Financial Stability Review (FSR) - bi.go.id · 1.17.2 DER and TL/TA of Non-Financial Public Listed Companies 14 ... 2.48 Volatility of several Asian Bourse Indices 43 2.49 Bank Share

The preparation of the Financial Stability Review (FSR) is one of the avenues

through which Bank Indonesia achieves its mission ≈to safeguard the stability of the Indonesian

Rupiah by maintaining monetary and financial system stability for sustainable national

economic development∆.

Publisher :

Bank Indonesia

Jl. MH Thamrin No.2, Jakarta

Indonesia

Information and Orders:

This edition is published in September 2010 and is based on data and information available as of June 2010, unless stated

otherwise.

The PDF format is downloadable from: http://www.bi.go.id

For inquiries, comments and feedback please contact:

Bank Indonesia

Directorate of Banking Research and Regulation

Financial System Stability Bureau

Jl.MH Thamrin No.2, Jakarta, Indonesia

Phone : (+62-21) 381 8902, 381 8075

Fax : (+62-21) 351 8629

Email : [email protected]

FSR is published biannually with the objectives:

To improve public insight in terms of understanding financial system stability.

To evaluate potential risks to financial system stability.

To analyze the developments of and issues within the financial system.

To offer policy recommendations to promote and maintain financial system stability.

Financial Stability Review( No. 15, September 2010 )

ii

iii

Foreword vi

Overview 3

Chapter 1 Macroeconomic Conditions and

the Real Sector 9

Macroeconomic Conditions 9

Real Sector Conditions 14

Box 1.1. Mortality Rate & Contingent Claim Analysis

Approach: Potential Corporate Credit Risk

in the Manufacturing Industry 17

Box 1.2. Household Debt Service Ratio (DSR) in

Indonesia 20

Box 1.3. Capital Flows and Financial System Stability

in Indonesia 21

Chapter 2 The Financial Sector 27

Indonesian Financial System Structure 27

Financial Sector Resilience 27

Banks 28

Funding and Liquidity Risk 28

Credit Growth and Risk 30

Profitability and Capital 36

Non-Bank Financial Institutions and the Capital

Market 38

Finance Companies 38

Capital Market 41

Box 2.1. Statutory Reserve Requirement (SSR) √ Loan

to Deposit Ratio (LDR) 47

Box 2.2. Indicators of Bank Liquidity Resilience 49

Box 2.3. Implementation of Operational Risk Capital

Charge 51

Box 2.4. Financial System Reform to Enhance

Financial Sector Resilience 52

Box 2.5. Impact of PSAK 55 (2006 revision)

Implementation on Banking in Indonesia 56

Table of Contents

Chapter 3 Financial Infrastructure and Risk

Mitigation 61

Payment System Performance 61

Bank Indonesia Real-Time Gross Settlement

System 62

Operational Activity and Liquidity Management 62

Bank Indonesia Scripless Securities Settlement

System (BI-SSSS) 62

Bank Indonesia National Clearing System (BI-NCS) 63

ATM and ATM/Debit Cards 63

The Credit Card Industry 63

Electronic Money 64

Payment System Development and Risk

Mitigation 64

Business Continuity Plan 64

Credit Bureau 65

Role and Development of Credit Information

Bureau 66

Development Stages 67

Public»s Role in the Credit System 67

Box 3.1. Overview of Liberalisation Forums

Participated by Indonesia 68

Box 3.2. Overview of ASEAN Economic Community

(AEC) 70

Chapter 4 Indonesian Financial System

Outlook 75

Economic Prospects and Risk Perception 75

Bank Risk Profile: Level and Direction 77

Potential Vulnerabilities 77

Articles

Article 1 Determinants of Capital Reserves at

Indonesia»s Banks 81

Article 2 Procyclicality of Loan Loss Provisioning in

Indonesia 93

iv

1.1 World Economic Indicators 9

1.2 Affect of Rupiah Depreciation on Conglomerate

Equity 15

2.1 Components of Liquid Assets 29

2.2 Bank Profit/Loss 36

2.3 Finance Ratios of Finance Companies 39

2.4 NPL of Finance Companies 40

2.5 NPL of Finance Companies 40

2.6 Indices of Regional Markets 42

2.7 Sectoral Indices 42

2.8 VaR by SUN Tenure 44

2.9 SUN Ownership 44

2.10 Issuances of Corporate Bonds and Value of

Mature Corporate Bonds 45

3.1 Demand for Historical IDI 65

3.2 Profile of DIS Members 65

4.1 Economic Indicator Projections 75

4.2 Domestic Economic Growth according to

Demand 76

4.3 Indonesian Risk Perception 76

Box Tables :

