagnation Low returns to clients were mainly due to their

conservative investment strategy It was suggested to impose regulations and barriers to

access of competitors to the market This will lead to maintaining a hold on a small but very

profitable market

Paul J M Klumpes (2004) applied performance benchmarking to measure the profit

and cost efficiency of UK life insurance products These products are required to be

59

distributed through either independent financial advisers (IFA) or appointed andor company

representatives (ARCR) as per polarization regulations Relative profit and cost efficiencies

are assessed using the fourier flexible form of econometric procedure and are based on

detailed product level disclosure information United Kingdom life insurance firms

employing IFA distribution systems are found to be more cost and profit inefficient than

ARCR firms

Ennsfellner Karl C Danielle Lewis Randy L Anderson (2004) examines the

developments in the production efficiency of the Austrian insurance market for the

period 1994-1999 using firm-specific data on lifehealth and non-life insurers obtained

from the Austrian Insurance Regulatory Authority The article uses a Bayesian stochastic

frontier to obtain aggregate and firm specific estimates of production efficiency The

study provides strong evidence that the process of deregulation had positive effects on the

production efficiency of Austrian insurers The lifehealth and non-life firms showed

similar patterns of development in that they were less efficient during the years 1994-

1996 and significantly more efficient in 1997-1999 If the Austrian experience is

representative similar benefits from deregulation may be expected for the Central and

Eastern European countries that prepare for the accession to the European Union

Tone Kaoru Biresh K Sahoo (2005) applies a new variant of data envelopment

analysis model to examine the performance of Life Insurance Corporation (LIC) of India

for a period of nineteen years The findings show significant heterogeneity in the cost

efficiency scores over the observation period A decline in performance after 1994ndash1995

may be due to the huge initial fixed cost undertaken by LIC in modernizing its

operations A significant increase in cost efficiency in 2000ndash2001 may prove to be a

cause for optimism that LIC may now be realizing a benefit from such modernization

James CJ Hao Lin Yhi Chou (2005) estimated the translog cost function for twenty-six

life insurance companies using data for twenty three years (1977ndash1999) The distribution

free approach (DFA) and Battese and Coelli (DFP) model was employed to estimate

inefficiency Then the constants or residuals were tested to see the relation of so called X

efficiencies with market share diversified product strategy scale efficiency and market

growth ratio and in the results efficiency was found to be related with the occurrence of

market share diversification products strategy and scale efficiency

60

Palli Madhuka (2006) measured a life assurance security gap to examine the extent of

underinsured people This gap is computed as the mean ratio of recommended insurance and

actual insurance to household earnings The research provides estimates of the life insurance

gap to maintain living standards of dependents after death of the primary wage earner It is

because inadequate protected families put burden of their welfare on public resources The

primary drivers of demand for risk security are age income affordability wealth and desire

to protect income from inflation Though aggregate demand is driven by these factors various

researches have shown that there is little correlation between a specific familys need for security

and its actual purchase of insurance According to one estimate mentioned in sigma in the

event of a spouses death nearly one third of secondary earners between the ages of twenty two

to thirty nine would suffer at least a decline of forty percent in their standard of living

Sherries Micheal (2006) explains the linkage between solvency capital allocation and fair

rate of return in insurance A method to allocate capital in insurance business is developed

based on an economic definition of solvency and the market value of the insurer balance

sheet Solvency and its financial impact are determined by the value of the insolvency

exchange option The allocation of capital is determined using a complete markets arbitrage

free model and consistency in allocated capital with the economic value of the balance sheet

assets and liabilities is observed as a result

Yang Zijiang (2006) conducted a study in order to know how to achieve efficiency

systematically for the Canadian life and health insurance industry For this purpose an

integrated approach of production and investment performance for the insurers was used

which provided management overall performance evaluation A two stage data envelopment

analysis model was created to provide valuable managerial insights when assessing the dual

impacts of operating and business strategies for the industry The results showed that the

Canadian life and health insurance industry operated fairly efficiently during the period

examined (the year 1998) In addition the scale efficiency was also found in this study

Sinha Ram Pratap (2007) compared thirteen life insurance companies in respect of

technical efficiency for the period 2002-2003 to 2005- 2006 using the assurance region

approach of DEA The comparison of mean technical efficiency scores reveal that mean

technical efficiency has improved in 2003-2004 relative to 2002-2003 remained on the same

level in 2004-2005 and declined in 2005-2006 This is likely because of divergence in the

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

54

Akhigbe Aigbe Stephen FBorde Jeff Madura (1993) measured the share price response

of insurers to increase in the dividend and matched control samples of banks and industrial

firms that are similarly assessed It was found that the share price response for insurers is

positive and significant The magnitude of the response for life insurers is smaller than that

of other types of insurers or industrial companies but is greater than that of banks This

result may be due to the relatively low level of capital maintained by life insurers A cross-

sectional analysis also suggested that the share price responses across insurers are not

related to firm-specific characteristics

Adams Mike (1997) examined empirically the determinants of audit committee formulation

in life insurance firms The study tested six hypotheses namely whether the existence of

audit committees is related to organizational form firm size leverage asset in place

reinsurance and total monitoring costs using pooled 1991-1993 data from New Zealandrsquos life

insurance industry Fixed effects regression was used to arrive at parametric estimates The

results indicated that consistent with expectations audit committees appear to be positively

associated with large entities high leverage companies and firms with high total monitoring

expenditures However the variables such as organizational form assets in place and

reinsurance were not found statistically significant Thus the study provides mixed empirical

results

Hirofumi Fukuyama (1997) investigates productive efficiency and productivity changes

of Japanese life insurance companies by focusing primarily on the ownership structures

(mutual and stock) and economic conditions (expansion and recession) The study indicates

that mutual and stock companies possess identical technologies despite differences in

incentives of managers and in legal form but productive efficiency and productivity

performances differ from time to time across the two ownership types under different

economic conditions

Adams Mike Hossain Mahmud (1998) explained differences in the level of information

which is being disclosed voluntarily by life insurance companies in their annual reports The

study thus specified the relation between voluntary disclosure and eight explanatory variables

representing major construct of the managerial discretion hypothesis in the form of fixed

effects regression model The data for the year 1988 to 1993 was drawn from New Zealandrsquos

55

life insurance industry It was found that the organizational form firm size product diversity

and distribution system are positively related to the level of voluntary disclosure as implied

by the managerial discretion hypothesis Non executive directors and reinsurers are those two

independent variables which were observed to be significant in opposite direction

Ranade Ajit and Rajeev Ahuja (1999 presented an overview of life insurance

operations in India and identified the emerging strategic issues in the light of

liberalization and the impending private sector entry into insurance The need for

private sector entry has been justified on the basis of enhancing the efficiency of

operations achieving a greater density and penetration of life insurance in the

country and for greater mobilization of long terms savings for long gestation

infrastructure projects In the wake of such coming competition the LIC with its 40

years of experience and wide reach is at an advantageous position However unless it

addresses strategic issues such as changing demography and demand for pensions

demand for a wider variety of products and having greater freedom in its investments

LIC may find it difficult to adapt to liberalized scenario

Pant Niranjan (1999) by considering the impact of liberalization and Insurance Bill 1999 on

insurance sector stated that this would result in increasing involvement of the large and

powerful insurance companies of the world in the Indian insurance industry The effect was

uncertain as this could work as an opportunity as well as a challenge for the life insurers So

it was stressed that it is essential to take this in an encouraging manner for turning this

involvement of private sector players into a positive factor of overall growth It was

also mentioned that such an effort would however require the support of a clearer and

more cogent legislation than the Insurance Regulation and Development Bill 1999

Rao D Tripati (1999) developed a proper perspective of the ongoing debates on the

privatisation and globalisation of the insurance sector A systematic study of the structure

and pattern of growth of the Indian insurance industry is essential An analysis of

pattern of growth of life insurance industry since its nationalisation in 1956 has been

carried out This article goes into the operating results of the Life Insurance Corporation

and their macro economic importance The study highlighted the pattern and growth of

life insurance business in India Specifically it deals with the analysis of growth of new

business business in force income and outgo (financial outflow) Life Fund ie

56

institutionalisation of savings and business by different zones of LIC Finally these

indicators a re compared with the related macro variables The analysis reveals that average

sum assured per policy has declined in real terms The increase in the rural business might

involve higher transaction costs in the absence of adequate infrastructure facilities in rural

areas But income and outgo has shown that even with lower sum assured and increase in

rural business the LIC has succeeded in converting a growing amount of annual premium

income in to life insurance fund The outgo as a proportion of income declined partly due to

the decline in death benefits and expense in management

Yates Jo Anne (1999) examined the early adoption and use of computers by life insurance

companies in 1950rsquos using Anthony Giddens Structuration Theory as theoretical lens It

helped to know how pre computer punched card tabulating technology was used in

insurance operations and use of computers in early computer era Most of the times it leads

to expect the reinforcement of existing structures It is also helpful in understanding the new

ways and innovative uses of computer technology in insurance

Grosen Anders Peter Lochte Jorgensen (1999) analyzed one of the most common life

insurance products ie participating (or with profits) policy and showed that the typical

participating policy can be decomposed into a risk free bond element a bonus option and a

surrender option A dynamic model was constructed in which these elements can be valued

separately using contingent claims analysis The impact of various bonus policies and various

levels of the guaranteed interest rate was analyzed numerically and it was found that values

of participating policies were highly sensitive to the bonus policy that surrender options can

be quite valuable and that LIC solvency can be quickly jeopardized if earning opportunities

deteriorate in a situation where bonus reserves are low and promised returns are high

Cummins J David Sharon Tennyson and Mary A Weiss (1999) examined the

relationship between mergers and acquisitions efficiency and scale economies in the US life

insurance industry Cost and revenue efficiency was estimated for the period of 1988-1995

using data envelopment analysis (DEA) The Malmquist methodology is used to measure

changes in efficiency over time It was found that acquired firms achieve greater efficiency

gains than firms that have not been involved in mergers and acquisitions Firms operating

with non decreasing returns to scale and financially vulnerable firms are more likely to be

acquisition targets Overall mergers and acquisitions in the life insurance industry have had

57

a beneficial effect on efficiency

Segal Dan (2000) estimated the acquisition and maintenance costs associated with life

policies as a function of the amount of insurance and number of policies of an insurer by

estimating a cost function The final sample consists of 448 firms and the study period

includes years from 1995 to 1998 Several statistical characteristics of the costs such as

mean and median of the sample were examined The data indicates that there is a large

variation among life insurance companies It was found that the costs associated with life

policies of the largest insurers are much higher than the corresponding costs of other firms

Comparing the costs between ldquobranch firmsrdquo and non-branch firmsrdquo it was revealed that the

costs of branch firms are generally higher than that of non branch firms

Rao D Tripati (2000) explained the macroeconomic implications of privatization and

foreign participation in the insurance sector It was obtained that the Life Insurance

Corporation (LIC) of India is dominant in the overall industry in two aspects pooling

and redistributing risks across millions of policyholders and in performance of financial

intermediation Therefore the issue of privatization and foreign participation must be

approached cautiously with a step by step approach and should be preceded by

microeconomic institutional and legal reforms

Sinha Tapen (2002) examined the institution of insurance in India Over the past century

Indian insurance industry has experienced big changes It started as a fully private system

with no restriction on foreign participation After the independence the industry went to the

other extreme It became a state owned monopoly In 1991 when rapid economic changes

took place in many parts of the Indian economy nothing happened to the institutional

structure of insurance it remained a monopoly Only in 1999 a new legislation came into

effect signaling a change in the insurance industry structure It was examined that what might

happen in the future when the domestic private insurance companies are allowed to compete

with some foreign participation Because of the time dependence of insurance contracts it is

highly unlikely that these erstwhile monopolies are going to disappear

Baranoff Etti G Sager Thomas W (2002) explained the impact of life risk based capital

(RBC) regulation on relation between capital and risk in the life insurance industry To

examine this issue simultaneous equation partial adjustment model was used Three

equations which express the interrelations among capital and two measures of risk (product

58

risk and asset risk) were used The asset-risk measure used in this paper reflects credit or

solvency risk as in RBC Product risk assessment for life insurance products is rationalized

by transaction cost economics contractual uncertainty A significant finding is that for life

insurers the relation between capital and asset risk is positive This agrees with prior studies

for the propertycasualty insurance industry and some banking studies But the relation

between capital and product risk is negative This is consistent with the hypothesized impact

of guarantee funds in other studies The contrast between the positive relation of capital to

asset risk and the negative relation of capital to product risk underscores the importance of

distinguishing these two components of risk

Adams Mike and Philip Hardwick (2003) stated that the insurance industry claims tend to

constitute the major proportion of total annual outgoings across almost all product lines The

study develops a cost function of insurance claims and applies the model to 1988-93 data

from the United Kingdom and New Zealand life insurance industry It found a similar set of

results for the two countries In general the results support the hypothesis that larger life

insurance firms on average face bigger claims to premium ratios than smaller life

insurance firms The evidence concerning the relationships between claims the

composition of output between claims and the degree of reinsurance is mixed but there is

clear support for the view that stock firms have a less severe claims experience than

mutuals It was concluded that the model provides intuitive insights into the determinants

of insurance claims which could help to stimulate and direct further research

Hautcoer Pierre Cyrille (2004) revealed that the French life insurance industry remained

underdeveloped in comparison with other countries of similar financial development during

the period between 1870 and 1939 The study explained that the wide fluctuations in the

insurance industry are the outcomes of technical peculiarities and their interaction with

macroeconomic fluctuations Nevertheless these fluctuations are not sufficient to explain

the industryrsquos long term stagnation Low returns to clients were mainly due to their

conservative investment strategy It was suggested to impose regulations and barriers to

access of competitors to the market This will lead to maintaining a hold on a small but very

profitable market

Paul J M Klumpes (2004) applied performance benchmarking to measure the profit

and cost efficiency of UK life insurance products These products are required to be

59

distributed through either independent financial advisers (IFA) or appointed andor company

representatives (ARCR) as per polarization regulations Relative profit and cost efficiencies

are assessed using the fourier flexible form of econometric procedure and are based on

detailed product level disclosure information United Kingdom life insurance firms

employing IFA distribution systems are found to be more cost and profit inefficient than

ARCR firms

Ennsfellner Karl C Danielle Lewis Randy L Anderson (2004) examines the

developments in the production efficiency of the Austrian insurance market for the

period 1994-1999 using firm-specific data on lifehealth and non-life insurers obtained

from the Austrian Insurance Regulatory Authority The article uses a Bayesian stochastic

frontier to obtain aggregate and firm specific estimates of production efficiency The

study provides strong evidence that the process of deregulation had positive effects on the

production efficiency of Austrian insurers The lifehealth and non-life firms showed

similar patterns of development in that they were less efficient during the years 1994-

1996 and significantly more efficient in 1997-1999 If the Austrian experience is

representative similar benefits from deregulation may be expected for the Central and

Eastern European countries that prepare for the accession to the European Union

Tone Kaoru Biresh K Sahoo (2005) applies a new variant of data envelopment

analysis model to examine the performance of Life Insurance Corporation (LIC) of India

for a period of nineteen years The findings show significant heterogeneity in the cost

efficiency scores over the observation period A decline in performance after 1994ndash1995

may be due to the huge initial fixed cost undertaken by LIC in modernizing its

operations A significant increase in cost efficiency in 2000ndash2001 may prove to be a

cause for optimism that LIC may now be realizing a benefit from such modernization

James CJ Hao Lin Yhi Chou (2005) estimated the translog cost function for twenty-six

life insurance companies using data for twenty three years (1977ndash1999) The distribution

free approach (DFA) and Battese and Coelli (DFP) model was employed to estimate

inefficiency Then the constants or residuals were tested to see the relation of so called X

efficiencies with market share diversified product strategy scale efficiency and market

growth ratio and in the results efficiency was found to be related with the occurrence of

market share diversification products strategy and scale efficiency

60

Palli Madhuka (2006) measured a life assurance security gap to examine the extent of

underinsured people This gap is computed as the mean ratio of recommended insurance and

actual insurance to household earnings The research provides estimates of the life insurance

gap to maintain living standards of dependents after death of the primary wage earner It is

because inadequate protected families put burden of their welfare on public resources The

primary drivers of demand for risk security are age income affordability wealth and desire

to protect income from inflation Though aggregate demand is driven by these factors various

researches have shown that there is little correlation between a specific familys need for security

and its actual purchase of insurance According to one estimate mentioned in sigma in the

event of a spouses death nearly one third of secondary earners between the ages of twenty two

to thirty nine would suffer at least a decline of forty percent in their standard of living

Sherries Micheal (2006) explains the linkage between solvency capital allocation and fair

rate of return in insurance A method to allocate capital in insurance business is developed

based on an economic definition of solvency and the market value of the insurer balance

sheet Solvency and its financial impact are determined by the value of the insolvency

exchange option The allocation of capital is determined using a complete markets arbitrage

free model and consistency in allocated capital with the economic value of the balance sheet

assets and liabilities is observed as a result

Yang Zijiang (2006) conducted a study in order to know how to achieve efficiency

systematically for the Canadian life and health insurance industry For this purpose an

integrated approach of production and investment performance for the insurers was used

which provided management overall performance evaluation A two stage data envelopment

analysis model was created to provide valuable managerial insights when assessing the dual

impacts of operating and business strategies for the industry The results showed that the

Canadian life and health insurance industry operated fairly efficiently during the period

examined (the year 1998) In addition the scale efficiency was also found in this study

Sinha Ram Pratap (2007) compared thirteen life insurance companies in respect of

technical efficiency for the period 2002-2003 to 2005- 2006 using the assurance region

approach of DEA The comparison of mean technical efficiency scores reveal that mean

technical efficiency has improved in 2003-2004 relative to 2002-2003 remained on the same

level in 2004-2005 and declined in 2005-2006 This is likely because of divergence in the

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

55

life insurance industry It was found that the organizational form firm size product diversity

and distribution system are positively related to the level of voluntary disclosure as implied

by the managerial discretion hypothesis Non executive directors and reinsurers are those two

independent variables which were observed to be significant in opposite direction

Ranade Ajit and Rajeev Ahuja (1999 presented an overview of life insurance

operations in India and identified the emerging strategic issues in the light of

liberalization and the impending private sector entry into insurance The need for

private sector entry has been justified on the basis of enhancing the efficiency of

operations achieving a greater density and penetration of life insurance in the

country and for greater mobilization of long terms savings for long gestation

infrastructure projects In the wake of such coming competition the LIC with its 40

years of experience and wide reach is at an advantageous position However unless it

addresses strategic issues such as changing demography and demand for pensions

demand for a wider variety of products and having greater freedom in its investments

LIC may find it difficult to adapt to liberalized scenario

Pant Niranjan (1999) by considering the impact of liberalization and Insurance Bill 1999 on

insurance sector stated that this would result in increasing involvement of the large and

powerful insurance companies of the world in the Indian insurance industry The effect was

uncertain as this could work as an opportunity as well as a challenge for the life insurers So

it was stressed that it is essential to take this in an encouraging manner for turning this

involvement of private sector players into a positive factor of overall growth It was

also mentioned that such an effort would however require the support of a clearer and

more cogent legislation than the Insurance Regulation and Development Bill 1999

Rao D Tripati (1999) developed a proper perspective of the ongoing debates on the

privatisation and globalisation of the insurance sector A systematic study of the structure

and pattern of growth of the Indian insurance industry is essential An analysis of

pattern of growth of life insurance industry since its nationalisation in 1956 has been

carried out This article goes into the operating results of the Life Insurance Corporation

and their macro economic importance The study highlighted the pattern and growth of

life insurance business in India Specifically it deals with the analysis of growth of new

business business in force income and outgo (financial outflow) Life Fund ie

56

institutionalisation of savings and business by different zones of LIC Finally these

indicators a re compared with the related macro variables The analysis reveals that average

sum assured per policy has declined in real terms The increase in the rural business might

involve higher transaction costs in the absence of adequate infrastructure facilities in rural

areas But income and outgo has shown that even with lower sum assured and increase in

rural business the LIC has succeeded in converting a growing amount of annual premium

income in to life insurance fund The outgo as a proportion of income declined partly due to

the decline in death benefits and expense in management

Yates Jo Anne (1999) examined the early adoption and use of computers by life insurance

companies in 1950rsquos using Anthony Giddens Structuration Theory as theoretical lens It

helped to know how pre computer punched card tabulating technology was used in

insurance operations and use of computers in early computer era Most of the times it leads

to expect the reinforcement of existing structures It is also helpful in understanding the new

ways and innovative uses of computer technology in insurance

Grosen Anders Peter Lochte Jorgensen (1999) analyzed one of the most common life

insurance products ie participating (or with profits) policy and showed that the typical

participating policy can be decomposed into a risk free bond element a bonus option and a

surrender option A dynamic model was constructed in which these elements can be valued

separately using contingent claims analysis The impact of various bonus policies and various

levels of the guaranteed interest rate was analyzed numerically and it was found that values

of participating policies were highly sensitive to the bonus policy that surrender options can

be quite valuable and that LIC solvency can be quickly jeopardized if earning opportunities

deteriorate in a situation where bonus reserves are low and promised returns are high