1.1.1 Average Probability of Default of three Industrial

Sectors 17

1.2.1 DSR by Province 20

1.2.2 Indebted Respondents by Province 20

2.3.1 Operational Risk Simulation 51

1.1 Global Economic Growth 10

1.2 Global Stock Price Index 10

1.3 GDP Growth in several Emerging Market

Countries 10

1.4 GDP Growth in Developed Countries 10

1.5 Value of Non-Oil/Gas Exports from Indonesia 11

1.6 Non-Oil/Gas Export/Import Growth 11

1.7 Price Indices of several Commodities 11

1.8 Rupiah Exchange Rate 11

1.9 Exchange Rate Volatility 12

1.10 Performance of Selected Global Currencies 12

1.11 Sectoral Stock Price Index 12

1.12 Inflation Rates in ASEAN-5 13

1.13 Real Interest Rates 13

1.14 FDI to Indonesia 13

1.15 Total Non-Agricultural Sector Employment 13

1.16 Consumer Confidence Index 14

1.17.1 ROA and ROE of Non-Financial Public Listed

Companies 14

1.17.2 DER and TL/TA of Non-Financial Public Listed

Companies 14

1.18 Key Corporate Financial Indicators 15

1.19 Ratio of Net Foreign Liabilities to Equity 16

2.1 Asset Composition of Financial Institutions 27

2.2 Financial Stability Index 28

2.3 Deposits by Component 28

2.4 Deposits by Bank Group 28

2.5 State Budget Surplus/Deficit January to July 29

2.6 Foreign Exchange Deposits √ IDR/USD

Exchange Rate 29

2.7 Bank Liquid Assets by Component 29

2.8 Liquid Assets by Bank Group 30

2.9 Credit Growth by Type (yoy) 31

2.10 Increase in Credit by Type - Semester I-2010

(ytd) 31

List of Tables and Figures

Tables Figures

v

2.11 Credit Growth by Economic Sector √ Semester

I-2010 (ytd) 31

2.12 Share of Credit by Economic Sector 31

2.13 Increase in Property Credit 32

2.14 Property Credit Growth (yoy) 32

2.15 Gross NPL 32

2.16 Credit Share by Collectability 33

2.17 Increase in Nominal NPL by Credit Type 33

2.18 Gross NPL Ratio by Credit Type 33

2.19 Increase in Nominal NPL by Economic Sector 33

2.20 NPL Ratio by Sector 34

2.21 Increase in Nominal NPL by Currency 34

2.22 Gross NPL ratio by Currency 34

2.23 Increase in Total Nominal NPL of Property Credit 34

2.24 Gross NPL Ratio of Property Credit 34

2.25 Credit Risk Stress Test 35

2.26 Rupiah Maturity Profile 35

2.27 Foreign Exchange Maturity Profile 35

2.28 Interest Rate Risk Stress Test 35

2.29 Net Open Position 36

2.30 SUN Share 36

2.31 Stress Test - SUN Price Decline (AFS + Trading) 36

2.32 ROA and Efficiency Ratio 37

2.33 Credit interest rate and BI Rate 37

2.34 Interest Rate Spread 37

2.35 Banking Profit/Loss Composition 37

2.36 Composition of Operational Profit 37

2.37 Share of Interest Income 38

2.38 Capital, Risk-Weighted Assets and CAR 38

2.39 CAR by Bank Group 38

2.40 Business Activity of Finance Companies 39

2.41 Composition of Finance for Finance Companies 39

2.42 Finance Companies» Source of Funds 39

2.43 Composition of Nominal Finance by Finance

Companies 41

2.44 Foreign Investment in SBI, SUN and Stock 41

2.45 Foreign Portfolio in Rupiah Financial Assets

(SBI, SUN, Stock) 41

2.46 Stock Market 41

2.47 JCI as well as Global and Regional Indices 42

2.48 Volatility of several Asian Bourse Indices 43

2.49 Bank Share Prices 43

2.50 Percentage Change in Bank Share Prices 43

2.51 Average Monthly SUN Price 43

2.52 SUN VaR 44

2.53 SUN Maturity Profile (June 2010) 44

2.54 Performance of Mutual Funds 45

2.55 Net Asset Value by type of Mutual Fund 45

2.56 Capitalisation and Stock Issuances 46

2.57 Issuances of Corporate Bonds 46

3.1 Nominal Transaction Value (in billions of rupiah) 61

3.2 Transaction Volume (in thousands of rupiah) 61

3.3 BI-RTGS System Transactions 62

3.4 BI-SSSS Transactions 62

3.5 BI-NCS Transactions 63

3.6 ATM/Debit Card Transactions 63

3.7 Credit Card Transactions 63

3.8 E-Money Transactions 63

3.9 The Role of CIB 66

4.1 Comparison of Economic Growth Projections

for several Country Groups 75

4.2 Credit Default Swap and Bond Yield Spread 76

4.3 Bank Risk Profile and Future Direction 78

Figures included in Boxes :

1.1.1 Mortality Rate of Industrial Sub-sectors based on

Outstanding Debits 18

1.1.2 Mortality Rate of Industrial Sub-sectors based on

Number of Debtors 18

1.3.1 Framework: Mechanism (excessive) Capital

Inflows leading to Financial and Economic Crisis 21

1.3.2 Ratio of Credit to GDP and Capital Flows to

GDP 22

1.3.3 Short-term Capital Flows (portfolio) versus

Long-term (FDI) 22

1.3.4 JSX Composite vs. Trend 22

2.2.1 Liquidity Coverage Ratio of Large Banks

2008 √ June 2010 49

2.2.2 Liquidity Coverage Ratio of Large Banks

2008 √ June 2010 50

2.2.3 NSFR of Large Banks 2008 √ June 2010 50

2.2.4 NSFR of Large Banks 2008 √ June 2010 50

2.3.1 Comparison of Bank RWA 51

2.4.1 Microprudential Supervision, Monetary Stability

and Financial System Stability 52

vi

We express sincere gratitude to God Almighty for His mercy and grace in the publication of this edition of the

Financial Stability Review (FSR) No. 15 September 2010 as planned. The publication of this FSR is expected to provide

information to the general public regarding the current performance and future prospects of financial system stability in

Indonesia amid persistent widespread uncertainty in the global financial system as well as a deluge of short-term capital

inflows.