Cummins J David Sharon Tennyson and Mary A Weiss (1999) examined the

relationship between mergers and acquisitions efficiency and scale economies in the US life

insurance industry Cost and revenue efficiency was estimated for the period of 1988-1995

using data envelopment analysis (DEA) The Malmquist methodology is used to measure

changes in efficiency over time It was found that acquired firms achieve greater efficiency

gains than firms that have not been involved in mergers and acquisitions Firms operating

with non decreasing returns to scale and financially vulnerable firms are more likely to be

acquisition targets Overall mergers and acquisitions in the life insurance industry have had

57

a beneficial effect on efficiency

Segal Dan (2000) estimated the acquisition and maintenance costs associated with life

policies as a function of the amount of insurance and number of policies of an insurer by

estimating a cost function The final sample consists of 448 firms and the study period

includes years from 1995 to 1998 Several statistical characteristics of the costs such as

mean and median of the sample were examined The data indicates that there is a large

variation among life insurance companies It was found that the costs associated with life

policies of the largest insurers are much higher than the corresponding costs of other firms

Comparing the costs between ldquobranch firmsrdquo and non-branch firmsrdquo it was revealed that the

costs of branch firms are generally higher than that of non branch firms

Rao D Tripati (2000) explained the macroeconomic implications of privatization and

foreign participation in the insurance sector It was obtained that the Life Insurance

Corporation (LIC) of India is dominant in the overall industry in two aspects pooling

and redistributing risks across millions of policyholders and in performance of financial

intermediation Therefore the issue of privatization and foreign participation must be

approached cautiously with a step by step approach and should be preceded by

microeconomic institutional and legal reforms

Sinha Tapen (2002) examined the institution of insurance in India Over the past century

Indian insurance industry has experienced big changes It started as a fully private system

with no restriction on foreign participation After the independence the industry went to the

other extreme It became a state owned monopoly In 1991 when rapid economic changes

took place in many parts of the Indian economy nothing happened to the institutional

structure of insurance it remained a monopoly Only in 1999 a new legislation came into

effect signaling a change in the insurance industry structure It was examined that what might

happen in the future when the domestic private insurance companies are allowed to compete

with some foreign participation Because of the time dependence of insurance contracts it is

highly unlikely that these erstwhile monopolies are going to disappear

Baranoff Etti G Sager Thomas W (2002) explained the impact of life risk based capital

(RBC) regulation on relation between capital and risk in the life insurance industry To

examine this issue simultaneous equation partial adjustment model was used Three

equations which express the interrelations among capital and two measures of risk (product

58

risk and asset risk) were used The asset-risk measure used in this paper reflects credit or

solvency risk as in RBC Product risk assessment for life insurance products is rationalized

by transaction cost economics contractual uncertainty A significant finding is that for life

insurers the relation between capital and asset risk is positive This agrees with prior studies

for the propertycasualty insurance industry and some banking studies But the relation

between capital and product risk is negative This is consistent with the hypothesized impact

of guarantee funds in other studies The contrast between the positive relation of capital to

asset risk and the negative relation of capital to product risk underscores the importance of

distinguishing these two components of risk

Adams Mike and Philip Hardwick (2003) stated that the insurance industry claims tend to

constitute the major proportion of total annual outgoings across almost all product lines The

study develops a cost function of insurance claims and applies the model to 1988-93 data

from the United Kingdom and New Zealand life insurance industry It found a similar set of

results for the two countries In general the results support the hypothesis that larger life

insurance firms on average face bigger claims to premium ratios than smaller life

insurance firms The evidence concerning the relationships between claims the

composition of output between claims and the degree of reinsurance is mixed but there is

clear support for the view that stock firms have a less severe claims experience than

mutuals It was concluded that the model provides intuitive insights into the determinants

of insurance claims which could help to stimulate and direct further research

Hautcoer Pierre Cyrille (2004) revealed that the French life insurance industry remained

underdeveloped in comparison with other countries of similar financial development during

the period between 1870 and 1939 The study explained that the wide fluctuations in the

insurance industry are the outcomes of technical peculiarities and their interaction with

macroeconomic fluctuations Nevertheless these fluctuations are not sufficient to explain

the industryrsquos long term stagnation Low returns to clients were mainly due to their

conservative investment strategy It was suggested to impose regulations and barriers to

access of competitors to the market This will lead to maintaining a hold on a small but very

profitable market

Paul J M Klumpes (2004) applied performance benchmarking to measure the profit

and cost efficiency of UK life insurance products These products are required to be

59

distributed through either independent financial advisers (IFA) or appointed andor company

representatives (ARCR) as per polarization regulations Relative profit and cost efficiencies

are assessed using the fourier flexible form of econometric procedure and are based on

detailed product level disclosure information United Kingdom life insurance firms

employing IFA distribution systems are found to be more cost and profit inefficient than

ARCR firms

Ennsfellner Karl C Danielle Lewis Randy L Anderson (2004) examines the

developments in the production efficiency of the Austrian insurance market for the

period 1994-1999 using firm-specific data on lifehealth and non-life insurers obtained

from the Austrian Insurance Regulatory Authority The article uses a Bayesian stochastic

frontier to obtain aggregate and firm specific estimates of production efficiency The

study provides strong evidence that the process of deregulation had positive effects on the

production efficiency of Austrian insurers The lifehealth and non-life firms showed

similar patterns of development in that they were less efficient during the years 1994-

1996 and significantly more efficient in 1997-1999 If the Austrian experience is

representative similar benefits from deregulation may be expected for the Central and

Eastern European countries that prepare for the accession to the European Union

Tone Kaoru Biresh K Sahoo (2005) applies a new variant of data envelopment

analysis model to examine the performance of Life Insurance Corporation (LIC) of India

for a period of nineteen years The findings show significant heterogeneity in the cost

efficiency scores over the observation period A decline in performance after 1994ndash1995

may be due to the huge initial fixed cost undertaken by LIC in modernizing its

operations A significant increase in cost efficiency in 2000ndash2001 may prove to be a

cause for optimism that LIC may now be realizing a benefit from such modernization

James CJ Hao Lin Yhi Chou (2005) estimated the translog cost function for twenty-six

life insurance companies using data for twenty three years (1977ndash1999) The distribution

free approach (DFA) and Battese and Coelli (DFP) model was employed to estimate

inefficiency Then the constants or residuals were tested to see the relation of so called X

efficiencies with market share diversified product strategy scale efficiency and market

growth ratio and in the results efficiency was found to be related with the occurrence of

market share diversification products strategy and scale efficiency

60

Palli Madhuka (2006) measured a life assurance security gap to examine the extent of

underinsured people This gap is computed as the mean ratio of recommended insurance and

actual insurance to household earnings The research provides estimates of the life insurance

gap to maintain living standards of dependents after death of the primary wage earner It is

because inadequate protected families put burden of their welfare on public resources The

primary drivers of demand for risk security are age income affordability wealth and desire

to protect income from inflation Though aggregate demand is driven by these factors various

researches have shown that there is little correlation between a specific familys need for security

and its actual purchase of insurance According to one estimate mentioned in sigma in the

event of a spouses death nearly one third of secondary earners between the ages of twenty two

to thirty nine would suffer at least a decline of forty percent in their standard of living

Sherries Micheal (2006) explains the linkage between solvency capital allocation and fair

rate of return in insurance A method to allocate capital in insurance business is developed

based on an economic definition of solvency and the market value of the insurer balance

sheet Solvency and its financial impact are determined by the value of the insolvency

exchange option The allocation of capital is determined using a complete markets arbitrage

free model and consistency in allocated capital with the economic value of the balance sheet

assets and liabilities is observed as a result

Yang Zijiang (2006) conducted a study in order to know how to achieve efficiency

systematically for the Canadian life and health insurance industry For this purpose an

integrated approach of production and investment performance for the insurers was used

which provided management overall performance evaluation A two stage data envelopment

analysis model was created to provide valuable managerial insights when assessing the dual

impacts of operating and business strategies for the industry The results showed that the

Canadian life and health insurance industry operated fairly efficiently during the period

examined (the year 1998) In addition the scale efficiency was also found in this study

Sinha Ram Pratap (2007) compared thirteen life insurance companies in respect of

technical efficiency for the period 2002-2003 to 2005- 2006 using the assurance region

approach of DEA The comparison of mean technical efficiency scores reveal that mean

technical efficiency has improved in 2003-2004 relative to 2002-2003 remained on the same

level in 2004-2005 and declined in 2005-2006 This is likely because of divergence in the

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

56

institutionalisation of savings and business by different zones of LIC Finally these

indicators a re compared with the related macro variables The analysis reveals that average

sum assured per policy has declined in real terms The increase in the rural business might

involve higher transaction costs in the absence of adequate infrastructure facilities in rural

areas But income and outgo has shown that even with lower sum assured and increase in

rural business the LIC has succeeded in converting a growing amount of annual premium

income in to life insurance fund The outgo as a proportion of income declined partly due to

the decline in death benefits and expense in management

Yates Jo Anne (1999) examined the early adoption and use of computers by life insurance

companies in 1950rsquos using Anthony Giddens Structuration Theory as theoretical lens It

helped to know how pre computer punched card tabulating technology was used in

insurance operations and use of computers in early computer era Most of the times it leads

to expect the reinforcement of existing structures It is also helpful in understanding the new

ways and innovative uses of computer technology in insurance

Grosen Anders Peter Lochte Jorgensen (1999) analyzed one of the most common life

insurance products ie participating (or with profits) policy and showed that the typical

participating policy can be decomposed into a risk free bond element a bonus option and a

surrender option A dynamic model was constructed in which these elements can be valued

separately using contingent claims analysis The impact of various bonus policies and various

levels of the guaranteed interest rate was analyzed numerically and it was found that values

of participating policies were highly sensitive to the bonus policy that surrender options can

be quite valuable and that LIC solvency can be quickly jeopardized if earning opportunities

deteriorate in a situation where bonus reserves are low and promised returns are high

Cummins J David Sharon Tennyson and Mary A Weiss (1999) examined the

relationship between mergers and acquisitions efficiency and scale economies in the US life

insurance industry Cost and revenue efficiency was estimated for the period of 1988-1995

using data envelopment analysis (DEA) The Malmquist methodology is used to measure

changes in efficiency over time It was found that acquired firms achieve greater efficiency

gains than firms that have not been involved in mergers and acquisitions Firms operating

with non decreasing returns to scale and financially vulnerable firms are more likely to be

acquisition targets Overall mergers and acquisitions in the life insurance industry have had

57

a beneficial effect on efficiency

Segal Dan (2000) estimated the acquisition and maintenance costs associated with life

policies as a function of the amount of insurance and number of policies of an insurer by

estimating a cost function The final sample consists of 448 firms and the study period

includes years from 1995 to 1998 Several statistical characteristics of the costs such as

mean and median of the sample were examined The data indicates that there is a large

variation among life insurance companies It was found that the costs associated with life

policies of the largest insurers are much higher than the corresponding costs of other firms

Comparing the costs between ldquobranch firmsrdquo and non-branch firmsrdquo it was revealed that the

costs of branch firms are generally higher than that of non branch firms

Rao D Tripati (2000) explained the macroeconomic implications of privatization and

foreign participation in the insurance sector It was obtained that the Life Insurance

Corporation (LIC) of India is dominant in the overall industry in two aspects pooling

and redistributing risks across millions of policyholders and in performance of financial

intermediation Therefore the issue of privatization and foreign participation must be

approached cautiously with a step by step approach and should be preceded by

microeconomic institutional and legal reforms

Sinha Tapen (2002) examined the institution of insurance in India Over the past century

Indian insurance industry has experienced big changes It started as a fully private system

with no restriction on foreign participation After the independence the industry went to the

other extreme It became a state owned monopoly In 1991 when rapid economic changes

took place in many parts of the Indian economy nothing happened to the institutional

structure of insurance it remained a monopoly Only in 1999 a new legislation came into

effect signaling a change in the insurance industry structure It was examined that what might

happen in the future when the domestic private insurance companies are allowed to compete

with some foreign participation Because of the time dependence of insurance contracts it is

highly unlikely that these erstwhile monopolies are going to disappear

Baranoff Etti G Sager Thomas W (2002) explained the impact of life risk based capital

(RBC) regulation on relation between capital and risk in the life insurance industry To

examine this issue simultaneous equation partial adjustment model was used Three

equations which express the interrelations among capital and two measures of risk (product

58

risk and asset risk) were used The asset-risk measure used in this paper reflects credit or

solvency risk as in RBC Product risk assessment for life insurance products is rationalized

by transaction cost economics contractual uncertainty A significant finding is that for life

insurers the relation between capital and asset risk is positive This agrees with prior studies

for the propertycasualty insurance industry and some banking studies But the relation

between capital and product risk is negative This is consistent with the hypothesized impact

of guarantee funds in other studies The contrast between the positive relation of capital to

asset risk and the negative relation of capital to product risk underscores the importance of

distinguishing these two components of risk

Adams Mike and Philip Hardwick (2003) stated that the insurance industry claims tend to

constitute the major proportion of total annual outgoings across almost all product lines The

study develops a cost function of insurance claims and applies the model to 1988-93 data

from the United Kingdom and New Zealand life insurance industry It found a similar set of

results for the two countries In general the results support the hypothesis that larger life

insurance firms on average face bigger claims to premium ratios than smaller life

insurance firms The evidence concerning the relationships between claims the

composition of output between claims and the degree of reinsurance is mixed but there is

clear support for the view that stock firms have a less severe claims experience than

mutuals It was concluded that the model provides intuitive insights into the determinants

of insurance claims which could help to stimulate and direct further research

Hautcoer Pierre Cyrille (2004) revealed that the French life insurance industry remained

underdeveloped in comparison with other countries of similar financial development during

the period between 1870 and 1939 The study explained that the wide fluctuations in the

insurance industry are the outcomes of technical peculiarities and their interaction with

macroeconomic fluctuations Nevertheless these fluctuations are not sufficient to explain

the industryrsquos long term stagnation Low returns to clients were mainly due to their

conservative investment strategy It was suggested to impose regulations and barriers to

access of competitors to the market This will lead to maintaining a hold on a small but very

profitable market

Paul J M Klumpes (2004) applied performance benchmarking to measure the profit

and cost efficiency of UK life insurance products These products are required to be

59

distributed through either independent financial advisers (IFA) or appointed andor company

representatives (ARCR) as per polarization regulations Relative profit and cost efficiencies

are assessed using the fourier flexible form of econometric procedure and are based on

detailed product level disclosure information United Kingdom life insurance firms

employing IFA distribution systems are found to be more cost and profit inefficient than

ARCR firms

Ennsfellner Karl C Danielle Lewis Randy L Anderson (2004) examines the

developments in the production efficiency of the Austrian insurance market for the

period 1994-1999 using firm-specific data on lifehealth and non-life insurers obtained

from the Austrian Insurance Regulatory Authority The article uses a Bayesian stochastic

frontier to obtain aggregate and firm specific estimates of production efficiency The

study provides strong evidence that the process of deregulation had positive effects on the

production efficiency of Austrian insurers The lifehealth and non-life firms showed

similar patterns of development in that they were less efficient during the years 1994-

1996 and significantly more efficient in 1997-1999 If the Austrian experience is

representative similar benefits from deregulation may be expected for the Central and

Eastern European countries that prepare for the accession to the European Union

Tone Kaoru Biresh K Sahoo (2005) applies a new variant of data envelopment

analysis model to examine the performance of Life Insurance Corporation (LIC) of India

for a period of nineteen years The findings show significant heterogeneity in the cost

efficiency scores over the observation period A decline in performance after 1994ndash1995

may be due to the huge initial fixed cost undertaken by LIC in modernizing its

operations A significant increase in cost efficiency in 2000ndash2001 may prove to be a

cause for optimism that LIC may now be realizing a benefit from such modernization

James CJ Hao Lin Yhi Chou (2005) estimated the translog cost function for twenty-six

life insurance companies using data for twenty three years (1977ndash1999) The distribution

free approach (DFA) and Battese and Coelli (DFP) model was employed to estimate

inefficiency Then the constants or residuals were tested to see the relation of so called X

efficiencies with market share diversified product strategy scale efficiency and market

growth ratio and in the results efficiency was found to be related with the occurrence of

market share diversification products strategy and scale efficiency

60

Palli Madhuka (2006) measured a life assurance security gap to examine the extent of

underinsured people This gap is computed as the mean ratio of recommended insurance and

actual insurance to household earnings The research provides estimates of the life insurance

gap to maintain living standards of dependents after death of the primary wage earner It is

because inadequate protected families put burden of their welfare on public resources The

primary drivers of demand for risk security are age income affordability wealth and desire

to protect income from inflation Though aggregate demand is driven by these factors various

researches have shown that there is little correlation between a specific familys need for security

and its actual purchase of insurance According to one estimate mentioned in sigma in the

event of a spouses death nearly one third of secondary earners between the ages of twenty two

to thirty nine would suffer at least a decline of forty percent in their standard of living

Sherries Micheal (2006) explains the linkage between solvency capital allocation and fair

rate of return in insurance A method to allocate capital in insurance business is developed

based on an economic definition of solvency and the market value of the insurer balance

sheet Solvency and its financial impact are determined by the value of the insolvency

exchange option The allocation of capital is determined using a complete markets arbitrage

free model and consistency in allocated capital with the economic value of the balance sheet

assets and liabilities is observed as a result

Yang Zijiang (2006) conducted a study in order to know how to achieve efficiency

systematically for the Canadian life and health insurance industry For this purpose an

integrated approach of production and investment performance for the insurers was used

which provided management overall performance evaluation A two stage data envelopment

analysis model was created to provide valuable managerial insights when assessing the dual

impacts of operating and business strategies for the industry The results showed that the

Canadian life and health insurance industry operated fairly efficiently during the period

examined (the year 1998) In addition the scale efficiency was also found in this study

Sinha Ram Pratap (2007) compared thirteen life insurance companies in respect of

technical efficiency for the period 2002-2003 to 2005- 2006 using the assurance region

approach of DEA The comparison of mean technical efficiency scores reveal that mean

technical efficiency has improved in 2003-2004 relative to 2002-2003 remained on the same

level in 2004-2005 and declined in 2005-2006 This is likely because of divergence in the

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

57

a beneficial effect on efficiency

Segal Dan (2000) estimated the acquisition and maintenance costs associated with life

policies as a function of the amount of insurance and number of policies of an insurer by

estimating a cost function The final sample consists of 448 firms and the study period

includes years from 1995 to 1998 Several statistical characteristics of the costs such as

mean and median of the sample were examined The data indicates that there is a large

variation among life insurance companies It was found that the costs associated with life

policies of the largest insurers are much higher than the corresponding costs of other firms

Comparing the costs between ldquobranch firmsrdquo and non-branch firmsrdquo it was revealed that the

costs of branch firms are generally higher than that of non branch firms

Rao D Tripati (2000) explained the macroeconomic implications of privatization and

foreign participation in the insurance sector It was obtained that the Life Insurance

Corporation (LIC) of India is dominant in the overall industry in two aspects pooling

and redistributing risks across millions of policyholders and in performance of financial

intermediation Therefore the issue of privatization and foreign participation must be

approached cautiously with a step by step approach and should be preceded by

microeconomic institutional and legal reforms

Sinha Tapen (2002) examined the institution of insurance in India Over the past century

Indian insurance industry has experienced big changes It started as a fully private system

with no restriction on foreign participation After the independence the industry went to the

other extreme It became a state owned monopoly In 1991 when rapid economic changes

took place in many parts of the Indian economy nothing happened to the institutional

structure of insurance it remained a monopoly Only in 1999 a new legislation came into

effect signaling a change in the insurance industry structure It was examined that what might

happen in the future when the domestic private insurance companies are allowed to compete

with some foreign participation Because of the time dependence of insurance contracts it is

highly unlikely that these erstwhile monopolies are going to disappear

Baranoff Etti G Sager Thomas W (2002) explained the impact of life risk based capital

(RBC) regulation on relation between capital and risk in the life insurance industry To

examine this issue simultaneous equation partial adjustment model was used Three

equations which express the interrelations among capital and two measures of risk (product

58

risk and asset risk) were used The asset-risk measure used in this paper reflects credit or

solvency risk as in RBC Product risk assessment for life insurance products is rationalized

by transaction cost economics contractual uncertainty A significant finding is that for life

insurers the relation between capital and asset risk is positive This agrees with prior studies

for the propertycasualty insurance industry and some banking studies But the relation

between capital and product risk is negative This is consistent with the hypothesized impact

of guarantee funds in other studies The contrast between the positive relation of capital to

asset risk and the negative relation of capital to product risk underscores the importance of

distinguishing these two components of risk

Adams Mike and Philip Hardwick (2003) stated that the insurance industry claims tend to

constitute the major proportion of total annual outgoings across almost all product lines The

study develops a cost function of insurance claims and applies the model to 1988-93 data

from the United Kingdom and New Zealand life insurance industry It found a similar set of

results for the two countries In general the results support the hypothesis that larger life

insurance firms on average face bigger claims to premium ratios than smaller life

insurance firms The evidence concerning the relationships between claims the

composition of output between claims and the degree of reinsurance is mixed but there is

clear support for the view that stock firms have a less severe claims experience than

mutuals It was concluded that the model provides intuitive insights into the determinants

of insurance claims which could help to stimulate and direct further research

Hautcoer Pierre Cyrille (2004) revealed that the French life insurance industry remained

underdeveloped in comparison with other countries of similar financial development during

the period between 1870 and 1939 The study explained that the wide fluctuations in the

insurance industry are the outcomes of technical peculiarities and their interaction with

macroeconomic fluctuations Nevertheless these fluctuations are not sufficient to explain

the industryrsquos long term stagnation Low returns to clients were mainly due to their

conservative investment strategy It was suggested to impose regulations and barriers to

access of competitors to the market This will lead to maintaining a hold on a small but very

profitable market

Paul J M Klumpes (2004) applied performance benchmarking to measure the profit

and cost efficiency of UK life insurance products These products are required to be

59

distributed through either independent financial advisers (IFA) or appointed andor company

representatives (ARCR) as per polarization regulations Relative profit and cost efficiencies

are assessed using the fourier flexible form of econometric procedure and are based on

detailed product level disclosure information United Kingdom life insurance firms

employing IFA distribution systems are found to be more cost and profit inefficient than

ARCR firms

Ennsfellner Karl C Danielle Lewis Randy L Anderson (2004) examines the

developments in the production efficiency of the Austrian insurance market for the

period 1994-1999 using firm-specific data on lifehealth and non-life insurers obtained

from the Austrian Insurance Regulatory Authority The article uses a Bayesian stochastic

frontier to obtain aggregate and firm specific estimates of production efficiency The

study provides strong evidence that the process of deregulation had positive effects on the

production efficiency of Austrian insurers The lifehealth and non-life firms showed

similar patterns of development in that they were less efficient during the years 1994-

1996 and significantly more efficient in 1997-1999 If the Austrian experience is

representative similar benefits from deregulation may be expected for the Central and

Eastern European countries that prepare for the accession to the European Union

Tone Kaoru Biresh K Sahoo (2005) applies a new variant of data envelopment

analysis model to examine the performance of Life Insurance Corporation (LIC) of India

for a period of nineteen years The findings show significant heterogeneity in the cost

efficiency scores over the observation period A decline in performance after 1994ndash1995

may be due to the huge initial fixed cost undertaken by LIC in modernizing its

operations A significant increase in cost efficiency in 2000ndash2001 may prove to be a

cause for optimism that LIC may now be realizing a benefit from such modernization

James CJ Hao Lin Yhi Chou (2005) estimated the translog cost function for twenty-six

life insurance companies using data for twenty three years (1977ndash1999) The distribution

free approach (DFA) and Battese and Coelli (DFP) model was employed to estimate

inefficiency Then the constants or residuals were tested to see the relation of so called X

efficiencies with market share diversified product strategy scale efficiency and market

growth ratio and in the results efficiency was found to be related with the occurrence of

market share diversification products strategy and scale efficiency

60

Palli Madhuka (2006) measured a life assurance security gap to examine the extent of

underinsured people This gap is computed as the mean ratio of recommended insurance and

actual insurance to household earnings The research provides estimates of the life insurance

gap to maintain living standards of dependents after death of the primary wage earner It is

because inadequate protected families put burden of their welfare on public resources The

primary drivers of demand for risk security are age income affordability wealth and desire

to protect income from inflation Though aggregate demand is driven by these factors various

researches have shown that there is little correlation between a specific familys need for security

and its actual purchase of insurance According to one estimate mentioned in sigma in the

event of a spouses death nearly one third of secondary earners between the ages of twenty two

to thirty nine would suffer at least a decline of forty percent in their standard of living

Sherries Micheal (2006) explains the linkage between solvency capital allocation and fair

rate of return in insurance A method to allocate capital in insurance business is developed

based on an economic definition of solvency and the market value of the insurer balance

sheet Solvency and its financial impact are determined by the value of the insolvency

exchange option The allocation of capital is determined using a complete markets arbitrage

free model and consistency in allocated capital with the economic value of the balance sheet

assets and liabilities is observed as a result

Yang Zijiang (2006) conducted a study in order to know how to achieve efficiency

systematically for the Canadian life and health insurance industry For this purpose an

integrated approach of production and investment performance for the insurers was used

which provided management overall performance evaluation A two stage data envelopment

analysis model was created to provide valuable managerial insights when assessing the dual

impacts of operating and business strategies for the industry The results showed that the

Canadian life and health insurance industry operated fairly efficiently during the period

examined (the year 1998) In addition the scale efficiency was also found in this study

Sinha Ram Pratap (2007) compared thirteen life insurance companies in respect of

technical efficiency for the period 2002-2003 to 2005- 2006 using the assurance region

approach of DEA The comparison of mean technical efficiency scores reveal that mean

technical efficiency has improved in 2003-2004 relative to 2002-2003 remained on the same

level in 2004-2005 and declined in 2005-2006 This is likely because of divergence in the

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

58

risk and asset risk) were used The asset-risk measure used in this paper reflects credit or

solvency risk as in RBC Product risk assessment for life insurance products is rationalized

by transaction cost economics contractual uncertainty A significant finding is that for life

insurers the relation between capital and asset risk is positive This agrees with prior studies

for the propertycasualty insurance industry and some banking studies But the relation

between capital and product risk is negative This is consistent with the hypothesized impact

of guarantee funds in other studies The contrast between the positive relation of capital to

asset risk and the negative relation of capital to product risk underscores the importance of

distinguishing these two components of risk

Adams Mike and Philip Hardwick (2003) stated that the insurance industry claims tend to

constitute the major proportion of total annual outgoings across almost all product lines The

study develops a cost function of insurance claims and applies the model to 1988-93 data

from the United Kingdom and New Zealand life insurance industry It found a similar set of

results for the two countries In general the results support the hypothesis that larger life

insurance firms on average face bigger claims to premium ratios than smaller life

insurance firms The evidence concerning the relationships between claims the

composition of output between claims and the degree of reinsurance is mixed but there is

clear support for the view that stock firms have a less severe claims experience than

mutuals It was concluded that the model provides intuitive insights into the determinants

of insurance claims which could help to stimulate and direct further research

Hautcoer Pierre Cyrille (2004) revealed that the French life insurance industry remained

underdeveloped in comparison with other countries of similar financial development during

the period between 1870 and 1939 The study explained that the wide fluctuations in the

insurance industry are the outcomes of technical peculiarities and their interaction with

macroeconomic fluctuations Nevertheless these fluctuations are not sufficient to explain

the industryrsquos long term stagnation Low returns to clients were mainly due to their

conservative investment strategy It was suggested to impose regulations and barriers to

access of competitors to the market This will lead to maintaining a hold on a small but very

profitable market

Paul J M Klumpes (2004) applied performance benchmarking to measure the profit

and cost efficiency of UK life insurance products These products are required to be

59

distributed through either independent financial advisers (IFA) or appointed andor company

representatives (ARCR) as per polarization regulations Relative profit and cost efficiencies

are assessed using the fourier flexible form of econometric procedure and are based on

detailed product level disclosure information United Kingdom life insurance firms

employing IFA distribution systems are found to be more cost and profit inefficient than

ARCR firms

Ennsfellner Karl C Danielle Lewis Randy L Anderson (2004) examines the

developments in the production efficiency of the Austrian insurance market for the

period 1994-1999 using firm-specific data on lifehealth and non-life insurers obtained

from the Austrian Insurance Regulatory Authority The article uses a Bayesian stochastic

frontier to obtain aggregate and firm specific estimates of production efficiency The

study provides strong evidence that the process of deregulation had positive effects on the

production efficiency of Austrian insurers The lifehealth and non-life firms showed

similar patterns of development in that they were less efficient during the years 1994-

1996 and significantly more efficient in 1997-1999 If the Austrian experience is

representative similar benefits from deregulation may be expected for the Central and

Eastern European countries that prepare for the accession to the European Union

Tone Kaoru Biresh K Sahoo (2005) applies a new variant of data envelopment

analysis model to examine the performance of Life Insurance Corporation (LIC) of India

for a period of nineteen years The findings show significant heterogeneity in the cost

efficiency scores over the observation period A decline in performance after 1994ndash1995

may be due to the huge initial fixed cost undertaken by LIC in modernizing its

operations A significant increase in cost efficiency in 2000ndash2001 may prove to be a

cause for optimism that LIC may now be realizing a benefit from such modernization

James CJ Hao Lin Yhi Chou (2005) estimated the translog cost function for twenty-six

life insurance companies using data for twenty three years (1977ndash1999) The distribution

free approach (DFA) and Battese and Coelli (DFP) model was employed to estimate

inefficiency Then the constants or residuals were tested to see the relation of so called X

efficiencies with market share diversified product strategy scale efficiency and market

growth ratio and in the results efficiency was found to be related with the occurrence of

market share diversification products strategy and scale efficiency

60

Palli Madhuka (2006) measured a life assurance security gap to examine the extent of

underinsured people This gap is computed as the mean ratio of recommended insurance and

actual insurance to household earnings The research provides estimates of the life insurance

gap to maintain living standards of dependents after death of the primary wage earner It is

because inadequate protected families put burden of their welfare on public resources The

primary drivers of demand for risk security are age income affordability wealth and desire

to protect income from inflation Though aggregate demand is driven by these factors various

researches have shown that there is little correlation between a specific familys need for security

and its actual purchase of insurance According to one estimate mentioned in sigma in the

event of a spouses death nearly one third of secondary earners between the ages of twenty two

to thirty nine would suffer at least a decline of forty percent in their standard of living

Sherries Micheal (2006) explains the linkage between solvency capital allocation and fair

rate of return in insurance A method to allocate capital in insurance business is developed

based on an economic definition of solvency and the market value of the insurer balance

sheet Solvency and its financial impact are determined by the value of the insolvency

exchange option The allocation of capital is determined using a complete markets arbitrage

free model and consistency in allocated capital with the economic value of the balance sheet

assets and liabilities is observed as a result

Yang Zijiang (2006) conducted a study in order to know how to achieve efficiency

systematically for the Canadian life and health insurance industry For this purpose an

integrated approach of production and investment performance for the insurers was used

which provided management overall performance evaluation A two stage data envelopment

analysis model was created to provide valuable managerial insights when assessing the dual

impacts of operating and business strategies for the industry The results showed that the

Canadian life and health insurance industry operated fairly efficiently during the period

examined (the year 1998) In addition the scale efficiency was also found in this study

Sinha Ram Pratap (2007) compared thirteen life insurance companies in respect of

technical efficiency for the period 2002-2003 to 2005- 2006 using the assurance region

approach of DEA The comparison of mean technical efficiency scores reveal that mean

technical efficiency has improved in 2003-2004 relative to 2002-2003 remained on the same

level in 2004-2005 and declined in 2005-2006 This is likely because of divergence in the

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

59

distributed through either independent financial advisers (IFA) or appointed andor company

representatives (ARCR) as per polarization regulations Relative profit and cost efficiencies

are assessed using the fourier flexible form of econometric procedure and are based on

detailed product level disclosure information United Kingdom life insurance firms

employing IFA distribution systems are found to be more cost and profit inefficient than

ARCR firms

Ennsfellner Karl C Danielle Lewis Randy L Anderson (2004) examines the

developments in the production efficiency of the Austrian insurance market for the

period 1994-1999 using firm-specific data on lifehealth and non-life insurers obtained

from the Austrian Insurance Regulatory Authority The article uses a Bayesian stochastic

frontier to obtain aggregate and firm specific estimates of production efficiency The

study provides strong evidence that the process of deregulation had positive effects on the

production efficiency of Austrian insurers The lifehealth and non-life firms showed

similar patterns of development in that they were less efficient during the years 1994-

1996 and significantly more efficient in 1997-1999 If the Austrian experience is

representative similar benefits from deregulation may be expected for the Central and

Eastern European countries that prepare for the accession to the European Union

Tone Kaoru Biresh K Sahoo (2005) applies a new variant of data envelopment

analysis model to examine the performance of Life Insurance Corporation (LIC) of India

for a period of nineteen years The findings show significant heterogeneity in the cost

efficiency scores over the observation period A decline in performance after 1994ndash1995

may be due to the huge initial fixed cost undertaken by LIC in modernizing its

operations A significant increase in cost efficiency in 2000ndash2001 may prove to be a

cause for optimism that LIC may now be realizing a benefit from such modernization

James CJ Hao Lin Yhi Chou (2005) estimated the translog cost function for twenty-six

life insurance companies using data for twenty three years (1977ndash1999) The distribution

free approach (DFA) and Battese and Coelli (DFP) model was employed to estimate

inefficiency Then the constants or residuals were tested to see the relation of so called X

efficiencies with market share diversified product strategy scale efficiency and market

growth ratio and in the results efficiency was found to be related with the occurrence of

market share diversification products strategy and scale efficiency

60

Palli Madhuka (2006) measured a life assurance security gap to examine the extent of

underinsured people This gap is computed as the mean ratio of recommended insurance and

actual insurance to household earnings The research provides estimates of the life insurance

gap to maintain living standards of dependents after death of the primary wage earner It is

because inadequate protected families put burden of their welfare on public resources The

primary drivers of demand for risk security are age income affordability wealth and desire

to protect income from inflation Though aggregate demand is driven by these factors various

researches have shown that there is little correlation between a specific familys need for security

and its actual purchase of insurance According to one estimate mentioned in sigma in the

event of a spouses death nearly one third of secondary earners between the ages of twenty two

to thirty nine would suffer at least a decline of forty percent in their standard of living

Sherries Micheal (2006) explains the linkage between solvency capital allocation and fair

rate of return in insurance A method to allocate capital in insurance business is developed

based on an economic definition of solvency and the market value of the insurer balance

sheet Solvency and its financial impact are determined by the value of the insolvency

exchange option The allocation of capital is determined using a complete markets arbitrage

free model and consistency in allocated capital with the economic value of the balance sheet

assets and liabilities is observed as a result

Yang Zijiang (2006) conducted a study in order to know how to achieve efficiency

systematically for the Canadian life and health insurance industry For this purpose an

integrated approach of production and investment performance for the insurers was used

which provided management overall performance evaluation A two stage data envelopment

analysis model was created to provide valuable managerial insights when assessing the dual

impacts of operating and business strategies for the industry The results showed that the

Canadian life and health insurance industry operated fairly efficiently during the period

examined (the year 1998) In addition the scale efficiency was also found in this study

Sinha Ram Pratap (2007) compared thirteen life insurance companies in respect of

technical efficiency for the period 2002-2003 to 2005- 2006 using the assurance region

approach of DEA The comparison of mean technical efficiency scores reveal that mean

technical efficiency has improved in 2003-2004 relative to 2002-2003 remained on the same

level in 2004-2005 and declined in 2005-2006 This is likely because of divergence in the

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

60

Palli Madhuka (2006) measured a life assurance security gap to examine the extent of

underinsured people This gap is computed as the mean ratio of recommended insurance and

actual insurance to household earnings The research provides estimates of the life insurance

gap to maintain living standards of dependents after death of the primary wage earner It is

because inadequate protected families put burden of their welfare on public resources The

primary drivers of demand for risk security are age income affordability wealth and desire

to protect income from inflation Though aggregate demand is driven by these factors various

researches have shown that there is little correlation between a specific familys need for security

and its actual purchase of insurance According to one estimate mentioned in sigma in the

event of a spouses death nearly one third of secondary earners between the ages of twenty two

to thirty nine would suffer at least a decline of forty percent in their standard of living

Sherries Micheal (2006) explains the linkage between solvency capital allocation and fair

rate of return in insurance A method to allocate capital in insurance business is developed

based on an economic definition of solvency and the market value of the insurer balance

sheet Solvency and its financial impact are determined by the value of the insolvency

exchange option The allocation of capital is determined using a complete markets arbitrage

free model and consistency in allocated capital with the economic value of the balance sheet

assets and liabilities is observed as a result

Yang Zijiang (2006) conducted a study in order to know how to achieve efficiency

systematically for the Canadian life and health insurance industry For this purpose an

integrated approach of production and investment performance for the insurers was used

which provided management overall performance evaluation A two stage data envelopment

analysis model was created to provide valuable managerial insights when assessing the dual

impacts of operating and business strategies for the industry The results showed that the

Canadian life and health insurance industry operated fairly efficiently during the period

examined (the year 1998) In addition the scale efficiency was also found in this study

Sinha Ram Pratap (2007) compared thirteen life insurance companies in respect of

technical efficiency for the period 2002-2003 to 2005- 2006 using the assurance region

approach of DEA The comparison of mean technical efficiency scores reveal that mean

technical efficiency has improved in 2003-2004 relative to 2002-2003 remained on the same

level in 2004-2005 and declined in 2005-2006 This is likely because of divergence in the

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

61

performance across the life insurers In the last two years most of the life insurers have

exhibited increasing returns to scale This is indicative of the wide opportunities that the

insurers have for them

Sinha Ram Pratap (2007) estimated cost efficiency of the life insurance companies

operating in India for the period 2002-03 to 2006-07 using the new cost efficiency approach

suggested by Tone (2002) and suggested an upward trend in cost efficiency of the observed

life insurers between 2002-03 and 2004-05 However the trend was reversed for the next two

years ie 2005- 06 and 2006-07This has been so because of the fact that during the initial

years of observation mean cost efficiency of the private life insurers was rising but the trend

was reversed in 2005-06 and 2006-07

Vivian Jeng Gene C Lai Michael J Mcnamara (2007) examined the efficiency changes

of US life insurers before and after demutualization in the 1980s and 1990s Two

frontier approaches (the value-added approach and the financial intermediary

approach) were used to measure the efficiency changes In addition Malmquist indices

were also used to investigate the efficiency and productivity change of converted life

insurers over time The results using the value added approach indicate that

demutualized life insurers improve their efficiency before demutualization On the

other hand the evidence using the financial intermediary approach shows the efficiency

of the demutualized life insurers relative to mutual control insurers deteriorates before

demutualization and improves after conversion The difference in the results between

the two approaches is due to the fact that the financial intermediary approach

considers financial conditions The results of both approaches suggest that there is no

efficiency improvement after demutualization relative to stock control insurers There

is however efficiency improvement relative to mutual control insurers when the

financial intermediary approach is used

Desheng W Zijiang Yan Sandra vela Liang (2007) created a new data envelopment

analysis model to provide valuable managerial insights when assessing the dual impacts of

operating and business strategies for Canadian life and health insurance industry This

problem oriented new DEA model is different from classical DEA model as it can

simultaneously assess the production and investment performance of insurers The

mathematical solution is provided for this new model and the results show that the Canadian

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

62

LampH insurance companies operated very efficiently for the examined three year period

(1996ndash1998) In addition no scale efficiency in the Canadian LampH insurance industry is

found in this study

Sinha Tapen (2007) affirmed the journey of life insurance sector in India The study pointed

out that it was 1956 when life insurance was nationalized and a monopoly was created In

1992 a Government appointed committee recommended that private companies should be

allowed to operate The private sector was admitted into the insurance business in 2000 It

was cited that the insurance market achieved nineteenth rank in 2003 Therefore it was also

expected that this strong economic growth would make this industry one of the potentially

largest markets in the future

Young Virgiana R (2007) developed a pricing rule for life insurance under stochastic

mortality in an incomplete market It was assumed that life insurers are in need of

compensation for its risk in the form of a pre specified instantaneous Sharpe ratio The results

emerging from the paper were that as the number of contracts approaches infinity a linear

partial differential equation is solved by price per contract Another important result is that

even if the number of contracts approaches infinity the risk adjusted premium is greater than

net premium only if hazard rate is stochastic Thus the price reflects the fact that systematic

mortality risk can not be eliminated by selling more life insurance policies

Sinha Ram Pratap (2007) stated that subsequent to the passage of the Insurance Regulatory

and Development Authority (IRDA) Act 1999 the life insurance market in India underwent

major structural changes in recent years Between March 2000 and March 2005 the number

of life insurance companies operating in India has increased from one to fifteen As on March