Domestically, conditions in the economy and financial sector are better than global conditions. Review results indicate

that financial sector resilience during Semester I-2010 was well maintained. This was principally attributable to conducive

macroeconomic conditions, among others, reflected by relatively stable public purchasing power, robust domestic demand

as well as rupiah exchange rate stability. Compared to the previous semester, instability pressures eased slightly as evidenced

by a decline in the Financial Stability Index (FSI) from 1.91 (December 2009) to 1.87 (June 2010).

Such favourable economic conditions empowered banks to improve their performance. The Capital Adequacy Ratio

(CAR) reached 17.4% (June 2010) on the back of good credit quality, which was indicated by gross non-performing loans

of just 3.3%. In addition, credit growth in Semester I-2010 reached 18.8% (yoy), which surpassed total growth in 2009

(10.0%). Controlled credit quality and greater credit distribution increased bank profitability with ROA equal to 2.9%.

Accordingly, bank liquidity, in general, was well preserved. Nonetheless, growth in deposits slowed during Semester

I-2010, which subsequently necessitates additional attention considering that deposits represent the largest source of

funds for banks.

The prospect of stable domestic interest rates strengthened the financial market and attracted foreign investor

interest in rupiah financial assets. This condition sustained the torrent of short-term capital inflows, which consequently

aid to the strengthening of the Rp/USD exchange rate and foreign exchange reserves. On the other hand, financial

industry performance (including the banks) was expected to improve.

However, alertness and prudence must be further enhanced in terms of addressing financial sector performance.

This is primarily due to the persistence of risk factors, among others, stemming from uncertainty regarding the pace

and strength of the global economic recovery process as well as the prevalence of short-term capital inflows to the

financial market that are a potential source of financial system instability, in particular if accompanied by a concomitant

large-scale capital reversal. In anticipation of a potential capital reversal a minimum holding period of one month was

imposed on Bank Indonesia Certificates. Concerning the banks, a number of measures have and will continue to be

implemented, including reinforcing bank capital and liquidity, enhancing risk management and good governance in

Foreword

vii

the financial sector, as well as strengthening macro and micro-prudential surveillance in order to discover potential

sources of instability earlier, thus affording additional time to implement risk mitigation measures more expeditiously

and accurately.

In closing, we hope that this edition of the Financial Stability Review can function as a medium to communicate to

our stakeholders the results of surveillance as well as reviews that have been conducted by Bank Indonesia concerning

financial system stability and future prospects. Please do not hesitate to submit and discuss with us any suggestions and

constructive criticism in order to further develop and refine the Financial Stability Review, thus ensuring that the FSR can

become even more beneficial to us all.

Jakarta, 30 September 2010

DEPUTY GOVERNOR OF BANK INDONESIA

MULIAMAN D. HADAD

viii

1

Overview

Overview

2

Overview

This page is intentionally blank

3

Overview

Financial sector resilience during Semester I-2010 was sufficiently well

maintained on the strength of conducive macroeconomic conditions, among

others, marked by relatively stable public purchasing power, strong domestic

demand and a steady rupiah exchange rate. Meanwhile, banks, as the

dominant force in the financial industry, continued to perform positively as

reflected by a high capital adequacy ratio and profitability, high quality earning

assets, and relatively controlled liquidity conditions. The performance of the

stock market and bond market improved compared to the previous semester.

However, several sources of instability remained, including a lacklustre global

economic recovery, high inflation expectations, slow growth of deposits and

a surge in short-term capital inflows. Looking ahead, risk mitigation measures

need to be redoubled in order to maintain financial system stability and ensure

a positive outlook.

1. SOURCES OF INSTABILITY

1.1. Global Economic Recovery

Externally, Indonesia»s economy continued to

confront risk factors stemming from uncertainty

surrounding the pace and strength of the global economic

recovery process. There were fears that the global economic

recovery is being undermined by the slow recovery of

economic activity in the United States and Japan as well

as a slowdown in China»s economic expansion. This

situation requires careful monitoring considering that

uncertainty regarding the pace of the economic recovery

has the potential to affect liquidity in the financial system,

in particular concerning the volatility of foreign capital

inflows.

1.2. Growth of Deposits

Semester I-2010 was marked by a slowdown in the

growth of deposits (14.9% yoy) to a level slightly below

the average for the past five years. Conversely, bank credit

during the same period grew by 18.8% yoy, which

represents an increase over the previous period. Despite

sufficient bank liquidity, the share of deposits as a source

of bank funds reached 91.8% of total bank funds; therefore,

the slowdown in deposits requires close monitoring.

1.3. Pressures on Headline Inflation

Headline inflation, as measured by the Consumer

Price Index, reached 5.05% (yoy) in Semester I-2010. This

indicates a rise in inflationary pressures triggered primarily

Overview

4

Overview

by volatile foods as a result of the limited supply of several

basic staples, as well as various constraints in the

distribution network. Consequently, inflation in 2010 will

be maintained within its target corridor of 5%±1% despite

intense inflationary pressures on volatile food prices and

administered prices.

1.4. Short-Term Capital Inflows

There is currently a deluge of short-term capital

inflows to Indonesia, not only because the yields offered

on financial instruments in Indonesia are attractive but also

due to the upgraded sovereign rating as a result of

impressive economic performance in Indonesia. On the

other hand, the rise in short-term capital inflows requires

monitoring because of its extreme vulnerability to a sudden

reversal, which could undermine financial stability.

1.5. Consumption Credit Risk Pressures

The global economic crisis compromised business

activity. Credit allocation to productive sectors declined

due to weaker demand, whilst banks also stopped lending

and became risk averse in line with the increase in potential

business default. Consequently, credit growth centred

more on consumption credit. The gross NPL ratio of

consumption credit was lower than any other type of credit,

however, risk pressures intensified. In the previous three

years (since 2008) total nominal NPL of consumption credit

has continued to increase, which indicates a potential rise

in credit risk in the future.