31 2005 the private sector life insurers enjoyed nearly ten percent of the premium income

and nearly twenty-five percent of the new business In view of the changing scenario of

competition in the life insurance sector the paper compares thirteen life insurance companies

for the financial years 2002-03 2003-04 and 2004-05 in respect of technical efficiency and

changes in total factor productivity For the purpose of computation of technical efficiency

and total factor productivity the net premium income of the observed life insurance

companies has been taken as the output and equity capital and the number of agents of

insurance industries have been taken as the inputs The results suggest that all the life

insurers exhibit positive total factor productivity growth during the period

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

63

Adams Mike Philip Hardwick Hong Zou (2008) tested the two tax related arguments

regarding use of reinsurance for a period of ten year data from 1992 to 2001 for a sample of

United Kingdom (UK) life insurance firms These two arguments were the income

volatility reduction and the income level enhancement arguments It was found that UK

life insurers with low marginal tax rates tend to use more reinsurance and vice versa

Moreover the volatility reduction argument is not supported as tax convexity is found to

have no significant impact on the purchase of reinsurance

Berry Stolzle Thomas R (2008) examined liquidation strategies and asset allocation

decisions for property and casualty insurance companies for different insurance product lines

The study proposed a cash flow based liquidation model of an insurance company and

analyzed selling strategies for a portfolio with liquid and illiquid assets Within this

framework the influence of different bid ask spread models on the minimum capital

requirement a solution set consisting of an optimal initial asset allocation and an optimal

liquidation strategy is also studied It showed that the initial asset allocation in conjunction

with the appropriate liquidation strategy is an important tool in minimizing the capital

committed to cover claims for a predetermined ruin probability This interdependence is of

importance to insurance companies stakeholders and regulators

Zweifel Peter Christoph Auckenthalert (2008) calls attention to a difficulty with insurerrsquos

investment policies that seems to have been overlooked so far There is the distinct

possibility that insurers cannot satisfy the demands of different stakeholders in terms of

expected returns and volatility While using the capital asset pricing model as the benchmark

the study distinguishes two groups of stakeholders that impose additional constraints One is

income security in the interest of current beneficiaries and older workers the other is

predictability of contributions in the interest of contributing younger workers and

sponsoring employers It defines the conditions for which the combination of these

constraints results in a lack of feasibility of investment policy Minimum deviation from the

capital market line is proposed as the performance benchmark in these situations

S Hun Seog (2008) develops an informational cascade model based on Bikhchandani

Hirshleifer and Welch (1992) with applications to the insurance market The study

investigates the existence of cascades and the effects of public information on cascades The

result applies to insurance markets to explain how catastrophic events may lead to increased

64

demand how loss shocks may lead to insurance cycles and how the heterogeneity of

policyholders affects the choice of limited auto insurance in Pennsylvania

Lai Gene C Michael J McNamara Tong Yu (2008) examines the wealth effect of

demutualization initial public offerings (IPOrsquos) by investigating under pricing and post

conversion long run stock performance The results suggest that there is more money left on

the table for demutualized insurers than for non demutualized insurers and show that higher

under pricing for demutualized firms can be explained by greater market demand market

sentiment and the size of the offering The study presents evidence that the out performance

in stock returns is mainly attributable to improvement in post demutualization operating

performance and demand at the time of the IPOrsquos The combined results of under pricing and

long term performance suggest that the wealth of policyholders who choose stock rather than

cash or policy credits is not harmed by demutualization

Wen Min Ming Anna D Martin Gene Lai Thomas J OrsquoBrien (2008) points out that due

to the highly skewed and heavy tailed distributions associated with the insurance claims

process the study evaluate the Rubinstein-Leland (RL) model for its ability to improve the

cost of equity estimates of insurance companies because of its distribution free feature The

implication is that if the insurer is small (assets size is less than $2291 million) andor its

returns are not symmetrical (the value of skewness is greater than 0509 or less than minus0509

then it should use the RL model rather than the CAPM to estimate its cost of capital

Thomas Gerstner Michael Griebel Markus Holtz Ralf Goschnick Marcus Haep

(2008) investigated the impact of the most important product and management parameters on

the risk exposure of the insurance company and for this purpose the study proposed a

discrete time stochastic asset liability management (ALM) model for the simulation of

simplified balance sheets of life insurance products The model incorporates the most

important life insurance product characteristics the surrender of contracts a reserve

dependent bonus declaration a dynamic asset allocation and a two factor stochastic capital

market Furthermore the model is designed to have a modular organization which permits

straightforward modifications and extensions to handle specific requirements The results

showed that the model captures the main behaviour patterns of the balance sheet

development of life insurance products

65

Gatzert Nadine Gudrun Hoermann Hato Schmeiser (2009) attempted to quantify the

effect of altered surrender behavior subject to the health status of an insured in a portfolio of

life insurance contracts on the surrender profits of primary insurers The model includes

mortality heterogeneity by applying a stochastic frailty factor to a mortality table The study

additionally analyzed the impact of the premium payment method by comparing results for

annual and single premium payments

Fier G Stephen James M Carson (2009) provided an evidence of a significant relationship

between catastrophes and life insurance demand both for states directly affected by the event

and for neighboring states For this purpose US state level data for the period of 1994 to

2004 was examined It was suggested that the occurrence of a catastrophe may lead to

increases in risk perception risk mitigation and insurance purchasing behaviour Similarly

the study posits that the occurrence of catastrophes also may be associated with an increased

demand for coverage against mortality risk

Chatterjee Biswajit Ram Pratap Sinha (2009) estimated cost efficiency of the life

insurance companies operating in India for the period 2002-03 to 2006-07 using the new cost

efficiency approach suggested by Tone (2002) The results suggest an upward trend in cost

efficiency of the observed life insurers between 2002-03 and 2004-05 However the trend

was reversed for the next two years ie 2005-06 and 2006-07 This has been so because of

the fact that during the initial years of observation mean cost efficiency of the private

life insurers was rising but the trend was reversed in 2005-06 and 2006-07

Rao MVS Srinivasa (2009) analyzed the impact of life insurance business in India and

concluded that Indiarsquos insurance industry accounted for twelve percent of total Gross

Domestic Product (GDP) in 2000-01 It was the year in which the insurance sector was

liberalized The percentage increased to 201 percent in 2005-06 The market share of the

private insurers and LIC in terms of policies underwritten was 1092 percent and 8908

percent in 2005-06 as against 852 percent and 9148 percent respectively in 2004-05 Total

pay-out by the life insurance industry towards commissions in 2005-06 was Rs 864329

crore as against Rs 710446 crore in 2004-05 With a population of more than one billion

sixteen percent of the rural population was insured at that time whereas average population

insured in India was twenty percent Since seventy percent of the Indian population lives in

rural areas the potential is very attractive

66

Mcshane Michael K Cox Larry A Butler Richard J (2009) delved that the regulatory

separation theory indicates that a system with multiple regulators leads to less forbearance

and limits producer gains while a model of banking regulation developed by DellrsquoAriccia and

Marquez in 2006 predicts the opposite Fragmented regulation of the US Life insurance

industry provides an especially rich environment for testing the effects of regulatory

competition The study found positive relations between regulatory competition and

profitability measures for this industry which is consistent with the DellrsquoAriccia and

Marquez model The results have practical implications for the debate over federal versus

state regulations of insurance and financial services in the US

Xiaoling Hu Cuizhen Zhang Jin-Li Hu Nong Zhu (2009) examined the efficiencies of

Chinas foreign and domestic life insurance providers The study was conducted with a

purpose to explore the relationship between ownership structure and the efficiencies of

insurers while taking into consideration other firm attributes The data envelopment analysis

(DEA) method was used to estimate the efficiencies of the insurers based on a panel data

between 1999 and 2004 The results indicate that the average efficiency scores for all the

insurers are cyclical Both technical and scale efficiency reached their peaks in 1999 and

2000 and gradually reduced for the rest of the period under examination until 2004 when

average efficiency were improved again The regression results showed that the insurers

market power the distribution channels used and the ownership structures may be attributed

to the variation in the efficiencies Based on the research findings and the discussions the

study also provided several recommendations for policy makers regulators and senior

executives of insurers

Debabrata Mitra amp Amlan Ghosh (2009) stated that life insurance is of paramount

importance for protecting human lives against accidents causalities and other types of risks

Life insurance has been dominated by public sector in India however with the liberalization

of Indian economy private sector entry in life insurance has got momentum The public

sector insurance companies particularly LIC of India has emphasized on exploiting the

potential of rural India as it provides immense scope even in the post globalised era

Therefore the paper highlighted emerging trends and patterns in Indian insurance business

during post globalised era It also focuses on the role of private partners in life insurance in

India

65

Gatzert Nadine Gudrun Hoermann Hato Schmeiser (2009) attempted to quantify the

effect of altered surrender behavior subject to the health status of an insured in a portfolio of

life insurance contracts on the surrender profits of primary insurers The model includes

mortality heterogeneity by applying a stochastic frailty factor to a mortality table The study

additionally analyzed the impact of the premium payment method by comparing results for

annual and single premium payments

Fier G Stephen James M Carson (2009) provided an evidence of a significant relationship

between catastrophes and life insurance demand both for states directly affected by the event

and for neighboring states For this purpose US state level data for the period of 1994 to

2004 was examined It was suggested that the occurrence of a catastrophe may lead to

increases in risk perception risk mitigation and insurance purchasing behaviour Similarly

the study posits that the occurrence of catastrophes also may be associated with an increased

demand for coverage against mortality risk

Chatterjee Biswajit Ram Pratap Sinha (2009) estimated cost efficiency of the life

insurance companies operating in India for the period 2002-03 to 2006-07 using the new cost

efficiency approach suggested by Tone (2002) The results suggest an upward trend in cost

efficiency of the observed life insurers between 2002-03 and 2004-05 However the trend

was reversed for the next two years ie 2005-06 and 2006-07 This has been so because of

the fact that during the initial years of observation mean cost efficiency of the private

life insurers was rising but the trend was reversed in 2005-06 and 2006-07

Rao MVS Srinivasa (2009) analyzed the impact of life insurance business in India and

concluded that Indiarsquos insurance industry accounted for twelve percent of total Gross

Domestic Product (GDP) in 2000-01 It was the year in which the insurance sector was

liberalized The percentage increased to 201 percent in 2005-06 The market share of the

private insurers and LIC in terms of policies underwritten was 1092 percent and 8908

percent in 2005-06 as against 852 percent and 9148 percent respectively in 2004-05 Total

pay-out by the life insurance industry towards commissions in 2005-06 was Rs 864329

crore as against Rs 710446 crore in 2004-05 With a population of more than one billion

sixteen percent of the rural population was insured at that time whereas average population

insured in India was twenty percent Since seventy percent of the Indian population lives in

rural areas the potential is very attractive

66

Mcshane Michael K Cox Larry A Butler Richard J (2009) delved that the regulatory

separation theory indicates that a system with multiple regulators leads to less forbearance

and limits producer gains while a model of banking regulation developed by DellrsquoAriccia and

Marquez in 2006 predicts the opposite Fragmented regulation of the US Life insurance

industry provides an especially rich environment for testing the effects of regulatory

competition The study found positive relations between regulatory competition and

profitability measures for this industry which is consistent with the DellrsquoAriccia and

Marquez model The results have practical implications for the debate over federal versus

state regulations of insurance and financial services in the US

Xiaoling Hu Cuizhen Zhang Jin-Li Hu Nong Zhu (2009) examined the efficiencies of

Chinas foreign and domestic life insurance providers The study was conducted with a

purpose to explore the relationship between ownership structure and the efficiencies of

insurers while taking into consideration other firm attributes The data envelopment analysis

(DEA) method was used to estimate the efficiencies of the insurers based on a panel data

between 1999 and 2004 The results indicate that the average efficiency scores for all the

insurers are cyclical Both technical and scale efficiency reached their peaks in 1999 and

2000 and gradually reduced for the rest of the period under examination until 2004 when

average efficiency were improved again The regression results showed that the insurers

market power the distribution channels used and the ownership structures may be attributed

to the variation in the efficiencies Based on the research findings and the discussions the

study also provided several recommendations for policy makers regulators and senior

executives of insurers

Debabrata Mitra amp Amlan Ghosh (2009) stated that life insurance is of paramount

importance for protecting human lives against accidents causalities and other types of risks

Life insurance has been dominated by public sector in India however with the liberalization

of Indian economy private sector entry in life insurance has got momentum The public

sector insurance companies particularly LIC of India has emphasized on exploiting the

potential of rural India as it provides immense scope even in the post globalised era

Therefore the paper highlighted emerging trends and patterns in Indian insurance business

during post globalised era It also focuses on the role of private partners in life insurance in

India

66

Mcshane Michael K Cox Larry A Butler Richard J (2009) delved that the regulatory

separation theory indicates that a system with multiple regulators leads to less forbearance

and limits producer gains while a model of banking regulation developed by DellrsquoAriccia and

Marquez in 2006 predicts the opposite Fragmented regulation of the US Life insurance

industry provides an especially rich environment for testing the effects of regulatory

competition The study found positive relations between regulatory competition and

profitability measures for this industry which is consistent with the DellrsquoAriccia and

Marquez model The results have practical implications for the debate over federal versus

state regulations of insurance and financial services in the US

Xiaoling Hu Cuizhen Zhang Jin-Li Hu Nong Zhu (2009) examined the efficiencies of

Chinas foreign and domestic life insurance providers The study was conducted with a

purpose to explore the relationship between ownership structure and the efficiencies of

insurers while taking into consideration other firm attributes The data envelopment analysis

(DEA) method was used to estimate the efficiencies of the insurers based on a panel data

between 1999 and 2004 The results indicate that the average efficiency scores for all the

insurers are cyclical Both technical and scale efficiency reached their peaks in 1999 and

2000 and gradually reduced for the rest of the period under examination until 2004 when

average efficiency were improved again The regression results showed that the insurers

market power the distribution channels used and the ownership structures may be attributed

to the variation in the efficiencies Based on the research findings and the discussions the

study also provided several recommendations for policy makers regulators and senior

executives of insurers

Debabrata Mitra amp Amlan Ghosh (2009) stated that life insurance is of paramount

importance for protecting human lives against accidents causalities and other types of risks

Life insurance has been dominated by public sector in India however with the liberalization

of Indian economy private sector entry in life insurance has got momentum The public

sector insurance companies particularly LIC of India has emphasized on exploiting the

potential of rural India as it provides immense scope even in the post globalised era

Therefore the paper highlighted emerging trends and patterns in Indian insurance business

during post globalised era It also focuses on the role of private partners in life insurance in

India

67

Mayer David Clifford W Smith (2010) explained that the monitoring by outside board

members and incentive compensation provisions in executive pay packages are alternative

mechanisms for controlling incentive problems between owners and managers The control

hypothesis suggested that if incentive conflicts vary materially those firms with more outside

directors also should implement a higher degree of pay for performance sensitivity The

evidence of the study is consistent with this control hypothesis It documented a relation

between board structure and the extent to which executive compensation is tied to

performance in mutual Compensation changes are significantly more sensitive to changes in

return on assets when the fraction of outsiders on the board is high

David L Eckles Martin Halek (2010) investigates incentives of insurance firm managers

to manipulate loss reserves in order to maximize their compensation It is found that

managers who receive bonuses are likely capped and those who do not receive bonus tend to

over reserve for current year incurred losses However managers who receive bonuses that

are likely not capped tend to be under reserved for current year incurred losses It is also

found that managers who exercise stock options tend to under reserve in the current period

Jiang Cheng Elyas Elyasian I Tzu-Ting Lin(2010) examined the markets reaction to

New York attorney general eliot spitzers civil suit against mega broker Marsh for bid rigging

and inappropriate use of contingent commissions within GARCH framework Effects on the

stock returns of insurance brokers and insurers were tested The findings were as follows

GARCH effects proved to be significant in modelling brokerinsurer returns the suit

generated negative effects on the brokerage industry and individual brokers It was suggested

that contagion dominates competitive effects spillover effects from the brokerage sector to

insurance business are significant and mostly negative demonstrating industry integration

and information based contagion was supported as opposed to the pure-panic contagion

Huang Hong Chih (2010) exhibited the importance of investment and risk control for

financial institutions Asset allocation provided a fundamental investing principle to manage

the risk and return trade off in financial markets The article proposes a general formulation

of a first approximation of multi period asset allocation modelling for those institutions who

invest to meet the target payment structures of a long term liability By addressing the

shortcomings of both single period models and the single point forecast of the mean variance

68

approach this article derived explicit formulae for optimal asset allocations taking into

account possible future realizations in a multi period discrete time model

Wang Jennifer L HC Huang Sharon S Yang Jeffrey T Tsai (2010) conducted a study

to examine the dealing of natural hedging strategy with longevity risks for life insurance

companies The study proposed an immunization model which incorporated a stochastic

mortality dynamic to calculate the optimal life insurance annuity product mix ratio to hedge

against longevity risks The study mode the use of the changes in future mortality using the

well known Lee Carter model and discuss the model risk issue by comparing the results

between the Lee Carter and Cairns Blake Dowd models On the basis of the mortality

experience and insurance products in the United States it was demonstrated that the

proposed model can lead to an optimal product mix and effectively reduce longevity risks for

life insurance companies

Liebenberg Andre P James M Carson Robert E Hoyt (2010) stated that the previous

research has examined the demand for life insurance policy loans using aggregate policy loan

data In contrast the study uses a detailed household survey data set containing life insurance

and policy loan information Four hypotheses traditionally associated with policy loan

demand were tested The research provided the first US evidence (in the post world war II

period) in support of the policy loan emergency fund hypothesis In particular it was found

that the more detailed emergency fund proxies used revealed a significantly positive relation

between loan demand and recent expense or income shocks

Corsaro S Angelis PL De Perla Z Marino Znetti P (2010) discussed the development

of portfolios valuation system of asset liability management for life insurance policies on

advanced architectures The first aim of the study was to introduce a change in the stochastic

processes for the risk sources thus providing estimates under the forward risk neutral

measure which results for gain in accuracy The Monte Carlo method was then introduced to

speed up the simulation process According to new rules of solvency II project numerical

simulations must provide reliable estimates of the relevant quantities involved in the

contracts Therefore valuation process has to rely on accurate algorithms able to provide

solutions in a suitable turnaround time

Sinha Ram Pratap (2010) compared fifteen life insurance companies operating in India

from 2005-06 to 2008-09 using the old and new Revenue Maximizing Approach The

69

difference between the two approaches lies in the specification of the production possibility

set In both the approaches only the Life Insurance Corporation of India (LIC) was found to

be efficient for the observed years followed by Sahara life very closely However since in

the old approach the technically inefficient firms are penalized very harshly the grand mean

technical efficiency score is less than fifty percent to that in the new approach

Dutta A and Sengupta PP (2010) focused on the important investment issue They tried to

answer about whether increasing investment on IT infrastructure (which is resulting into a

technological innovation in business operation of the private companies) has a favorable

impact on efficiency or not For the purpose a panel data set of twelve private life insurance

companies over the financial period 2006-2009 was taken The efficiency was evaluated by

applying Data Envelopment Analysis (DEA) and calculating the scale efficiency The results

showed that increasing investment on IT infrastructure had a positive impact on scale and

technical efficiency change if constant and variable returns to scale assumptions were

considered

Rao Ananth Kashani Hossein and Marie Attiea (2010) analyzed the efficiency and

productivity issues of the insurance sector from the policymakers as well as investors view

point so as to insulate the business and financial risks of UAE corporate houses The paper

uses two inputs of administrative amp general expenses and equity amp change in legal reserves

versus two outputs of rate of return on investments and liquid assets to total liability ratio to

assess the allocative efficiency of companies using DEA The data set for nineteen insurers in

the region was considered for the study To evaluate the performance of the insurers the

efficiency is broken down in to technical and scale efficiency by using malmquist

productivity index Considerable degree of managerial inefficiency among the insurers with

least efficiency in 2000 and highest efficiency in 2004 was observed as a result Further the

insurers achieved a mere 08 percent annual gain in total factor productivity over the study

period

Alamelu K (2011) stated that the insurance sector in India was dominated by the state

owned Life Insurance Corporation (LIC) and the General Insurance Corporation (GIC) along

with its four subsidiaries But in 1999 the Insurance Regulatory and Development Authority

(IRDA) bill opened it up to private and foreign players whose share in the insurance market

has been rising The IRDA is the regulatory authority of the insurance sector entrusted with

70

protecting the interests of the insurance policy holders and regulating promoting and

ensuring orderly growth of the insurance industry in India As financial intermediaries life

insurers tap savings of the public in the form of premium In order to sustain public

confidence they have to maintain their financial credibility intact In other words a strong

financial background enables insurance companies to augment their business The

International Monetary Fund (IMF) suggested a number of indicators to diagnose the health

of the insurance sector This paper makes an attempt to analyze the financial soundness of

Indian Life Insurance Companies in terms of capital adequacy asset quality reinsurance

management soundness earnings and profitability liquidity and solvency ratios

Andreas Milidonis Konstantinos Stathopoulos (2011) tried to find the relation between

executive compensation and market implied default risk for listed insurance firms from 1992

to 2007 Shareholders are expected to encourage managerial risk sharing through equity

based incentive compensation Thus it was found that long term incentives and other share

based plans do not affect the default risk faced by firms However the extensive use of stock

options leads to higher future default risk for insurance firms It was argued that this is

because option based incentives induce managerial risk taking behaviour which seeks to

maximize managerial payoff through equity volatility This could be detrimental to the

interests of shareholders especially during a financial crisis

Dutta Anirban Sengupta Partha Pratim (2011) stated that efficiency is the key concern

of policymakers to encourage further development of the insurance industry as well as for the

managers of the insurance companies to exist profitably in the business in the long run and

used a panel dataset of fourteen life insurance companies over the period 2004ndash09 to

evaluate their efficiency scores by applying Data Envelopment Analysis and calculating the

scale efficiency The results render light on policy design and implementations for future

development of the life insurance industry in India

Neelaveni V (2012) stated that the evaluation of financial performance of the life insurance

companies is essentially needed to select the a best life insurance policy Therefore five life

insurance companies are randomly selected at the time of 2002-03 and evaluated in terms of

performance It is because with reforms of regulations and opening up of the insurance

sector to the private management in the year 1999 tough competition can be seen in the

insurance industry The number of general insurance and life insurance companies has been

68

approach this article derived explicit formulae for optimal asset allocations taking into

account possible future realizations in a multi period discrete time model

Wang Jennifer L HC Huang Sharon S Yang Jeffrey T Tsai (2010) conducted a study

to examine the dealing of natural hedging strategy with longevity risks for life insurance

companies The study proposed an immunization model which incorporated a stochastic

mortality dynamic to calculate the optimal life insurance annuity product mix ratio to hedge

against longevity risks The study mode the use of the changes in future mortality using the

well known Lee Carter model and discuss the model risk issue by comparing the results

between the Lee Carter and Cairns Blake Dowd models On the basis of the mortality

experience and insurance products in the United States it was demonstrated that the

proposed model can lead to an optimal product mix and effectively reduce longevity risks for

life insurance companies

Liebenberg Andre P James M Carson Robert E Hoyt (2010) stated that the previous

research has examined the demand for life insurance policy loans using aggregate policy loan

data In contrast the study uses a detailed household survey data set containing life insurance

and policy loan information Four hypotheses traditionally associated with policy loan

demand were tested The research provided the first US evidence (in the post world war II

period) in support of the policy loan emergency fund hypothesis In particular it was found

that the more detailed emergency fund proxies used revealed a significantly positive relation

between loan demand and recent expense or income shocks

Corsaro S Angelis PL De Perla Z Marino Znetti P (2010) discussed the development

of portfolios valuation system of asset liability management for life insurance policies on

advanced architectures The first aim of the study was to introduce a change in the stochastic

processes for the risk sources thus providing estimates under the forward risk neutral

measure which results for gain in accuracy The Monte Carlo method was then introduced to

speed up the simulation process According to new rules of solvency II project numerical

simulations must provide reliable estimates of the relevant quantities involved in the

contracts Therefore valuation process has to rely on accurate algorithms able to provide

solutions in a suitable turnaround time

Sinha Ram Pratap (2010) compared fifteen life insurance companies operating in India

from 2005-06 to 2008-09 using the old and new Revenue Maximizing Approach The

69

difference between the two approaches lies in the specification of the production possibility

set In both the approaches only the Life Insurance Corporation of India (LIC) was found to

be efficient for the observed years followed by Sahara life very closely However since in

the old approach the technically inefficient firms are penalized very harshly the grand mean

technical efficiency score is less than fifty percent to that in the new approach

Dutta A and Sengupta PP (2010) focused on the important investment issue They tried to

answer about whether increasing investment on IT infrastructure (which is resulting into a

technological innovation in business operation of the private companies) has a favorable

impact on efficiency or not For the purpose a panel data set of twelve private life insurance

companies over the financial period 2006-2009 was taken The efficiency was evaluated by

applying Data Envelopment Analysis (DEA) and calculating the scale efficiency The results

showed that increasing investment on IT infrastructure had a positive impact on scale and

technical efficiency change if constant and variable returns to scale assumptions were

considered

Rao Ananth Kashani Hossein and Marie Attiea (2010) analyzed the efficiency and

productivity issues of the insurance sector from the policymakers as well as investors view

point so as to insulate the business and financial risks of UAE corporate houses The paper

uses two inputs of administrative amp general expenses and equity amp change in legal reserves

versus two outputs of rate of return on investments and liquid assets to total liability ratio to

assess the allocative efficiency of companies using DEA The data set for nineteen insurers in

the region was considered for the study To evaluate the performance of the insurers the

efficiency is broken down in to technical and scale efficiency by using malmquist

productivity index Considerable degree of managerial inefficiency among the insurers with

least efficiency in 2000 and highest efficiency in 2004 was observed as a result Further the

insurers achieved a mere 08 percent annual gain in total factor productivity over the study

period

Alamelu K (2011) stated that the insurance sector in India was dominated by the state

owned Life Insurance Corporation (LIC) and the General Insurance Corporation (GIC) along

with its four subsidiaries But in 1999 the Insurance Regulatory and Development Authority

(IRDA) bill opened it up to private and foreign players whose share in the insurance market

has been rising The IRDA is the regulatory authority of the insurance sector entrusted with

70

protecting the interests of the insurance policy holders and regulating promoting and

ensuring orderly growth of the insurance industry in India As financial intermediaries life

insurers tap savings of the public in the form of premium In order to sustain public

confidence they have to maintain their financial credibility intact In other words a strong

financial background enables insurance companies to augment their business The

International Monetary Fund (IMF) suggested a number of indicators to diagnose the health

of the insurance sector This paper makes an attempt to analyze the financial soundness of

Indian Life Insurance Companies in terms of capital adequacy asset quality reinsurance

management soundness earnings and profitability liquidity and solvency ratios

Andreas Milidonis Konstantinos Stathopoulos (2011) tried to find the relation between

executive compensation and market implied default risk for listed insurance firms from 1992

to 2007 Shareholders are expected to encourage managerial risk sharing through equity

based incentive compensation Thus it was found that long term incentives and other share

based plans do not affect the default risk faced by firms However the extensive use of stock

options leads to higher future default risk for insurance firms It was argued that this is

because option based incentives induce managerial risk taking behaviour which seeks to

maximize managerial payoff through equity volatility This could be detrimental to the

interests of shareholders especially during a financial crisis

Dutta Anirban Sengupta Partha Pratim (2011) stated that efficiency is the key concern

of policymakers to encourage further development of the insurance industry as well as for the

managers of the insurance companies to exist profitably in the business in the long run and

used a panel dataset of fourteen life insurance companies over the period 2004ndash09 to

evaluate their efficiency scores by applying Data Envelopment Analysis and calculating the

scale efficiency The results render light on policy design and implementations for future

development of the life insurance industry in India

Neelaveni V (2012) stated that the evaluation of financial performance of the life insurance

companies is essentially needed to select the a best life insurance policy Therefore five life

insurance companies are randomly selected at the time of 2002-03 and evaluated in terms of

performance It is because with reforms of regulations and opening up of the insurance

sector to the private management in the year 1999 tough competition can be seen in the

insurance industry The number of general insurance and life insurance companies has been

69

difference between the two approaches lies in the specification of the production possibility

set In both the approaches only the Life Insurance Corporation of India (LIC) was found to

be efficient for the observed years followed by Sahara life very closely However since in

the old approach the technically inefficient firms are penalized very harshly the grand mean

technical efficiency score is less than fifty percent to that in the new approach

Dutta A and Sengupta PP (2010) focused on the important investment issue They tried to

answer about whether increasing investment on IT infrastructure (which is resulting into a

technological innovation in business operation of the private companies) has a favorable

impact on efficiency or not For the purpose a panel data set of twelve private life insurance

companies over the financial period 2006-2009 was taken The efficiency was evaluated by

applying Data Envelopment Analysis (DEA) and calculating the scale efficiency The results

showed that increasing investment on IT infrastructure had a positive impact on scale and

technical efficiency change if constant and variable returns to scale assumptions were

considered

Rao Ananth Kashani Hossein and Marie Attiea (2010) analyzed the efficiency and

productivity issues of the insurance sector from the policymakers as well as investors view

point so as to insulate the business and financial risks of UAE corporate houses The paper

uses two inputs of administrative amp general expenses and equity amp change in legal reserves

versus two outputs of rate of return on investments and liquid assets to total liability ratio to

assess the allocative efficiency of companies using DEA The data set for nineteen insurers in

the region was considered for the study To evaluate the performance of the insurers the

efficiency is broken down in to technical and scale efficiency by using malmquist

productivity index Considerable degree of managerial inefficiency among the insurers with

least efficiency in 2000 and highest efficiency in 2004 was observed as a result Further the

insurers achieved a mere 08 percent annual gain in total factor productivity over the study

period

Alamelu K (2011) stated that the insurance sector in India was dominated by the state

owned Life Insurance Corporation (LIC) and the General Insurance Corporation (GIC) along

with its four subsidiaries But in 1999 the Insurance Regulatory and Development Authority

(IRDA) bill opened it up to private and foreign players whose share in the insurance market

has been rising The IRDA is the regulatory authority of the insurance sector entrusted with

70

protecting the interests of the insurance policy holders and regulating promoting and

ensuring orderly growth of the insurance industry in India As financial intermediaries life

insurers tap savings of the public in the form of premium In order to sustain public

confidence they have to maintain their financial credibility intact In other words a strong

financial background enables insurance companies to augment their business The

International Monetary Fund (IMF) suggested a number of indicators to diagnose the health

of the insurance sector This paper makes an attempt to analyze the financial soundness of

Indian Life Insurance Companies in terms of capital adequacy asset quality reinsurance

management soundness earnings and profitability liquidity and solvency ratios

Andreas Milidonis Konstantinos Stathopoulos (2011) tried to find the relation between

executive compensation and market implied default risk for listed insurance firms from 1992

to 2007 Shareholders are expected to encourage managerial risk sharing through equity

based incentive compensation Thus it was found that long term incentives and other share

based plans do not affect the default risk faced by firms However the extensive use of stock

options leads to higher future default risk for insurance firms It was argued that this is

because option based incentives induce managerial risk taking behaviour which seeks to

maximize managerial payoff through equity volatility This could be detrimental to the

interests of shareholders especially during a financial crisis

Dutta Anirban Sengupta Partha Pratim (2011) stated that efficiency is the key concern

of policymakers to encourage further development of the insurance industry as well as for the

managers of the insurance companies to exist profitably in the business in the long run and

used a panel dataset of fourteen life insurance companies over the period 2004ndash09 to

evaluate their efficiency scores by applying Data Envelopment Analysis and calculating the

scale efficiency The results render light on policy design and implementations for future

development of the life insurance industry in India

Neelaveni V (2012) stated that the evaluation of financial performance of the life insurance

companies is essentially needed to select the a best life insurance policy Therefore five life

insurance companies are randomly selected at the time of 2002-03 and evaluated in terms of

performance It is because with reforms of regulations and opening up of the insurance

sector to the private management in the year 1999 tough competition can be seen in the

insurance industry The number of general insurance and life insurance companies has been

70

protecting the interests of the insurance policy holders and regulating promoting and

ensuring orderly growth of the insurance industry in India As financial intermediaries life

insurers tap savings of the public in the form of premium In order to sustain public

confidence they have to maintain their financial credibility intact In other words a strong

financial background enables insurance companies to augment their business The

International Monetary Fund (IMF) suggested a number of indicators to diagnose the health

of the insurance sector This paper makes an attempt to analyze the financial soundness of

Indian Life Insurance Companies in terms of capital adequacy asset quality reinsurance

management soundness earnings and profitability liquidity and solvency ratios

Andreas Milidonis Konstantinos Stathopoulos (2011) tried to find the relation between

executive compensation and market implied default risk for listed insurance firms from 1992

to 2007 Shareholders are expected to encourage managerial risk sharing through equity

based incentive compensation Thus it was found that long term incentives and other share

based plans do not affect the default risk faced by firms However the extensive use of stock

options leads to higher future default risk for insurance firms It was argued that this is

because option based incentives induce managerial risk taking behaviour which seeks to

maximize managerial payoff through equity volatility This could be detrimental to the

interests of shareholders especially during a financial crisis

Dutta Anirban Sengupta Partha Pratim (2011) stated that efficiency is the key concern

of policymakers to encourage further development of the insurance industry as well as for the

managers of the insurance companies to exist profitably in the business in the long run and

used a panel dataset of fourteen life insurance companies over the period 2004ndash09 to

evaluate their efficiency scores by applying Data Envelopment Analysis and calculating the

scale efficiency The results render light on policy design and implementations for future

development of the life insurance industry in India

Neelaveni V (2012) stated that the evaluation of financial performance of the life insurance

companies is essentially needed to select the a best life insurance policy Therefore five life

insurance companies are randomly selected at the time of 2002-03 and evaluated in terms of

performance It is because with reforms of regulations and opening up of the insurance

sector to the private management in the year 1999 tough competition can be seen in the

insurance industry The number of general insurance and life insurance companies has been

71

increasing in the 21st century The ultimate person is an investor or customer who has to get

the update information observe keenly the performance of the companies and their attractive

products

Charumathi B (2012) tried to model the factors determining the profitability of life insurers

operating in India taking return on asset as dependent variable All the twenty three Indian

life insurers (including one public and twenty two private) were included in the sample for

study and the data pertaining to three financial years viz 2008-09 2009-10 and 2010-11

was used For this purpose firm specific characteristics such as leverage size premium

growth liquidity underwriting risk and equity capital are regressed against return on assets

This study led to the conclusion that profitability of life insurers is positively and

significantly influenced by the size (as explained by logarithm of net premium) and liquidity

The leverage premium growth and logarithm of equity capital have negatively and

significantly influenced the profitability of Indian life insurers The study did not find any

evidence for the relationship between underwriting risk and profitability

Srivastava Arnika Tripathi sarika Kumar Amit (2012) explained the contribution of

insurance industry to the financial sector of an economy It was explored that the growth of

the insurance sector in India has been phenomenal The insurance industry has undergone a

massive change over the last few years There are numerous private and public sector

insurance companies in India that have become synonymous with the term insurance over the

years Offering a diversified product portfolio and excellent services many of the insurance

companies in India have managed to make their way into almost every Indian household

Chakraorty Kalyan Dutta Anirban and Partha Pratim Sengupta (2012) investigate

technical efficiency and productivity growth in Indian life insurance industry in the era of

deregulation The empirical study uses DEA method and Malmquist productivity index to

measure and decompose technical efficiency and productivity growth respectively The

results suggest that the growth in overall productivity is mainly attributed to improvement in

efficiency Higher pure technical efficiency and lower scale efficiency indicate the insurance

firms have generally moved away from the optimal scale over the study period The

truncated regression exploring the main drivers of efficiency in the long run found that the

claims ratio distribution ratio and firm-size have positively influenced technical efficiency

72

The study also found that the firms which had both life and non-life businesses are more

efficient than firms that has only life insurance business

Padhi Bidyadhar (2013) focused on the role and performance of private insurance

companies for the period from 2001 to 2012 The study reflected the performance of selected

private insurance companies in the areas like number of policies floated amount of premium

collected and the annual growth in the respective areas from 2001 to 2012 It was concluded

that the overall performances of all the private insurance companies are very satisfactory and

they need to continue this pace to penetrate their market more and more

Sharma Vikas Chowhan Sudhinder Singh (2013) made an attempt to analyse the

performance of public and private life insurance companies in India The data used in the

paper covers the period from 2006-07 to 2011-12For the analysis of data statistical tools

like percentages ratios growth rates and coefficient of variation have been used The results

showed that the LIC continues to dominate the sector Private sector insurance companies

also tried to increase their market share Private life insurers used the new business channels

of marketing to a great extent when compared with LIC Investment pattern of LIC and

private insurers also showed some differences Solvency ratio of private life insurers was

much better than LIC in spite of big losses suffered by them Lapsation ratio of private

insurers was higher than LIC and servicing of death claims was better in case of LIC as

compared to private life insurers

Sinha Ram Pratap (2013) estimated cost efficiency of the life insurance companies

operating in India for the period 2005-06 to 2009-10 using Farrell and Tones measure In

both the approaches it was found that the mean cost efficiency exhibit significant fluctuations

during the period under observation implying significant divergence from the frontier The

study also decomposes the Farrell measure of cost efficiency into input oriented technical

efficiency and allocative efficiency Further the cost efficiency estimates were related

(through a censored tobit model) to product and channel composition of the in-sample

insurance players

T Hymavathi Kumari (2013) aimed at understanding the life insurance sector in India and

flagging issues relating to competition in this sector Therefore an attempt has been made to

study the performance of life insurance industry in India in post liberalization era The

performance of public as well as private sector in terms of market share and growth has been

73

analyzed and it is stated that rapid rate of Indiarsquos economic growth has been one of the most

significant developments in the global economy This growth has its roots in the introduction

of economic liberalization of the early 1990s which has allowed India to exploit its economic

potential and raise the populationrsquos standard of living Opening up of the financial sector is

one of the financial reforms which the government was to implement as an integral part of

structural reforms and stabilization process of the economy Insurance has a very important

role in this process Government allowed the entrance of private players into the industry As

a result many private insurers also came into existence

Nena Sonal (2013) evaluated the performance of Life Insurance Corporation of India The

major source of income (Premium Earned) and the significant heads of expenses

(Commission amp Operating Expenses) of LIC are analyzed in order to measure the

performance during the period of study The study period consists of five years ie 2005-

2010 The performance evaluation showed consistent increase in the business of LIC During

the period of the study no major change in the performance of the LIC is observed So it

clarifies that the performance is unchanged and LIC has maintained the market value of their

products

Gulati Neelam (2014) analyzed the productivity in this paper Different variables have been

used to calculate the productivity viz- New Business Procured per Branch New Business

Per Active Agent Number of Policies Per Branch Number of Policies Per Agent Premium

Income Per Branch Premium Income Per Agent Ratio of Expenses to Premium Income

Complaints per Thousand Mean Number of Policies in Force Percentage of outstanding

Claims to total Claims Payable The study is based on secondary data The data has been

drawn from annual reports of LIC and IRDA and further have been tabulated and subject to

statistical calculations like t-value and CGR It is therefore concluded that LIC has been able

to earn higher rate of return as selected variables (except expenses) have increased

significantly The Compound Growth Rate has been found positive for income values and

negative for expense and claims payable As a result customer centered approach is going to

be the most compelling agenda for LIC in the coming years

74

SECTION-II

RESEARCH METHODOLOGY

Research methodology is the process of conducting research for research problem under

investigation Research methodology is the process of identification of the research

objectives keeping in view the findings of the previous studies collecting information and

analysis of the information for obtaining the objectives of the research Since Insurance

sector is growing at faster rate it seems to be the area of interest for researcher and

policyholder to know the Operating Efficiency of Life Insurance Companies in India

Furthermore Wikipedia explains operational efficiency as the ratio between the input to run

a business operation and the output gained from the business For the purpose of improving

operational efficiency the ratio of output to input must be improved This can be achieved by

having same output for less input more output for same input and much more output for less

input In addition ehowcom defines that operational efficiency minimizes waste and

maximizes resource capabilities in order to deliver quality products and services to

consumers It identifies wasteful processes and resources that drain the organizations profits

and can also design new work processes that improve quality and productivity Companies

are using several techniques to measure and gauge their operational efficiency Qualitative

approaches include benchmarking operations to industry standards and comparing and

evaluating performance to competitive companies Quantitative analysis techniques include

analyzing operations financial statements and the cost of goods

Need of the Study

In spite of India being second most populous country in the world Indiarsquos life insurance

density is very low as compared to the developed countries and developing countries This

shows that there is scope for life insurance sector to develop in India and hence the need for

the study emerges

Objectives of the Study

To describe the developments in Indian life insurance sector

To present a comparative analysis of operational efficiency of Indian life insurance

companies using CARAMEL model

To compare the Revenue Efficiency of life insurance companies operating in India

75

To evaluate the Cost Efficiency of Indian life insurance industry

To compare the Profit Efficiency of Indian life insurance companies

To arrive at the logical conclusions and to provide constructive suggestions to

increase the efficiency of life insurance companies

Scope of the Study

The study period ranges for the years starting from 2000-01 to 2011-12 Further while

calculating efficiency scores from DEA data from 2005-06 onwards is considered because of

non availability of consistent data for comparison in years prior to this The Life Insurance