1.6. Problems in the Real Sector and with

Infrastructure

Economic performance in Indonesia during Semester

I-2010 demonstrated strong resilience; even following an

upward trend. The improvement in domestic economic

performance was influenced by global economic

conditions, relatively stable public purchasing power that

drove domestic demand, as well as a stable rupiah

exchange rate. However, the domestic economy was also

beset with a number of arduous challenges, primarily

stemming from persistent microstructural problems in the

real sector, including weak industrial sector competitiveness

and stagnant infrastructure development. If the problems

faced by the real sector continue with no solution

forthcoming, in the long-run, they have the potential to

trigger instability in the financial sector.

2. RISK MITIGATION

2.1. Capital and Liquidity

Strong capital and adequate liquidity represent two

areas of concern for the relevant authorities, in particular

after the experience of the recent global financial crisis.

At the meeting on 12th September 2010, the Group of

Governors and Heads of Supervision from the Basel

Committee on Banking Supervision announced new capital

regulations pursuant to those previously agreed on 26th

July 2010. Regulatory reform coupled with the application

of global liquidity standards represents the core agenda

of global financial reforms, which will be presented at the

G20 Leaders Summit in November 2000 in Seoul. This

initiative is particularly relevant to Indonesia»s banking

system considering the future challenges faced. However,

banks are a primary sector that support economic growth,

hence, the impact of these policies on the lending ability

of banks must be taken into consideration.

2.2. Risk Management and Good Governance

Strengthening risk management and good

governance in the financial sector is one method to mitigate

risk. Banks are perpetually encouraged to enhance the

quality of their risk management and governance, not only

to meet Bank Indonesia»s regulations but also to nurture

5

Overview

market discipline. Comprehensive risk management

corresponding to expectations of inflationary pressures and

the impact on interest rates is important due to its overall

impact on credit, market risk and bank liquidity.

2.3. Surveillance

The relevant authorities implement risk mitigation

by strengthening micro and macro-prudential surveillance.

Micro-prudential surveillance is performed on an individual

bank or financial institution in order to ensure the fulfilment

of prudential regulations through on-site and off-site

supervision. Additionally, macro-prudential surveillance also

aims to ensure that prudential regulations are adhered to,

however, at the industry level as an aggregate.

Under a framework of strengthening micro-

prudential surveillance, a number of measures have been

introduced by Bank Indonesia to bolster and improve

surveillance in order to better anticipate the symptoms of

troubled banks on a risk basis, as well as enhancing the

competence of human resources through training,

attachments and certification programs. In addition,

improvements to the tools and methodologies used in

surveillance are ongoing in order to reinforce macro-

prudential aspects, among others, stress testing, probability

of default analysis, transition matrices and other early

warning mechanisms.

3. FINANCIAL SYSTEM OUTLOOK

The improvement in macro conditions, as indicated

by stronger economic growth and greater foreign investor

confidence that is the result of a stable exchange rate and

the upgraded debt rating of Indonesia, has strengthened

financial system stability. Exchange rate volatility remained

under control amid a return to bullish conditions on the

stock and bond markets after a significant freefall in

February 2010. Domestic financial sector stability and

economic recovery were sufficient to stave off a sudden

reversal in short-term capital flows that peaked in May

2000. Accordingly, the prospects of Indonesia»s financial

sector up to yearend 2010 are expected to remain stable

despite a slight intensification of inflationary pressures.

For the actual realisation of such positive financial

system stability prospects in the future, cooperation and

support from all stakeholders is imperative, including the

creation of conducive conditions from a legal, political and

security standpoint.

6

Overview


7

Chapter 1 Macroeconomic Conditions and the Real Sector

Chapter 1Macroeconomic Conditionsand the Real Sector

8



9


1.1. MACROECONOMIC CONDITIONS

Global economic performance improved duringGlobal economic performance improved duringGlobal economic performance improved duringGlobal economic performance improved duringGlobal economic performance improved during

semester I-2010. semester I-2010. semester I-2010. semester I-2010. semester I-2010. Global economic growth at the end of

quarter II-2010 reached 4.9%. Such conditions are

congruent to the increase in projected global economic

growth for 2010 by the IMF from 4.2% in April 2010 to

4.6% in July 2010, despite growth in 2011 projected at a

level of 4.3%. This increase in global economic expansion

is supported by an economic recovery in Europe and robust

economic growth in emerging market countries.

Table 1.1World Economic Indicators

World Output: 3.0 (0.6) 4.6 4.3Advanced Economies 0.5 (3.2) 2.6 2.4

United States 0.4 (2.4) 3.3 2.9Emerging & Developing Countries 6.1 2.5 6.8 6.4

Consumer Price:Advanced Economies 3.4 0.1 1.4 1.3Emerging & Developing Countries1) 9.3 5.2 6.3 5.0

LIBOR2)

US Dollar Deposit 3.0 1.1 0.6 0.9Euro Deposit 4.6 1.2 0.8 1.2Yen Deposit 1.0 0.5 0.5 0.6

Oil Price (USD) - average3) 36.4 (36.3) 21.8 3.0

Category 2008 2009

(percent)(percent)(percent)(percent)(percent)Projection

2010 2011

Source: World Economic Outlook - IMF July 2010

Macroeconomic Conditions andthe Real Sector

Chapter 1

Macroeconomic stability improved in Indonesia during semester I-2010.