Corporation of India and some of the private sector life insurance companies (excluding

those which started their operations after 14th

May 2002) are selected for the study

Therefore the profile of private sector life insurance companies is selected for the study and

those which are considered outside the scope of study are given below

Profile of Indian Life Insurance Companies Selected for the Study

S

No

Regn

No

Date of

Regn Name of the Company Abbreviation used

1 101 23-10-2000 HDFC Standard Life Insurance Company Ltd HSLIC

2 104 15-11-2000 Max Life Insurance Co Ltd MAX LIFE

3 105 24-11-2000 ICICI Prudential Life Insurance Company Ltd IPLIC

4 107 10-01-2001 Kotak Mahindra Old Mutual Life Insurance Ltd KOTAK MAHINDRA

5 109 31-01-2001 Birla Sun Life Insurance Company Ltd BSLIC

6 110 12-02-2001 Tata AIA Life Insurance Co Ltd TATA-AIA

7 111 30-03-2001 SBI Life Insurance Co Ltd SBI-LIFE

8 114 02-08-2001 ING Vysya Life Insurance Company Pvt Ltd ING-VYSYA

9 116 03-08-2001 Bajaj Allianz Life Insurance Company Ltd BAJAJ-ALLIANZ

10 117 06-08-2001 Met Life India Insurance Company Ltd MET-LIFE

11 121 03-01-2002 Reliance Life Insurance Company Ltd RELIANCE

12 122 14-05-2002 Aviva Life Insurance Co India Pvt Ltd AVIVA

Source Compiled from the Annual Reports of IRDA

76

Profile of Companies which are outside the Purview of the Study

Sr No Regn No Date of Regn Name of the Company

1 127 06-02-2004 Sahara India Life Insurance Company Ltd

2 128 17-11-2005 Shriram Life Insurance Company Ltd

3 130 14-07-2006 Bharti AXA Life Insurance Company Ltd

4 133 04-09-2007 Future Generali India Life Insurance Co Ltd

5 135 19-12-2007 IDBI Federal Life Insurance Co Ltd

6 136 08-05-2008 Canara HSBC Oriental Bank of Commerce Life

Insurance Company Ltd

7 138 27-06-2008 Aegon Religare Life Insurance Company Ltd

8 140 27-06-2008 DLF Pramerica Life Insurance Company Ltd

9 142 26-12-2008 Star Union Dai-ichi Life Insurance Co Ltd

10 143 05-11-2009 India First Life Insurance Company Ltd

11 147 10-05-2011 Edelweiss Tokio Life Insurance Company Ltd

Source Compiled from the Annual Reports of IRDA

Although the above stated companies are considered outside the purview of study but still

the data for these companies are combined in tables of chapter III under heading ldquoOthersrdquo

This is done so as to know the accurate percentage share of selected companies to total share

of life insurance industry

Collection of the Data

The study is based on secondary data To make the study more analytical amp scientific and to

arrive at definite conclusions the secondary data is collected from the Annual Reports Fact

Books Manual of the insurance and Websites of IRDA Life Insurance Corporation of India

and private life insurance companies etc Experts in the field were also approached for the

purpose of discussion to understand the problem in right perspective The work of

academicians on this subject has also been consulted for the purpose of analysis The analysis

is descriptive in nature

Statistical Tools Applied

At the time of analyzing the data various statistical tools such as CARAMEL Model

Mean Coefficient of Variation Data Envelopment Analysis Frequency Distribution

Compound Annual Growth Rate and Percentages have been used in analyzing the

variables

77

CARAMEL Model The model is used to evaluate the operational efficiency of life

insurance companies in India The model makes use of ratio analysis Ratio analysis is an

analysis of financial statements which is done with the help of Ratios A Ratio expresses the

relationship that exists between two numbers taken from the financial statements Ratio

analysis is among the best tools available with the analyst to analyze the financial

performance of a company as it allows inter-company and intra company comparison It also

provides a birdrsquos eye view regarding the financial condition of the company An overview of

CARAMEL Indicators used in chapter three of the study is presented in the table given

below

Overview of CARAMEL Indicators Used for Measuring Operational Efficiency

Type of FSI Aspects of

Financial

System

Selected Indicators used to monitor different aspects

of financial system

Financial

Soundness

Capital

Adequacy

CapitalTotal Assets

CapitalMathematical Reserves

Earnings

Profitability

Operating ExpensesNet Premium Underwritten

CommissionNet Premium Underwritten

Other ExpensesNet Premium Underwritten

ExpensesNet Premium Underwritten

Shareholders Investment IncomeShareholder Investment

Policyholders Investment IncomePolicyholders

Investment

Investment IncomeInvestment Assets

Return on Equity

(Profit after interest tax and dividendShare Capital)

Insurance

Sector

Vulnerabilities

Asset Quality EquityTotal Assets

Reinsurance

and Actuarial

Issues

Risk Retention Ratio (Net PremiumGross Premium)

Mathematical Reserves to Average of Net Premium

(ANP) received in last three years

Management

Soundness

Operating ExpensesGross Premium

Liquidity Liquid AssetsCurrent Liabilities

Solvency Net AssetsNet Premium Underwritten

78

After approaching towards the results of the above mentioned ratios rank to each

parameter is assigned on the basis of average ratio and at last the composite ranking of

CARAMEL framework is made in order to arrive at conclusions

Data Envelopment Analysis (DEA)

Data Envelopment Analysis (DEA) is a methodology based upon an interesting application

of linear programming It was originally developed for performance measurement It has

been successfully employed for assessing the relative performance of a set of firms that use a

variety of identical inputs to produce a variety of identical outputs It is a technique based on

linear programming It is used to measure the performance efficiency of organizational units

which are termed as (DMUs) This technique aims at measuring how efficiently a DMU uses

resources available to generate a set of outputs (Charnes et al1978) Decision Making Units

can include manufacturing units departments of big organizations such as universities

schools bank branches hospitals power plants police stations tax offices prisons defence

basis a set of firms or even practising individuals such as medical practitioners The

performance of DMUs is assessed in DEA using the concept of efficiency or productivity

which is the ratio of total outputs to total inputs The best performing Decision Making Unit

is assigned an efficiency score of unity The performances of other DMUs vary between zero

to one

Here in this study Efficiency is computed in terms of Revenue Cost and Profit using

DEA-Solver Pro 50 version of Data Envelopment Analysis and is presented in chapter

four The chapter is divided in to three sections ie Revenue efficiency Cost efficiency

and Profit efficiency of life insurance companies operating in India

Inputs and Outputs selected for the study Inputs and outputs selected for three different

types of efficiencies are as follows

1 For computing Revenue efficiency New-Revenue-V approach is used and

following data set for input output is used

Inputs (I)

Commission expenses

Operating expenses

79

Output (O)

Number of policies

Price (P)

Sum assured per policy

2 Cost efficiency is calculated using New-Cost-V approach of DEA The inputs and

output used to compute the cost efficiency score are as follows

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Sum assured per policy

3 New-Profit-V approach of DEA is applied in order to evaluate the Profit efficiency of

Indian life insurers and the following input output combination is used

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Number of policies

Price (P)

Sum assured per policy

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

72

The study also found that the firms which had both life and non-life businesses are more

efficient than firms that has only life insurance business

Padhi Bidyadhar (2013) focused on the role and performance of private insurance

companies for the period from 2001 to 2012 The study reflected the performance of selected

private insurance companies in the areas like number of policies floated amount of premium

collected and the annual growth in the respective areas from 2001 to 2012 It was concluded

that the overall performances of all the private insurance companies are very satisfactory and

they need to continue this pace to penetrate their market more and more

Sharma Vikas Chowhan Sudhinder Singh (2013) made an attempt to analyse the

performance of public and private life insurance companies in India The data used in the

paper covers the period from 2006-07 to 2011-12For the analysis of data statistical tools

like percentages ratios growth rates and coefficient of variation have been used The results

showed that the LIC continues to dominate the sector Private sector insurance companies

also tried to increase their market share Private life insurers used the new business channels

of marketing to a great extent when compared with LIC Investment pattern of LIC and

private insurers also showed some differences Solvency ratio of private life insurers was

much better than LIC in spite of big losses suffered by them Lapsation ratio of private

insurers was higher than LIC and servicing of death claims was better in case of LIC as

compared to private life insurers

Sinha Ram Pratap (2013) estimated cost efficiency of the life insurance companies

operating in India for the period 2005-06 to 2009-10 using Farrell and Tones measure In

both the approaches it was found that the mean cost efficiency exhibit significant fluctuations

during the period under observation implying significant divergence from the frontier The

study also decomposes the Farrell measure of cost efficiency into input oriented technical

efficiency and allocative efficiency Further the cost efficiency estimates were related

(through a censored tobit model) to product and channel composition of the in-sample

insurance players

T Hymavathi Kumari (2013) aimed at understanding the life insurance sector in India and

flagging issues relating to competition in this sector Therefore an attempt has been made to

study the performance of life insurance industry in India in post liberalization era The

performance of public as well as private sector in terms of market share and growth has been

73

analyzed and it is stated that rapid rate of Indiarsquos economic growth has been one of the most

significant developments in the global economy This growth has its roots in the introduction

of economic liberalization of the early 1990s which has allowed India to exploit its economic

potential and raise the populationrsquos standard of living Opening up of the financial sector is

one of the financial reforms which the government was to implement as an integral part of

structural reforms and stabilization process of the economy Insurance has a very important

role in this process Government allowed the entrance of private players into the industry As

a result many private insurers also came into existence

Nena Sonal (2013) evaluated the performance of Life Insurance Corporation of India The

major source of income (Premium Earned) and the significant heads of expenses

(Commission amp Operating Expenses) of LIC are analyzed in order to measure the

performance during the period of study The study period consists of five years ie 2005-

2010 The performance evaluation showed consistent increase in the business of LIC During

the period of the study no major change in the performance of the LIC is observed So it

clarifies that the performance is unchanged and LIC has maintained the market value of their

products

Gulati Neelam (2014) analyzed the productivity in this paper Different variables have been

used to calculate the productivity viz- New Business Procured per Branch New Business

Per Active Agent Number of Policies Per Branch Number of Policies Per Agent Premium

Income Per Branch Premium Income Per Agent Ratio of Expenses to Premium Income

Complaints per Thousand Mean Number of Policies in Force Percentage of outstanding

Claims to total Claims Payable The study is based on secondary data The data has been

drawn from annual reports of LIC and IRDA and further have been tabulated and subject to

statistical calculations like t-value and CGR It is therefore concluded that LIC has been able

to earn higher rate of return as selected variables (except expenses) have increased

significantly The Compound Growth Rate has been found positive for income values and

negative for expense and claims payable As a result customer centered approach is going to

be the most compelling agenda for LIC in the coming years

74

SECTION-II

RESEARCH METHODOLOGY

Research methodology is the process of conducting research for research problem under

investigation Research methodology is the process of identification of the research

objectives keeping in view the findings of the previous studies collecting information and

analysis of the information for obtaining the objectives of the research Since Insurance

sector is growing at faster rate it seems to be the area of interest for researcher and

policyholder to know the Operating Efficiency of Life Insurance Companies in India

Furthermore Wikipedia explains operational efficiency as the ratio between the input to run

a business operation and the output gained from the business For the purpose of improving

operational efficiency the ratio of output to input must be improved This can be achieved by

having same output for less input more output for same input and much more output for less

input In addition ehowcom defines that operational efficiency minimizes waste and

maximizes resource capabilities in order to deliver quality products and services to

consumers It identifies wasteful processes and resources that drain the organizations profits

and can also design new work processes that improve quality and productivity Companies

are using several techniques to measure and gauge their operational efficiency Qualitative

approaches include benchmarking operations to industry standards and comparing and

evaluating performance to competitive companies Quantitative analysis techniques include

analyzing operations financial statements and the cost of goods

Need of the Study

In spite of India being second most populous country in the world Indiarsquos life insurance

density is very low as compared to the developed countries and developing countries This

shows that there is scope for life insurance sector to develop in India and hence the need for

the study emerges

Objectives of the Study

To describe the developments in Indian life insurance sector

To present a comparative analysis of operational efficiency of Indian life insurance

companies using CARAMEL model

To compare the Revenue Efficiency of life insurance companies operating in India

75

To evaluate the Cost Efficiency of Indian life insurance industry

To compare the Profit Efficiency of Indian life insurance companies

To arrive at the logical conclusions and to provide constructive suggestions to

increase the efficiency of life insurance companies

Scope of the Study

The study period ranges for the years starting from 2000-01 to 2011-12 Further while

calculating efficiency scores from DEA data from 2005-06 onwards is considered because of

non availability of consistent data for comparison in years prior to this The Life Insurance

Corporation of India and some of the private sector life insurance companies (excluding

those which started their operations after 14th

May 2002) are selected for the study

Therefore the profile of private sector life insurance companies is selected for the study and

those which are considered outside the scope of study are given below

Profile of Indian Life Insurance Companies Selected for the Study

S

No

Regn

No

Date of

Regn Name of the Company Abbreviation used

1 101 23-10-2000 HDFC Standard Life Insurance Company Ltd HSLIC

2 104 15-11-2000 Max Life Insurance Co Ltd MAX LIFE

3 105 24-11-2000 ICICI Prudential Life Insurance Company Ltd IPLIC

4 107 10-01-2001 Kotak Mahindra Old Mutual Life Insurance Ltd KOTAK MAHINDRA

5 109 31-01-2001 Birla Sun Life Insurance Company Ltd BSLIC

6 110 12-02-2001 Tata AIA Life Insurance Co Ltd TATA-AIA

7 111 30-03-2001 SBI Life Insurance Co Ltd SBI-LIFE

8 114 02-08-2001 ING Vysya Life Insurance Company Pvt Ltd ING-VYSYA

9 116 03-08-2001 Bajaj Allianz Life Insurance Company Ltd BAJAJ-ALLIANZ

10 117 06-08-2001 Met Life India Insurance Company Ltd MET-LIFE

11 121 03-01-2002 Reliance Life Insurance Company Ltd RELIANCE

12 122 14-05-2002 Aviva Life Insurance Co India Pvt Ltd AVIVA

Source Compiled from the Annual Reports of IRDA

76

Profile of Companies which are outside the Purview of the Study

Sr No Regn No Date of Regn Name of the Company

1 127 06-02-2004 Sahara India Life Insurance Company Ltd

2 128 17-11-2005 Shriram Life Insurance Company Ltd

3 130 14-07-2006 Bharti AXA Life Insurance Company Ltd

4 133 04-09-2007 Future Generali India Life Insurance Co Ltd

5 135 19-12-2007 IDBI Federal Life Insurance Co Ltd

6 136 08-05-2008 Canara HSBC Oriental Bank of Commerce Life

Insurance Company Ltd

7 138 27-06-2008 Aegon Religare Life Insurance Company Ltd

8 140 27-06-2008 DLF Pramerica Life Insurance Company Ltd

9 142 26-12-2008 Star Union Dai-ichi Life Insurance Co Ltd

10 143 05-11-2009 India First Life Insurance Company Ltd

11 147 10-05-2011 Edelweiss Tokio Life Insurance Company Ltd

Source Compiled from the Annual Reports of IRDA

Although the above stated companies are considered outside the purview of study but still

the data for these companies are combined in tables of chapter III under heading ldquoOthersrdquo

This is done so as to know the accurate percentage share of selected companies to total share

of life insurance industry

Collection of the Data

The study is based on secondary data To make the study more analytical amp scientific and to

arrive at definite conclusions the secondary data is collected from the Annual Reports Fact

Books Manual of the insurance and Websites of IRDA Life Insurance Corporation of India

and private life insurance companies etc Experts in the field were also approached for the

purpose of discussion to understand the problem in right perspective The work of

academicians on this subject has also been consulted for the purpose of analysis The analysis

is descriptive in nature

Statistical Tools Applied

At the time of analyzing the data various statistical tools such as CARAMEL Model

Mean Coefficient of Variation Data Envelopment Analysis Frequency Distribution

Compound Annual Growth Rate and Percentages have been used in analyzing the

variables

77

CARAMEL Model The model is used to evaluate the operational efficiency of life

insurance companies in India The model makes use of ratio analysis Ratio analysis is an

analysis of financial statements which is done with the help of Ratios A Ratio expresses the

relationship that exists between two numbers taken from the financial statements Ratio

analysis is among the best tools available with the analyst to analyze the financial

performance of a company as it allows inter-company and intra company comparison It also

provides a birdrsquos eye view regarding the financial condition of the company An overview of

CARAMEL Indicators used in chapter three of the study is presented in the table given

below

Overview of CARAMEL Indicators Used for Measuring Operational Efficiency

Type of FSI Aspects of

Financial

System

Selected Indicators used to monitor different aspects

of financial system

Financial

Soundness

Capital

Adequacy

CapitalTotal Assets

CapitalMathematical Reserves

Earnings

Profitability

Operating ExpensesNet Premium Underwritten

CommissionNet Premium Underwritten

Other ExpensesNet Premium Underwritten

ExpensesNet Premium Underwritten

Shareholders Investment IncomeShareholder Investment

Policyholders Investment IncomePolicyholders

Investment

Investment IncomeInvestment Assets

Return on Equity

(Profit after interest tax and dividendShare Capital)

Insurance

Sector

Vulnerabilities

Asset Quality EquityTotal Assets

Reinsurance

and Actuarial

Issues

Risk Retention Ratio (Net PremiumGross Premium)

Mathematical Reserves to Average of Net Premium

(ANP) received in last three years

Management

Soundness

Operating ExpensesGross Premium

Liquidity Liquid AssetsCurrent Liabilities

Solvency Net AssetsNet Premium Underwritten

78

After approaching towards the results of the above mentioned ratios rank to each

parameter is assigned on the basis of average ratio and at last the composite ranking of

CARAMEL framework is made in order to arrive at conclusions

Data Envelopment Analysis (DEA)

Data Envelopment Analysis (DEA) is a methodology based upon an interesting application

of linear programming It was originally developed for performance measurement It has

been successfully employed for assessing the relative performance of a set of firms that use a

variety of identical inputs to produce a variety of identical outputs It is a technique based on

linear programming It is used to measure the performance efficiency of organizational units

which are termed as (DMUs) This technique aims at measuring how efficiently a DMU uses

resources available to generate a set of outputs (Charnes et al1978) Decision Making Units

can include manufacturing units departments of big organizations such as universities

schools bank branches hospitals power plants police stations tax offices prisons defence

basis a set of firms or even practising individuals such as medical practitioners The

performance of DMUs is assessed in DEA using the concept of efficiency or productivity

which is the ratio of total outputs to total inputs The best performing Decision Making Unit

is assigned an efficiency score of unity The performances of other DMUs vary between zero

to one

Here in this study Efficiency is computed in terms of Revenue Cost and Profit using

DEA-Solver Pro 50 version of Data Envelopment Analysis and is presented in chapter

four The chapter is divided in to three sections ie Revenue efficiency Cost efficiency

and Profit efficiency of life insurance companies operating in India

Inputs and Outputs selected for the study Inputs and outputs selected for three different

types of efficiencies are as follows

1 For computing Revenue efficiency New-Revenue-V approach is used and

following data set for input output is used

Inputs (I)

Commission expenses

Operating expenses

79

Output (O)

Number of policies

Price (P)

Sum assured per policy

2 Cost efficiency is calculated using New-Cost-V approach of DEA The inputs and

output used to compute the cost efficiency score are as follows

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Sum assured per policy

3 New-Profit-V approach of DEA is applied in order to evaluate the Profit efficiency of

Indian life insurers and the following input output combination is used

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Number of policies

Price (P)

Sum assured per policy

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

73

analyzed and it is stated that rapid rate of Indiarsquos economic growth has been one of the most

significant developments in the global economy This growth has its roots in the introduction

of economic liberalization of the early 1990s which has allowed India to exploit its economic

potential and raise the populationrsquos standard of living Opening up of the financial sector is

one of the financial reforms which the government was to implement as an integral part of

structural reforms and stabilization process of the economy Insurance has a very important

role in this process Government allowed the entrance of private players into the industry As

a result many private insurers also came into existence

Nena Sonal (2013) evaluated the performance of Life Insurance Corporation of India The

major source of income (Premium Earned) and the significant heads of expenses

(Commission amp Operating Expenses) of LIC are analyzed in order to measure the

performance during the period of study The study period consists of five years ie 2005-

2010 The performance evaluation showed consistent increase in the business of LIC During

the period of the study no major change in the performance of the LIC is observed So it

clarifies that the performance is unchanged and LIC has maintained the market value of their

products

Gulati Neelam (2014) analyzed the productivity in this paper Different variables have been

used to calculate the productivity viz- New Business Procured per Branch New Business

Per Active Agent Number of Policies Per Branch Number of Policies Per Agent Premium

Income Per Branch Premium Income Per Agent Ratio of Expenses to Premium Income

Complaints per Thousand Mean Number of Policies in Force Percentage of outstanding

Claims to total Claims Payable The study is based on secondary data The data has been

drawn from annual reports of LIC and IRDA and further have been tabulated and subject to

statistical calculations like t-value and CGR It is therefore concluded that LIC has been able

to earn higher rate of return as selected variables (except expenses) have increased

significantly The Compound Growth Rate has been found positive for income values and

negative for expense and claims payable As a result customer centered approach is going to

be the most compelling agenda for LIC in the coming years

74

SECTION-II

RESEARCH METHODOLOGY

Research methodology is the process of conducting research for research problem under

investigation Research methodology is the process of identification of the research

objectives keeping in view the findings of the previous studies collecting information and

analysis of the information for obtaining the objectives of the research Since Insurance

sector is growing at faster rate it seems to be the area of interest for researcher and

policyholder to know the Operating Efficiency of Life Insurance Companies in India

Furthermore Wikipedia explains operational efficiency as the ratio between the input to run

a business operation and the output gained from the business For the purpose of improving

operational efficiency the ratio of output to input must be improved This can be achieved by

having same output for less input more output for same input and much more output for less

input In addition ehowcom defines that operational efficiency minimizes waste and

maximizes resource capabilities in order to deliver quality products and services to

consumers It identifies wasteful processes and resources that drain the organizations profits

and can also design new work processes that improve quality and productivity Companies

are using several techniques to measure and gauge their operational efficiency Qualitative

approaches include benchmarking operations to industry standards and comparing and

evaluating performance to competitive companies Quantitative analysis techniques include

analyzing operations financial statements and the cost of goods

Need of the Study

In spite of India being second most populous country in the world Indiarsquos life insurance

density is very low as compared to the developed countries and developing countries This

shows that there is scope for life insurance sector to develop in India and hence the need for

the study emerges

Objectives of the Study

To describe the developments in Indian life insurance sector

To present a comparative analysis of operational efficiency of Indian life insurance

companies using CARAMEL model

To compare the Revenue Efficiency of life insurance companies operating in India

75

To evaluate the Cost Efficiency of Indian life insurance industry

To compare the Profit Efficiency of Indian life insurance companies

To arrive at the logical conclusions and to provide constructive suggestions to

increase the efficiency of life insurance companies

Scope of the Study

The study period ranges for the years starting from 2000-01 to 2011-12 Further while

calculating efficiency scores from DEA data from 2005-06 onwards is considered because of

non availability of consistent data for comparison in years prior to this The Life Insurance

Corporation of India and some of the private sector life insurance companies (excluding

those which started their operations after 14th

May 2002) are selected for the study

Therefore the profile of private sector life insurance companies is selected for the study and

those which are considered outside the scope of study are given below

Profile of Indian Life Insurance Companies Selected for the Study

S

No

Regn

No

Date of

Regn Name of the Company Abbreviation used

1 101 23-10-2000 HDFC Standard Life Insurance Company Ltd HSLIC

2 104 15-11-2000 Max Life Insurance Co Ltd MAX LIFE

3 105 24-11-2000 ICICI Prudential Life Insurance Company Ltd IPLIC

4 107 10-01-2001 Kotak Mahindra Old Mutual Life Insurance Ltd KOTAK MAHINDRA

5 109 31-01-2001 Birla Sun Life Insurance Company Ltd BSLIC

6 110 12-02-2001 Tata AIA Life Insurance Co Ltd TATA-AIA

7 111 30-03-2001 SBI Life Insurance Co Ltd SBI-LIFE

8 114 02-08-2001 ING Vysya Life Insurance Company Pvt Ltd ING-VYSYA

9 116 03-08-2001 Bajaj Allianz Life Insurance Company Ltd BAJAJ-ALLIANZ

10 117 06-08-2001 Met Life India Insurance Company Ltd MET-LIFE

11 121 03-01-2002 Reliance Life Insurance Company Ltd RELIANCE

12 122 14-05-2002 Aviva Life Insurance Co India Pvt Ltd AVIVA

Source Compiled from the Annual Reports of IRDA

76

Profile of Companies which are outside the Purview of the Study

Sr No Regn No Date of Regn Name of the Company

1 127 06-02-2004 Sahara India Life Insurance Company Ltd

2 128 17-11-2005 Shriram Life Insurance Company Ltd

3 130 14-07-2006 Bharti AXA Life Insurance Company Ltd

4 133 04-09-2007 Future Generali India Life Insurance Co Ltd

5 135 19-12-2007 IDBI Federal Life Insurance Co Ltd

6 136 08-05-2008 Canara HSBC Oriental Bank of Commerce Life

Insurance Company Ltd

7 138 27-06-2008 Aegon Religare Life Insurance Company Ltd

8 140 27-06-2008 DLF Pramerica Life Insurance Company Ltd

9 142 26-12-2008 Star Union Dai-ichi Life Insurance Co Ltd

10 143 05-11-2009 India First Life Insurance Company Ltd

11 147 10-05-2011 Edelweiss Tokio Life Insurance Company Ltd

Source Compiled from the Annual Reports of IRDA

Although the above stated companies are considered outside the purview of study but still

the data for these companies are combined in tables of chapter III under heading ldquoOthersrdquo

This is done so as to know the accurate percentage share of selected companies to total share

of life insurance industry

Collection of the Data

The study is based on secondary data To make the study more analytical amp scientific and to

arrive at definite conclusions the secondary data is collected from the Annual Reports Fact

Books Manual of the insurance and Websites of IRDA Life Insurance Corporation of India

and private life insurance companies etc Experts in the field were also approached for the

purpose of discussion to understand the problem in right perspective The work of

academicians on this subject has also been consulted for the purpose of analysis The analysis

is descriptive in nature

Statistical Tools Applied

At the time of analyzing the data various statistical tools such as CARAMEL Model

Mean Coefficient of Variation Data Envelopment Analysis Frequency Distribution

Compound Annual Growth Rate and Percentages have been used in analyzing the

variables

77

CARAMEL Model The model is used to evaluate the operational efficiency of life

insurance companies in India The model makes use of ratio analysis Ratio analysis is an

analysis of financial statements which is done with the help of Ratios A Ratio expresses the

relationship that exists between two numbers taken from the financial statements Ratio

analysis is among the best tools available with the analyst to analyze the financial

performance of a company as it allows inter-company and intra company comparison It also

provides a birdrsquos eye view regarding the financial condition of the company An overview of

CARAMEL Indicators used in chapter three of the study is presented in the table given

below

Overview of CARAMEL Indicators Used for Measuring Operational Efficiency

Type of FSI Aspects of

Financial

System

Selected Indicators used to monitor different aspects

of financial system

Financial

Soundness

Capital

Adequacy

CapitalTotal Assets

CapitalMathematical Reserves

Earnings

Profitability

Operating ExpensesNet Premium Underwritten

CommissionNet Premium Underwritten

Other ExpensesNet Premium Underwritten

ExpensesNet Premium Underwritten

Shareholders Investment IncomeShareholder Investment

Policyholders Investment IncomePolicyholders

Investment

Investment IncomeInvestment Assets

Return on Equity

(Profit after interest tax and dividendShare Capital)

Insurance

Sector

Vulnerabilities

Asset Quality EquityTotal Assets

Reinsurance

and Actuarial

Issues

Risk Retention Ratio (Net PremiumGross Premium)

Mathematical Reserves to Average of Net Premium

(ANP) received in last three years

Management

Soundness

Operating ExpensesGross Premium

Liquidity Liquid AssetsCurrent Liabilities

Solvency Net AssetsNet Premium Underwritten

78

After approaching towards the results of the above mentioned ratios rank to each

parameter is assigned on the basis of average ratio and at last the composite ranking of

CARAMEL framework is made in order to arrive at conclusions

Data Envelopment Analysis (DEA)

Data Envelopment Analysis (DEA) is a methodology based upon an interesting application

of linear programming It was originally developed for performance measurement It has

been successfully employed for assessing the relative performance of a set of firms that use a

variety of identical inputs to produce a variety of identical outputs It is a technique based on

linear programming It is used to measure the performance efficiency of organizational units

which are termed as (DMUs) This technique aims at measuring how efficiently a DMU uses

resources available to generate a set of outputs (Charnes et al1978) Decision Making Units

can include manufacturing units departments of big organizations such as universities

schools bank branches hospitals power plants police stations tax offices prisons defence

basis a set of firms or even practising individuals such as medical practitioners The

performance of DMUs is assessed in DEA using the concept of efficiency or productivity

which is the ratio of total outputs to total inputs The best performing Decision Making Unit

is assigned an efficiency score of unity The performances of other DMUs vary between zero

to one

Here in this study Efficiency is computed in terms of Revenue Cost and Profit using

DEA-Solver Pro 50 version of Data Envelopment Analysis and is presented in chapter

four The chapter is divided in to three sections ie Revenue efficiency Cost efficiency

and Profit efficiency of life insurance companies operating in India

Inputs and Outputs selected for the study Inputs and outputs selected for three different

types of efficiencies are as follows

1 For computing Revenue efficiency New-Revenue-V approach is used and

following data set for input output is used

Inputs (I)

Commission expenses

Operating expenses

79

Output (O)

Number of policies

Price (P)

Sum assured per policy

2 Cost efficiency is calculated using New-Cost-V approach of DEA The inputs and

output used to compute the cost efficiency score are as follows

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Sum assured per policy

3 New-Profit-V approach of DEA is applied in order to evaluate the Profit efficiency of

Indian life insurers and the following input output combination is used

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Number of policies

Price (P)

Sum assured per policy

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

74

SECTION-II

RESEARCH METHODOLOGY

Research methodology is the process of conducting research for research problem under

investigation Research methodology is the process of identification of the research

objectives keeping in view the findings of the previous studies collecting information and

analysis of the information for obtaining the objectives of the research Since Insurance

sector is growing at faster rate it seems to be the area of interest for researcher and

policyholder to know the Operating Efficiency of Life Insurance Companies in India

Furthermore Wikipedia explains operational efficiency as the ratio between the input to run

a business operation and the output gained from the business For the purpose of improving

operational efficiency the ratio of output to input must be improved This can be achieved by

having same output for less input more output for same input and much more output for less

input In addition ehowcom defines that operational efficiency minimizes waste and

maximizes resource capabilities in order to deliver quality products and services to

consumers It identifies wasteful processes and resources that drain the organizations profits

and can also design new work processes that improve quality and productivity Companies

are using several techniques to measure and gauge their operational efficiency Qualitative

approaches include benchmarking operations to industry standards and comparing and

evaluating performance to competitive companies Quantitative analysis techniques include

analyzing operations financial statements and the cost of goods

Need of the Study

In spite of India being second most populous country in the world Indiarsquos life insurance

density is very low as compared to the developed countries and developing countries This

shows that there is scope for life insurance sector to develop in India and hence the need for

the study emerges

Objectives of the Study

To describe the developments in Indian life insurance sector

To present a comparative analysis of operational efficiency of Indian life insurance

companies using CARAMEL model

To compare the Revenue Efficiency of life insurance companies operating in India

75

To evaluate the Cost Efficiency of Indian life insurance industry

To compare the Profit Efficiency of Indian life insurance companies

To arrive at the logical conclusions and to provide constructive suggestions to

increase the efficiency of life insurance companies

Scope of the Study

The study period ranges for the years starting from 2000-01 to 2011-12 Further while

calculating efficiency scores from DEA data from 2005-06 onwards is considered because of

non availability of consistent data for comparison in years prior to this The Life Insurance

Corporation of India and some of the private sector life insurance companies (excluding

those which started their operations after 14th

May 2002) are selected for the study

Therefore the profile of private sector life insurance companies is selected for the study and

those which are considered outside the scope of study are given below

Profile of Indian Life Insurance Companies Selected for the Study

S

No

Regn

No

Date of

Regn Name of the Company Abbreviation used

1 101 23-10-2000 HDFC Standard Life Insurance Company Ltd HSLIC

2 104 15-11-2000 Max Life Insurance Co Ltd MAX LIFE

3 105 24-11-2000 ICICI Prudential Life Insurance Company Ltd IPLIC

4 107 10-01-2001 Kotak Mahindra Old Mutual Life Insurance Ltd KOTAK MAHINDRA

5 109 31-01-2001 Birla Sun Life Insurance Company Ltd BSLIC

6 110 12-02-2001 Tata AIA Life Insurance Co Ltd TATA-AIA

7 111 30-03-2001 SBI Life Insurance Co Ltd SBI-LIFE

8 114 02-08-2001 ING Vysya Life Insurance Company Pvt Ltd ING-VYSYA

9 116 03-08-2001 Bajaj Allianz Life Insurance Company Ltd BAJAJ-ALLIANZ

10 117 06-08-2001 Met Life India Insurance Company Ltd MET-LIFE

11 121 03-01-2002 Reliance Life Insurance Company Ltd RELIANCE

12 122 14-05-2002 Aviva Life Insurance Co India Pvt Ltd AVIVA

Source Compiled from the Annual Reports of IRDA

76

Profile of Companies which are outside the Purview of the Study

Sr No Regn No Date of Regn Name of the Company

1 127 06-02-2004 Sahara India Life Insurance Company Ltd

2 128 17-11-2005 Shriram Life Insurance Company Ltd

3 130 14-07-2006 Bharti AXA Life Insurance Company Ltd

4 133 04-09-2007 Future Generali India Life Insurance Co Ltd

5 135 19-12-2007 IDBI Federal Life Insurance Co Ltd

6 136 08-05-2008 Canara HSBC Oriental Bank of Commerce Life

Insurance Company Ltd

7 138 27-06-2008 Aegon Religare Life Insurance Company Ltd

8 140 27-06-2008 DLF Pramerica Life Insurance Company Ltd

9 142 26-12-2008 Star Union Dai-ichi Life Insurance Co Ltd

10 143 05-11-2009 India First Life Insurance Company Ltd

11 147 10-05-2011 Edelweiss Tokio Life Insurance Company Ltd

Source Compiled from the Annual Reports of IRDA

Although the above stated companies are considered outside the purview of study but still

the data for these companies are combined in tables of chapter III under heading ldquoOthersrdquo

This is done so as to know the accurate percentage share of selected companies to total share

of life insurance industry

Collection of the Data

The study is based on secondary data To make the study more analytical amp scientific and to

arrive at definite conclusions the secondary data is collected from the Annual Reports Fact

Books Manual of the insurance and Websites of IRDA Life Insurance Corporation of India

and private life insurance companies etc Experts in the field were also approached for the

purpose of discussion to understand the problem in right perspective The work of

academicians on this subject has also been consulted for the purpose of analysis The analysis

is descriptive in nature

Statistical Tools Applied

At the time of analyzing the data various statistical tools such as CARAMEL Model

Mean Coefficient of Variation Data Envelopment Analysis Frequency Distribution

Compound Annual Growth Rate and Percentages have been used in analyzing the

variables

77

CARAMEL Model The model is used to evaluate the operational efficiency of life

insurance companies in India The model makes use of ratio analysis Ratio analysis is an

analysis of financial statements which is done with the help of Ratios A Ratio expresses the

relationship that exists between two numbers taken from the financial statements Ratio

analysis is among the best tools available with the analyst to analyze the financial

performance of a company as it allows inter-company and intra company comparison It also

provides a birdrsquos eye view regarding the financial condition of the company An overview of

CARAMEL Indicators used in chapter three of the study is presented in the table given

below

Overview of CARAMEL Indicators Used for Measuring Operational Efficiency

Type of FSI Aspects of

Financial

System

Selected Indicators used to monitor different aspects

of financial system

Financial

Soundness

Capital

Adequacy

CapitalTotal Assets

CapitalMathematical Reserves

Earnings

Profitability

Operating ExpensesNet Premium Underwritten

CommissionNet Premium Underwritten

Other ExpensesNet Premium Underwritten

ExpensesNet Premium Underwritten

Shareholders Investment IncomeShareholder Investment

Policyholders Investment IncomePolicyholders

Investment

Investment IncomeInvestment Assets

Return on Equity

(Profit after interest tax and dividendShare Capital)

Insurance

Sector

Vulnerabilities

Asset Quality EquityTotal Assets

Reinsurance

and Actuarial

Issues

Risk Retention Ratio (Net PremiumGross Premium)

Mathematical Reserves to Average of Net Premium

(ANP) received in last three years

Management

Soundness

Operating ExpensesGross Premium

Liquidity Liquid AssetsCurrent Liabilities

Solvency Net AssetsNet Premium Underwritten

78

After approaching towards the results of the above mentioned ratios rank to each

parameter is assigned on the basis of average ratio and at last the composite ranking of

CARAMEL framework is made in order to arrive at conclusions

Data Envelopment Analysis (DEA)

Data Envelopment Analysis (DEA) is a methodology based upon an interesting application

of linear programming It was originally developed for performance measurement It has

been successfully employed for assessing the relative performance of a set of firms that use a

variety of identical inputs to produce a variety of identical outputs It is a technique based on

linear programming It is used to measure the performance efficiency of organizational units

which are termed as (DMUs) This technique aims at measuring how efficiently a DMU uses

resources available to generate a set of outputs (Charnes et al1978) Decision Making Units

can include manufacturing units departments of big organizations such as universities

schools bank branches hospitals power plants police stations tax offices prisons defence

basis a set of firms or even practising individuals such as medical practitioners The

performance of DMUs is assessed in DEA using the concept of efficiency or productivity

which is the ratio of total outputs to total inputs The best performing Decision Making Unit

is assigned an efficiency score of unity The performances of other DMUs vary between zero

to one

Here in this study Efficiency is computed in terms of Revenue Cost and Profit using

DEA-Solver Pro 50 version of Data Envelopment Analysis and is presented in chapter

four The chapter is divided in to three sections ie Revenue efficiency Cost efficiency

and Profit efficiency of life insurance companies operating in India

Inputs and Outputs selected for the study Inputs and outputs selected for three different

types of efficiencies are as follows

1 For computing Revenue efficiency New-Revenue-V approach is used and

following data set for input output is used

Inputs (I)

Commission expenses

Operating expenses

79

Output (O)

Number of policies

Price (P)

Sum assured per policy

2 Cost efficiency is calculated using New-Cost-V approach of DEA The inputs and

output used to compute the cost efficiency score are as follows

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Sum assured per policy

3 New-Profit-V approach of DEA is applied in order to evaluate the Profit efficiency of

Indian life insurers and the following input output combination is used

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Number of policies

Price (P)

Sum assured per policy

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

75

To evaluate the Cost Efficiency of Indian life insurance industry

To compare the Profit Efficiency of Indian life insurance companies

To arrive at the logical conclusions and to provide constructive suggestions to

increase the efficiency of life insurance companies

Scope of the Study

The study period ranges for the years starting from 2000-01 to 2011-12 Further while

calculating efficiency scores from DEA data from 2005-06 onwards is considered because of

non availability of consistent data for comparison in years prior to this The Life Insurance