Furthermore, economic performance showed indications of improvement in

line with positive developments in the global economy. A sound and stable

banking sector coupled with growth in exports and strong domestic demand

contributed to the strengthening of Indonesia»s economic performance.

Looking ahead, the economy of Indonesia has the potential to strengthen

further, however, several internal and external risk factors remain that require

attention. From a global perspective, one of the challenges faced stems

from uncertainty regarding economic performance in the US and a slowdown

in China»s economic expansion. Domestically, however, in line with the deluge

of foreign capital inflows into the country, a number of micro-structural

challenges have emerged, including weak industrial sector competitiveness.

This requires immediate resolution in order to further stimulate investment

and domestic consumption.

10


The economic recovery in Europe is primarily

attributable to industrial sector performance and the results

of stress tests on banks in Europe that exceeded initial

estimates, thus alleviating pressures on global financial

markets. The global economic recovery, among others, was

reflected by enhanced global stock market performance

as well as improved risk perception. Compared to the same

period of the previous year, in June 2010 the stock price

index in several countries, in general, experienced a gain.

The most significant hike was recorded on the Hong Kong

stock exchange. In June 2010, the Hang Seng Index

reached a level of 20,536.5; equivalent to a 1715.3-point

increase over June 2009.

Figure 1.2Global Stock Price Index

resurgence, which underpinned global economic growth

amid languid economic expansion in advanced countries.

On average, economic growth in emerging market

countries was in the range of 8.3% during semester I-

2010, representing an increase of 9.3% compared to

semester II-2009. Meanwhile, economic expansion in

developed countries was a mere 5.0% on average in

semester I-2010, which is an increase of just 7.4% over

the previous semester.

Figure 1.1Global Economic Growth

Figure 1.3GDP Growth in several Emerging Market Countries

-15

-10

-5

0

5

10

15

I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV2006 2007 2008 2009 2010 2011

World GDPGDP of Developed CountriesGDP of Developing Countries

0

5,000

10,000

15,000

20,000

25,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun2009 2010

JCI Index STI Index KLCI IndexPCOMP Index NKY Index HSI IndexNYA index UKX Index INDU Index

Figure 1.4GDP Growth in Developed Countries

IndonesiaIndiaMexico

ThailandBrazilPhilippines

(11.00)

(8.00)

(5.00)

(2.00)

1.00

4.00

7.00

10.00

13.00

2006 2007 2008 2009 2010

%

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

2006 2007 2008 2009 2010

%

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4-10.00

-5.00

0.00

5.00

10.00

USGermanyChinaSouth Korea

JapanUKHongkong

Concomitant to alleviating of of pressures in the

global financial market, economic performance in

emerging market countries experienced a significant

Similar to other emerging market countries,

economic performance in Indonesia during semester I-

2010 demonstrated strong and improved resilience. Since

the crisis in 2009 up to June 2010 economic growth in

Indonesia has been maintained at a positive level. During

the second quarter of 2010, economic growth in Indonesia

achieved the relatively high level of 6.17% (yoy), which

11


Indonesia»s balance of payments remained positive

due to strong exports. In June 2010 the balance of

payments recorded a large surplus, namely US$5,421

million. Accordingly, foreign exchange reserves in June

2010 swelled to US$76.3 billion, which was equivalent to

5.8 months of imports and foreign debt repayments.

In line with Indonesia»s favourable balance of

payments position the rupiah exchange rate

strengthened with low volatility. Compared to the end

of semester II-2009, the rupiah appreciated by 3.5% in

the first semester of 2010 to a level of Rp9,074 against

the US dollar. During the first semester of 2010, the

rupiah peaked at Rp9,160 per US dollar in the second

quarter. Meanwhile, average rupiah volatility against the

US dollar in semester I-2010 was 0.31% compared to

0.36% in semester I-2009. Accordingly, the rupiah

was 2.17% higher than the growth recorded in the second

quarter of 2009 at 4.0% (yoy).

The strengthening of domestic economic conditions

was influenced by the global economy, which posted signs

of recovery. The global economic recovery has advanced

exports performance, in particular manufactured exports.

In addition, relatively stable public purchasing power drove

domestic demand. On the other hand, however, increased

domestic economic activity was also expected to spur an

increase in imports, resulting in a slightly lower current

account surplus, namely US$1,834 million in June 2010,

down US$645 million compared to June 2009.

Nevertheless, this increase in imports was offset by a sharp

rise in exports as well as global commodity prices that

remained high.

Figure 1.5Value of Non-Oil/Gas Exports from Indonesia

2006 2007 2008 2009 20100

2000

4000

6000

8000

10000

0

2000

4000

6000

8000

10000

Million USD Million USD

Source: BI

ManufacturingMining and QuarryingAgriculture, Hunting, FishingTotal

Figure 1.6Non-Oil/Gas Export/Import Growth

Figure 1.7Price Indices of several Commodities

2007 2008 2009 2010

Million USD

-60

-40

-20

0

20

40

60

80

Export Non-Oil/GasImport Non-Oil/Gas

Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr

2007 2008 2009 2010

Million USD

Jan0

100

200

300

400

500

600

700

May Sep Jan May Sep Jan May Sep Jan May Sep Jan May2006

Oil Aluminium CopperTin Gold Palm OilCoffee

Figure 1.8Rupiah Exchange Rate

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

Source: Bloomberg2008 2009 2010

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 60

2,000

4,000

6,000

8,000

10,000

12,000

14,000

9,2599,257 9,124 9,134

11,623

10,542

9,985 9,4679,262 9,116

9,258 9,352

11,079

9,718 9,188

9,40

69,

180

9,17

89,

203

9,28

1

9,15

99,

288

9,15

19,

354

9,99

011

,803

11,3

1411

,152

11,8

7511

,865

11,0

5010

,377

10,1

9310

,113

9,98

49,

856

9,48

69,

457

9,45

9

9,34

59,

167

9,03

0

9,14

69,

173

9,28

6

Monthly averageQuarterly averageSemester average

12


remained relatively strong against other Asian and hard

currencies, excluding the Japanese yen, during Semester

I-2010.

In terms of the financial sector, optimism in the

recovery of global economic conditions, a robust domestic

economy as well as an improved rating and favourable

economic prospects provided global investors with positive

expectations that triggered a surge in foreign capital

inflows to Indonesia»s financial markets. Meanwhile, the

domestic financial market continued to improve, which

was reflected, among others, by better stock market

performance and rupiah appreciation. The Jakarta

Composite Index maintained a level of 2,893 during the

first semester of 2010, compared to 2,534 in the second

semester of 2009. This improvement in the performance

of the domestic stock market was in harmony with

improvements in the stock markets of neighbouring

countries in the region as well as other advanced countries.

By sector, the steepest hike in the stock price index affected

the consumption sector, more specifically a rise of 287.7

points from 671.3 at the end of semester II-2009 to 959.0

at the end of semester I-2010.

In terms of prices, inflationary pressures in the second

quarter of 2010 tended to intensify driven by non-

fundamental factors, especially volatile foods. At the end

of semester I-2010, consumer price index inflation had

reached 5.05% (yoy), increasing by 2.3% compared to

the end of semester II-2009. This increase was triggered

by uncertainty in the seasons as well as production and

distribution constraints stemming from unseasonably high

rainfall. Nevertheless, in general, inflationary pressures from

January to June 2010 remained under control within the

expected range.

The investment climate in Indonesia remained

attractive because interest rates continued to exceed the

inflation rate, thus, in real terms the interest rate in

Indonesia surpassed that of several other countries in the

ASEAN region, as well as the United States.

Foreign direct investment (FDI) to Indonesia during

the first semester of 2010 reached US$4,871 million, which

Figure 1.10Performance of Selected Global Currencies

2009

Index

80

85

90

95

100

105

110

115

31 Dec 2009 = 100Increase in the index = exchange rate appreciation

Dec Jan Feb Mar Apr May Jun2010

IDR SGD THB PHP KRW EUR JPY

Figure 1.11Sectoral Stock Price Index

Consumption GoodsMiningFinancialConstruction, Property and Real EstateTrade or Services

AgricultureBasic Industry and ChemicalMiscelianous IndustryInfrastructure dan TransportationJCI

2009

500

1000

1500

2000

2500

3000

3500

4000

2010

0Jan Mar JulMay Sep Nov Jan Mar JulMay Sep Nov Jan Mar May

2008

Figure 1.9Exchange Rate Volatility

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

31 61 91 121 151 181 211 241

Period (263 days)

Volatility

1

Lower Limit Upper Limit Actual

13


represents a significant jump from US$1,526 million at

the end of semester II-2009.

Looking forward, the Indonesian economy is

expected to continue improving despite being

overshadowed by a number of external and internal risk

factors. From a global perspective, the global economic

recovery that in turn can affect Indonesia»s economic

performance is a form of uncertainty risk relating to the

recovery in the US and slowdown in China.

In June 2010, primary indicators for the US economy

deteriorated, hence, uncertainty emerged regarding the

direction of economic conditions in the superpower. Non-

farm payroll data published by the Bureau of Labour

Statistics has declined since June 2010 subsequent to

experiencing a rise at the beginning of year. New job

creation in June (130,000) was less than that in May

(131,000). The stagnant recovery in the labour force sector

precipitated a decline in the consumer confidence index.

In addition, the Institute for Supply Management

Manufacturing Purchasing Managers» Index (ISM

Manufacturing), which indicates recent developments in

the US manufacturing sector by measuring purchases in

the sector, also declined. In June 2000, ISM Manufacturing

for the US was at a level of 56.2, representing a decline

compared to the previous month at 59.7, which indicates

a decline in expansionary activities in the US manufacturing

sector.

Meanwhile, in order to curb growth in China, which

is considered too rapid and in particular to prevent an asset

bubble appearing in the property sector, the Chinese

government rescinded its stimulus package. Accordingly,

Figure 1.12Inflation Rates in ASEAN-5

2007 2009

10

5

0

(5)

(10)

Philippines

y.o.y %

Jan Jun Nov Apr Sep Feb Jul Dec May2008 2010

Malaysia

Singapore

Indonesia

Thailand

Figure 1.13Real Interest Rates

2006 2009

Percent

2008 2010

-8.00

-6.00

-4.00

-2.00

0.00

2.00

4.00

Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun2007

Indonesia US Singapore

Figure 1.14FDI to Indonesia

2009

Million USD

2008 20102007

3,500

3,000

2,500

2,000

1,500

1,000

500

0Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

Figure 1.15Total Non-Agricultural Sector Employment

Total Employment

2010Feb

106,600

106,650

106,700

106,750

106,800

106,850

106,900

106,950

107,000

Source: The ADP National Employment Report, July 2010

Mar Apr May Jun Jul

14


economic expansion in China during the second semester

of 2010 is projected at a moderate level. Nevertheless,

many economists around the world consider these

measures to be temporary and, therefore, they will not

have a significant effect on the global economy as a whole.