Corporation of India and some of the private sector life insurance companies (excluding

those which started their operations after 14th

May 2002) are selected for the study

Therefore the profile of private sector life insurance companies is selected for the study and

those which are considered outside the scope of study are given below

Profile of Indian Life Insurance Companies Selected for the Study

S

No

Regn

No

Date of

Regn Name of the Company Abbreviation used

1 101 23-10-2000 HDFC Standard Life Insurance Company Ltd HSLIC

2 104 15-11-2000 Max Life Insurance Co Ltd MAX LIFE

3 105 24-11-2000 ICICI Prudential Life Insurance Company Ltd IPLIC

4 107 10-01-2001 Kotak Mahindra Old Mutual Life Insurance Ltd KOTAK MAHINDRA

5 109 31-01-2001 Birla Sun Life Insurance Company Ltd BSLIC

6 110 12-02-2001 Tata AIA Life Insurance Co Ltd TATA-AIA

7 111 30-03-2001 SBI Life Insurance Co Ltd SBI-LIFE

8 114 02-08-2001 ING Vysya Life Insurance Company Pvt Ltd ING-VYSYA

9 116 03-08-2001 Bajaj Allianz Life Insurance Company Ltd BAJAJ-ALLIANZ

10 117 06-08-2001 Met Life India Insurance Company Ltd MET-LIFE

11 121 03-01-2002 Reliance Life Insurance Company Ltd RELIANCE

12 122 14-05-2002 Aviva Life Insurance Co India Pvt Ltd AVIVA

Source Compiled from the Annual Reports of IRDA

76

Profile of Companies which are outside the Purview of the Study

Sr No Regn No Date of Regn Name of the Company

1 127 06-02-2004 Sahara India Life Insurance Company Ltd

2 128 17-11-2005 Shriram Life Insurance Company Ltd

3 130 14-07-2006 Bharti AXA Life Insurance Company Ltd

4 133 04-09-2007 Future Generali India Life Insurance Co Ltd

5 135 19-12-2007 IDBI Federal Life Insurance Co Ltd

6 136 08-05-2008 Canara HSBC Oriental Bank of Commerce Life

Insurance Company Ltd

7 138 27-06-2008 Aegon Religare Life Insurance Company Ltd

8 140 27-06-2008 DLF Pramerica Life Insurance Company Ltd

9 142 26-12-2008 Star Union Dai-ichi Life Insurance Co Ltd

10 143 05-11-2009 India First Life Insurance Company Ltd

11 147 10-05-2011 Edelweiss Tokio Life Insurance Company Ltd

Source Compiled from the Annual Reports of IRDA

Although the above stated companies are considered outside the purview of study but still

the data for these companies are combined in tables of chapter III under heading ldquoOthersrdquo

This is done so as to know the accurate percentage share of selected companies to total share

of life insurance industry

Collection of the Data

The study is based on secondary data To make the study more analytical amp scientific and to

arrive at definite conclusions the secondary data is collected from the Annual Reports Fact

Books Manual of the insurance and Websites of IRDA Life Insurance Corporation of India

and private life insurance companies etc Experts in the field were also approached for the

purpose of discussion to understand the problem in right perspective The work of

academicians on this subject has also been consulted for the purpose of analysis The analysis

is descriptive in nature

Statistical Tools Applied

At the time of analyzing the data various statistical tools such as CARAMEL Model

Mean Coefficient of Variation Data Envelopment Analysis Frequency Distribution

Compound Annual Growth Rate and Percentages have been used in analyzing the

variables

77

CARAMEL Model The model is used to evaluate the operational efficiency of life

insurance companies in India The model makes use of ratio analysis Ratio analysis is an

analysis of financial statements which is done with the help of Ratios A Ratio expresses the

relationship that exists between two numbers taken from the financial statements Ratio

analysis is among the best tools available with the analyst to analyze the financial

performance of a company as it allows inter-company and intra company comparison It also

provides a birdrsquos eye view regarding the financial condition of the company An overview of

CARAMEL Indicators used in chapter three of the study is presented in the table given

below

Overview of CARAMEL Indicators Used for Measuring Operational Efficiency

Type of FSI Aspects of

Financial

System

Selected Indicators used to monitor different aspects

of financial system

Financial

Soundness

Capital

Adequacy

CapitalTotal Assets

CapitalMathematical Reserves

Earnings

Profitability

Operating ExpensesNet Premium Underwritten

CommissionNet Premium Underwritten

Other ExpensesNet Premium Underwritten

ExpensesNet Premium Underwritten

Shareholders Investment IncomeShareholder Investment

Policyholders Investment IncomePolicyholders

Investment

Investment IncomeInvestment Assets

Return on Equity

(Profit after interest tax and dividendShare Capital)

Insurance

Sector

Vulnerabilities

Asset Quality EquityTotal Assets

Reinsurance

and Actuarial

Issues

Risk Retention Ratio (Net PremiumGross Premium)

Mathematical Reserves to Average of Net Premium

(ANP) received in last three years

Management

Soundness

Operating ExpensesGross Premium

Liquidity Liquid AssetsCurrent Liabilities

Solvency Net AssetsNet Premium Underwritten

78

After approaching towards the results of the above mentioned ratios rank to each

parameter is assigned on the basis of average ratio and at last the composite ranking of

CARAMEL framework is made in order to arrive at conclusions

Data Envelopment Analysis (DEA)

Data Envelopment Analysis (DEA) is a methodology based upon an interesting application

of linear programming It was originally developed for performance measurement It has

been successfully employed for assessing the relative performance of a set of firms that use a

variety of identical inputs to produce a variety of identical outputs It is a technique based on

linear programming It is used to measure the performance efficiency of organizational units

which are termed as (DMUs) This technique aims at measuring how efficiently a DMU uses

resources available to generate a set of outputs (Charnes et al1978) Decision Making Units

can include manufacturing units departments of big organizations such as universities

schools bank branches hospitals power plants police stations tax offices prisons defence

basis a set of firms or even practising individuals such as medical practitioners The

performance of DMUs is assessed in DEA using the concept of efficiency or productivity

which is the ratio of total outputs to total inputs The best performing Decision Making Unit

is assigned an efficiency score of unity The performances of other DMUs vary between zero

to one

Here in this study Efficiency is computed in terms of Revenue Cost and Profit using

DEA-Solver Pro 50 version of Data Envelopment Analysis and is presented in chapter

four The chapter is divided in to three sections ie Revenue efficiency Cost efficiency

and Profit efficiency of life insurance companies operating in India

Inputs and Outputs selected for the study Inputs and outputs selected for three different

types of efficiencies are as follows

1 For computing Revenue efficiency New-Revenue-V approach is used and

following data set for input output is used

Inputs (I)

Commission expenses

Operating expenses

79

Output (O)

Number of policies

Price (P)

Sum assured per policy

2 Cost efficiency is calculated using New-Cost-V approach of DEA The inputs and

output used to compute the cost efficiency score are as follows

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Sum assured per policy

3 New-Profit-V approach of DEA is applied in order to evaluate the Profit efficiency of

Indian life insurers and the following input output combination is used

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Number of policies

Price (P)

Sum assured per policy

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

76

Profile of Companies which are outside the Purview of the Study

Sr No Regn No Date of Regn Name of the Company

1 127 06-02-2004 Sahara India Life Insurance Company Ltd

2 128 17-11-2005 Shriram Life Insurance Company Ltd

3 130 14-07-2006 Bharti AXA Life Insurance Company Ltd

4 133 04-09-2007 Future Generali India Life Insurance Co Ltd

5 135 19-12-2007 IDBI Federal Life Insurance Co Ltd

6 136 08-05-2008 Canara HSBC Oriental Bank of Commerce Life

Insurance Company Ltd

7 138 27-06-2008 Aegon Religare Life Insurance Company Ltd

8 140 27-06-2008 DLF Pramerica Life Insurance Company Ltd

9 142 26-12-2008 Star Union Dai-ichi Life Insurance Co Ltd

10 143 05-11-2009 India First Life Insurance Company Ltd

11 147 10-05-2011 Edelweiss Tokio Life Insurance Company Ltd

Source Compiled from the Annual Reports of IRDA

Although the above stated companies are considered outside the purview of study but still

the data for these companies are combined in tables of chapter III under heading ldquoOthersrdquo

This is done so as to know the accurate percentage share of selected companies to total share

of life insurance industry

Collection of the Data

The study is based on secondary data To make the study more analytical amp scientific and to

arrive at definite conclusions the secondary data is collected from the Annual Reports Fact

Books Manual of the insurance and Websites of IRDA Life Insurance Corporation of India

and private life insurance companies etc Experts in the field were also approached for the

purpose of discussion to understand the problem in right perspective The work of

academicians on this subject has also been consulted for the purpose of analysis The analysis

is descriptive in nature

Statistical Tools Applied

At the time of analyzing the data various statistical tools such as CARAMEL Model

Mean Coefficient of Variation Data Envelopment Analysis Frequency Distribution

Compound Annual Growth Rate and Percentages have been used in analyzing the

variables

77

CARAMEL Model The model is used to evaluate the operational efficiency of life

insurance companies in India The model makes use of ratio analysis Ratio analysis is an

analysis of financial statements which is done with the help of Ratios A Ratio expresses the

relationship that exists between two numbers taken from the financial statements Ratio

analysis is among the best tools available with the analyst to analyze the financial

performance of a company as it allows inter-company and intra company comparison It also

provides a birdrsquos eye view regarding the financial condition of the company An overview of

CARAMEL Indicators used in chapter three of the study is presented in the table given

below

Overview of CARAMEL Indicators Used for Measuring Operational Efficiency

Type of FSI Aspects of

Financial

System

Selected Indicators used to monitor different aspects

of financial system

Financial

Soundness

Capital

Adequacy

CapitalTotal Assets

CapitalMathematical Reserves

Earnings

Profitability

Operating ExpensesNet Premium Underwritten

CommissionNet Premium Underwritten

Other ExpensesNet Premium Underwritten

ExpensesNet Premium Underwritten

Shareholders Investment IncomeShareholder Investment

Policyholders Investment IncomePolicyholders

Investment

Investment IncomeInvestment Assets

Return on Equity

(Profit after interest tax and dividendShare Capital)

Insurance

Sector

Vulnerabilities

Asset Quality EquityTotal Assets

Reinsurance

and Actuarial

Issues

Risk Retention Ratio (Net PremiumGross Premium)

Mathematical Reserves to Average of Net Premium

(ANP) received in last three years

Management

Soundness

Operating ExpensesGross Premium

Liquidity Liquid AssetsCurrent Liabilities

Solvency Net AssetsNet Premium Underwritten

78

After approaching towards the results of the above mentioned ratios rank to each

parameter is assigned on the basis of average ratio and at last the composite ranking of

CARAMEL framework is made in order to arrive at conclusions

Data Envelopment Analysis (DEA)

Data Envelopment Analysis (DEA) is a methodology based upon an interesting application

of linear programming It was originally developed for performance measurement It has

been successfully employed for assessing the relative performance of a set of firms that use a

variety of identical inputs to produce a variety of identical outputs It is a technique based on

linear programming It is used to measure the performance efficiency of organizational units

which are termed as (DMUs) This technique aims at measuring how efficiently a DMU uses

resources available to generate a set of outputs (Charnes et al1978) Decision Making Units

can include manufacturing units departments of big organizations such as universities

schools bank branches hospitals power plants police stations tax offices prisons defence

basis a set of firms or even practising individuals such as medical practitioners The

performance of DMUs is assessed in DEA using the concept of efficiency or productivity

which is the ratio of total outputs to total inputs The best performing Decision Making Unit

is assigned an efficiency score of unity The performances of other DMUs vary between zero

to one

Here in this study Efficiency is computed in terms of Revenue Cost and Profit using

DEA-Solver Pro 50 version of Data Envelopment Analysis and is presented in chapter

four The chapter is divided in to three sections ie Revenue efficiency Cost efficiency

and Profit efficiency of life insurance companies operating in India

Inputs and Outputs selected for the study Inputs and outputs selected for three different

types of efficiencies are as follows

1 For computing Revenue efficiency New-Revenue-V approach is used and

following data set for input output is used

Inputs (I)

Commission expenses

Operating expenses

79

Output (O)

Number of policies

Price (P)

Sum assured per policy

2 Cost efficiency is calculated using New-Cost-V approach of DEA The inputs and

output used to compute the cost efficiency score are as follows

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Sum assured per policy

3 New-Profit-V approach of DEA is applied in order to evaluate the Profit efficiency of

Indian life insurers and the following input output combination is used

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Number of policies

Price (P)

Sum assured per policy

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

77

CARAMEL Model The model is used to evaluate the operational efficiency of life

insurance companies in India The model makes use of ratio analysis Ratio analysis is an

analysis of financial statements which is done with the help of Ratios A Ratio expresses the

relationship that exists between two numbers taken from the financial statements Ratio

analysis is among the best tools available with the analyst to analyze the financial

performance of a company as it allows inter-company and intra company comparison It also

provides a birdrsquos eye view regarding the financial condition of the company An overview of

CARAMEL Indicators used in chapter three of the study is presented in the table given

below

Overview of CARAMEL Indicators Used for Measuring Operational Efficiency

Type of FSI Aspects of

Financial

System

Selected Indicators used to monitor different aspects

of financial system

Financial

Soundness

Capital

Adequacy

CapitalTotal Assets

CapitalMathematical Reserves

Earnings

Profitability

Operating ExpensesNet Premium Underwritten

CommissionNet Premium Underwritten

Other ExpensesNet Premium Underwritten

ExpensesNet Premium Underwritten

Shareholders Investment IncomeShareholder Investment

Policyholders Investment IncomePolicyholders

Investment

Investment IncomeInvestment Assets

Return on Equity

(Profit after interest tax and dividendShare Capital)

Insurance

Sector

Vulnerabilities

Asset Quality EquityTotal Assets

Reinsurance

and Actuarial

Issues

Risk Retention Ratio (Net PremiumGross Premium)

Mathematical Reserves to Average of Net Premium

(ANP) received in last three years

Management

Soundness

Operating ExpensesGross Premium

Liquidity Liquid AssetsCurrent Liabilities

Solvency Net AssetsNet Premium Underwritten

78

After approaching towards the results of the above mentioned ratios rank to each

parameter is assigned on the basis of average ratio and at last the composite ranking of

CARAMEL framework is made in order to arrive at conclusions

Data Envelopment Analysis (DEA)

Data Envelopment Analysis (DEA) is a methodology based upon an interesting application

of linear programming It was originally developed for performance measurement It has

been successfully employed for assessing the relative performance of a set of firms that use a

variety of identical inputs to produce a variety of identical outputs It is a technique based on

linear programming It is used to measure the performance efficiency of organizational units

which are termed as (DMUs) This technique aims at measuring how efficiently a DMU uses

resources available to generate a set of outputs (Charnes et al1978) Decision Making Units

can include manufacturing units departments of big organizations such as universities

schools bank branches hospitals power plants police stations tax offices prisons defence

basis a set of firms or even practising individuals such as medical practitioners The

performance of DMUs is assessed in DEA using the concept of efficiency or productivity

which is the ratio of total outputs to total inputs The best performing Decision Making Unit

is assigned an efficiency score of unity The performances of other DMUs vary between zero

to one

Here in this study Efficiency is computed in terms of Revenue Cost and Profit using

DEA-Solver Pro 50 version of Data Envelopment Analysis and is presented in chapter

four The chapter is divided in to three sections ie Revenue efficiency Cost efficiency

and Profit efficiency of life insurance companies operating in India

Inputs and Outputs selected for the study Inputs and outputs selected for three different

types of efficiencies are as follows

1 For computing Revenue efficiency New-Revenue-V approach is used and

following data set for input output is used

Inputs (I)

Commission expenses

Operating expenses

79

Output (O)

Number of policies

Price (P)

Sum assured per policy

2 Cost efficiency is calculated using New-Cost-V approach of DEA The inputs and

output used to compute the cost efficiency score are as follows

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Sum assured per policy

3 New-Profit-V approach of DEA is applied in order to evaluate the Profit efficiency of

Indian life insurers and the following input output combination is used

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Number of policies

Price (P)

Sum assured per policy

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

78

After approaching towards the results of the above mentioned ratios rank to each

parameter is assigned on the basis of average ratio and at last the composite ranking of

CARAMEL framework is made in order to arrive at conclusions

Data Envelopment Analysis (DEA)

Data Envelopment Analysis (DEA) is a methodology based upon an interesting application

of linear programming It was originally developed for performance measurement It has

been successfully employed for assessing the relative performance of a set of firms that use a

variety of identical inputs to produce a variety of identical outputs It is a technique based on

linear programming It is used to measure the performance efficiency of organizational units

which are termed as (DMUs) This technique aims at measuring how efficiently a DMU uses

resources available to generate a set of outputs (Charnes et al1978) Decision Making Units

can include manufacturing units departments of big organizations such as universities

schools bank branches hospitals power plants police stations tax offices prisons defence

basis a set of firms or even practising individuals such as medical practitioners The

performance of DMUs is assessed in DEA using the concept of efficiency or productivity

which is the ratio of total outputs to total inputs The best performing Decision Making Unit

is assigned an efficiency score of unity The performances of other DMUs vary between zero

to one

Here in this study Efficiency is computed in terms of Revenue Cost and Profit using

DEA-Solver Pro 50 version of Data Envelopment Analysis and is presented in chapter

four The chapter is divided in to three sections ie Revenue efficiency Cost efficiency

and Profit efficiency of life insurance companies operating in India

Inputs and Outputs selected for the study Inputs and outputs selected for three different

types of efficiencies are as follows

1 For computing Revenue efficiency New-Revenue-V approach is used and

following data set for input output is used

Inputs (I)

Commission expenses

Operating expenses

79

Output (O)

Number of policies

Price (P)

Sum assured per policy

2 Cost efficiency is calculated using New-Cost-V approach of DEA The inputs and

output used to compute the cost efficiency score are as follows

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Sum assured per policy

3 New-Profit-V approach of DEA is applied in order to evaluate the Profit efficiency of

Indian life insurers and the following input output combination is used

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Number of policies

Price (P)

Sum assured per policy

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

79

Output (O)

Number of policies

Price (P)

Sum assured per policy

2 Cost efficiency is calculated using New-Cost-V approach of DEA The inputs and

output used to compute the cost efficiency score are as follows

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Sum assured per policy

3 New-Profit-V approach of DEA is applied in order to evaluate the Profit efficiency of

Indian life insurers and the following input output combination is used

Inputs (I)

Number of agents

Number of offices

Cost (C)

Commission expenses

Operating expenses

Output (O)

Number of policies

Price (P)

Sum assured per policy

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

80

After arriving at the efficiency scores these scores have been distributed in four different

ranges so as to know the efficiency level of various life insurers These ranges are up to 025

025 to 050 050 to 075 and above 075 and their corresponding efficiency levels Least

efficient Low efficient Efficient and Highly efficient Thereafter graph for each year is also

prepared in order to rank the insurers on the basis of their efficiency scores After presenting

the score on yearly basis it is compiled in a single table which consists of the score for each

year (ie from 2005-06 to 2011-12) Increase decrease or no change in score in the next year

is represented by symbols such as + - or NC in the next step The company having three or

more + symbols are termed as Improved performer and with - symbols as Deteriorate

performer The company having two + two ndash amp two NC signs and with three - amp three +

signs is considered to be the Consistent performer Therefore at last table indicating

performance of life insurers is prepared at the end of each section

Usefulness of the Study

Keeping in view the various issues analyzed in the study it can be concluded that the study

provides a meaningful contribution in todayrsquos era The findings of the study would be

beneficial to the multiple groups of people Firstly the study will be helpful to the Indian life

insurance companies With the help of the study the companies will be able to know their

ranking in the market and the ways to improve it Secondly it will be of immense help to the

individuals interested in investing money in these companies Last but not the least the

study will prove very beneficial for the students and researchers in the area of Finance

Banking and Insurance

Organization of the Study

The study is organized in five chapters as follows

Chapter I describes the profile as well as growth of Indian life insurance industry during

different phases of time

Chapter II deals with review of earlier studies regarding efficiency of life insurers and

describes the research methodology and organization of the study

Chapter III explains the analysis of operational efficiency of life insurance companies using

CARAMEL model

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies

81

Chapter IV presents the revenue cost and profit efficiency of life insurers in India

Chapter V provides the summary of the findings suggestions and recommendations of the

study

Limitations of the study

The research work is undertaken so as to maximize objectivity and minimize the errors

However there are certain limitations of the study which are as follows

The study completely depends on the data which collected from the Annual Reports

of IRDA Therefore study incorporates all the limitations that are inherent in the

published data

The data for analysis is purely derived from annual reports They are not adjusted for

inflation

Since DEA is an extreme point technique errors in measurement can cause

significant problems DEA efficiencies are very sensitive to even small errors

making sensitivity analysis is an important component of post DEA procedure and

this aspect has not been carried out in this study

Study period is confined to financial year 2000-01 to 2011-12 only This is due to

existence of private sector life insurance companies from 2000-01 onwards only and

data for the year 2012-13 was not available till the completion of study Since it is an

introduction phase of private sector life insurance companies the results might be

affected and may not be similar in the long run

Further Scope of the Study

While calculating cost efficiency in the study actual observed cost can be decomposed in to

minimum cost and loss due to input efficiency Moreover loss due to input efficiency can

also be expressed as input technical price and allocative inefficiencies Secondly post DEA

procedure which includes sensitivity analysis can be carried out in the study Thirdly the

study emphasizes on efficiency of Indian life insurance companies only Therefore the

performance of the companies which are operating outside India can also be compared with

Indian companies