Domestically, in line with the deluge of capital inflows

to the country, a number of microstructural challenges in

the domestic economy, including the relatively low

competitiveness of the industrial sector, need to be resolved

in order to stimulate investment and domestic

consumption, thus avoiding the risk of overheating as well

as credit and asset bubbles emerging.

1.2. REAL SECTOR CONDITIONS

Strong export performance driven by the global

economic recovery bolstered domestic real sector

performance;both household and corporate. Based on

survey results, household consumption during semester I-

2010 remained robust supported by relatively stable public

purchasing power and maintained consumer confidence.

This can be observed from the consumer confidence index,

which rebounded to an optimistic level.

Figure 1.16Consumer Confidence Index

just 3.3%. This indicates that the value of household debt

is very small compared to total household assets (see box

1.2). In terms of risk, the household sector has sufficiently

large assets in order to cover their liabilities in the event of

a shock to the household cash flow.

In terms of the corporate sector, strong household

consumption and a recovery in exports lifted corporate

sector performance at the end of semester I-2010 (quarter

II-2010). Improvements in the corporate sector were

reflected by the stronger financial performance of non-

financial companies listed on the Indonesian Stock

Exchange. ROA increased from 2.87% in the second

quarter of 2009 to 3.26% in quarter II-2010. Meanwhile,

ROE declined from 6.42% in the second quarter of 2009

to 6.12% in quarter II-2009.

60.0

70.0

80.0

90.0

100.0

110.0

120.0

130.0

140.0

Index

2010200920081 2 3 4 5 6 7 8 9 10 1112 1 2 3 4 5 6 7 8 9 10 1112 1 2 3 4 5 6

Present Situation Index (PSI)Consumer Expectation IndexConsumer Confidence Index

Increase ofFuel Price

Global EconomyCrisis

Optimistic

Pessimistic

Figure 1.17.1ROA and ROE of Non-Financial

Public Listed Companies

Figure 1.17.2DER and TL/TA of Non-Financial

Public Listed Companies

201020092008

ROA (left)ROE (right)

-200

-100

0

100

200

300

400

-300

-200

-100

0

100

200

300

400

500

600

700

20072006200520042003Q2 Q4 Q2 Q4 Q2 Q4 Q2 Q4 Q2 Q4 Q2 Q4 Q2 Q4 Q2

201020092008

DERTL/TA

20072006200520042003

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

Q2 Q4 Q2 Q4 Q2 Q4 Q2 Q4 Q2 Q4 Q2 Q4 Q2 Q4 Q2

Based on recent survey results, household balance

sheets in Indonesia are sound. The ratio of household debt

to household assets (gearing ratio) remained very low at

15


With respect to financing, the corporate sector relied

predominantly on internal capital and tended to reduce

funds loaned from a third-party, including banks as well

as the issuance of other bonds and securities. This is

evidenced by a decline in the debt to equity ratio (DER)

from 1.24 (quarter II-2009) to 0.88 (quarter II-2010) and

the ratio of total liabilities to total assets (TL/TA) in the

second quarter of 2009 compared to the same period in

2010.

Auspicious corporate conditions in Indonesia were

also observable from the liquidity ratios, namely the current

ratio, inventory turnover ratio and collection period. The

current ratio declined slightly from 1.36% (quarter II-2009)

to 1.31% (quarter II-2010). The downward trend in the

inventory turnover ratio indicated that the corporate sector

was able to efficiently manage its inventory. Meanwhile,

the collection period experienced a decline from 0.40

(quarter II-2009) to 0.29 (quarter II-2010). This indicates

that corporate revenue in the form of cash experienced a

decline compared to the same quarter in the previous

period.

In addition to credit risk, firms in the real sector also

faced exchange rate risk. The results of stress tests on 46

large conglomerates in Indonesia in December 2009

showed that one conglomerate has potential negative

equity. Accordingly, if the rupiah depreciated to Rp17,000

per US dollar it would have the potential to undermine

the performance of one conglomerate by reducing its

capital by 90%. In general, Indonesian conglomerates are

vulnerable to fluctuations in exchange rate. Furthermore,

waning export demand would affect domestic economic

growth; therefore, prudence is paramount considering that

18 large conglomerates have a ratio of net foreign liabilities

to equity of more than 25%.

Looking ahead, real sector performance will face

numerous arduous challenges relating, among others, to

financial system stability and economic resilience.

Uncertainty surrounding the US economic recovery

Figure 1.18Key Corporate Financial Indicators

2009:Q2 2010:Q2

Current Ratio

ROA

ROE

Inventory Turn OverRatio

Collection Period

DER

01234567

Percentage ofequity decrease

IDR/USD

10,500 11,000 11,500 12,000 12,500 13,000 13,500 14,000 14,500 15,000 15,500 16,000 16,500 17,000

Table 1.2Affect of Rupiah Depreciation on Conglomerate Equity

Number of corporatesNumber of corporatesNumber of corporatesNumber of corporatesNumber of corporateswith impacted equitywith impacted equitywith impacted equitywith impacted equitywith impacted equity

10% 2 8 9 7 8 10 8 7 6 6 6 7 5 520% 2 5 6 4 5 4 5 6 5 4 5 530% 1 2 2 4 5 3 2 3 4 5 340% 2 1 1 3 4 4 2 1 250% 1 2 1 1 2 4 3 360% 1 2 1 2 370% 1 180% 1 2 190% 1100%

22222 88888 1111111111 1313131313 1616161616 1818181818 1919191919 1919191919 1919191919 2121212121 2222222222 2323232323 2323232323 2323232323

16


Figure 1.19Ratio of Net Foreign Liabilities to Equity

%

150

100

50

0

(50)

(100)

(150)

(200)

Net forex obligation toequity ratio > 25%

R P A O T AD C B AN X U F AC E AL L AA AT G I AH W AQ

process has the potential to spark a possible capital

reversal. This would be expected to endanger domestic

financial system stabil ity. In addition, several

microstructural problems continue to plague the real

sector, for instance weak competitiveness of the industrial

sector and stagnant infrastructure development, which

need to be addressed immediately in the face of tighter

market competition.

17


Mortality Rate & Contingent Claim Analysis Approach:Potential Corporate Credit Risk in the Manufacturing Industry

Box 1.1

Mortality rate is one instrument to detect the

credit risk of a debtor by calculating the default rate or

percentage of debtors that will default (collectability

3, 4, 5) out of the total number of debtors in the

manufacturing industry. The technique used is the

mortality rate developed by Prof Edward I. Altman with

the following equation:

MMR(t)= debtors in default in year t/ total debtors at

beginning of year t

Utilising data from the Debtor Information

System, 10 mortality rate positions from 52

manufacturing industry subsectors are obtained.

Estimation results demonstrated that of the 52

subsectors, the subsector that assembles domestic

components (Maritime) had the highest mortality rate

of all other subsectors. Furthermore, most credit risk

was concentrated around debtors in this subsector. This

is reflected by:

Based on outstanding debt, the largest mortality

rate was experienced by the Maritime subsector in

the range of 48.45% to 50.44%.

Based on total debtors, the largest mortality rate

was experienced by other subsectors that assemble

domestic components in the range of 7.96% to

76.87%.

The Contingent Claim Analysis (CCA) Approach

is used to calculate the probability of default for

companies listed on the capital market. Default is

defined as when the value of a company»s assets is

surpassed by the value of its liabilities. Corporate equity

is analogous with the European Call Option; more

specifically this approach can calculate the value of a

firm»s implied assets. The data used includes the daily

equity of companies listed on the capital market for a

period of 260 days in order to obtain equity volatility

as well as the book value of liabilities for the period.

Basic Industry Animal Feed 6.5 2.7 2.3 0.4 3.5 5.1 5.8 2.6 0.3 0.3

Cement 14.3 15.2 0.4 2.2 2.8 1.4 1.1 0.1 0.0 0.0

Ceramics, Glass, Porcelain 1.2 0.3 0.0 0.0 1.0 0.5 0.5 0.5 0.0 0.0

Chemicals 11.4 9.6 2.3 5.1 6.9 7.2 7.1 4.4 0.4 20.4

Metal and Allied Products 16.8 10.5 18.8 19.0 0.8 0.1 1.4 1.1 1.1 0.6

Plastics & Packaging 4.8 3.7 3.4 3.6 2.9 2.6 2.3 1.4 33.7 20.2

Pulp & Paper 3.4 3.5 2.1 1.4 3.3 5.8 6.3 5.2 66.7 100.0

Wood Industries 6.2 8.8 6.6 6.3 11.7 17.2 16.7 12.1 0.0 0.0

Consumer Goods Cosmetics and Household 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 50.1 0.0

Industry Food and Beverages 5.8 1.1 1.8 2.1 2.3 3.6 5.1 3.5 0.0 0.0

Pharmaceuticals 2.0 2.4 2.6 2.7 1.7 2.0 2.3 4.2 0.3 0.3

Tobacco Manufacturers 0.1 0.1 0.1 1.8 2.5 1.4 1.0 0.1 0.0 0.0

Miscellaneous Automotive and Components 0.1 0.1 0.1 1.8 2.9 3.6 4.1 2.6 0.0 0.0

Industry Textile, Garment 3.8 5.3 4.6 2.9 2.8 5.6 8.2 9.2 0.0 0.0

Box Table 1.1.1Average Probability of Default of three Industrial Sectors

Sector Industry Sub Sector2008Q1

2008Q2

2008Q3

2008Q4

2009Q1

2009Q2

2009Q3

2009Q4

2010Q1

2010Q2

(Percent)

18


Box Figure 1.1.1Mortality Rate of Industrial Sub-sectors based on Outstanding Debits

Flour Industry Sugar IndustryRice Milling Crude Palm Oil IndustryPalm Oil Seed Industry Other Plant Oils

0

2

4

6

8

10

12

Oct»07-Sep»08 Jan»08-Dec»08 Apr»08-Mar»09 Jul»08-Jun»09 Oct»08-Sep»09 Jan»09-Dec»09 Apr»09-Mar»10 May»09-Apr»10 Jun»09-May»10 Jul»09-Jun»10

Paper and Paper ProductsPulp IndustryPharmaceutical Industry

Printing and PublishingFertilizers and PesticidesPlastics

0

1

2

3

4

5

6


10

20

30

40

50

60


Assembly of Automotive Foreign ComponentsAssembly of Agricultural Foreign ComponentsAssembly of Maritime Domestic Components

Assembly of Maritime Foreign ComponentsAssembly of Electronic Foreign ComponentsAssembly of other Foreign Components

Salt Industry Beverage IndustryTabaco Industry Cigarette IndustryOther Foods Livestock and Fish Industry

0

1

2

3

4

5

6


Other Chemical Products Remilling and SmokehouseCrumb Rubber Industry Other Rubber ProductsEssential Oils Chemicals, Natural Oil Produce, Coal

0

2

4

6

8

10

12

14

16


Assembly of Automotive Domestic ComponentsAssembly of Agricultural Domestic ComponentsProducer of Maritime Components

0

2

4

6

8

10

12

14


Assembly of Electronic Domestic ComponentsAssembly of other Domestic ComponentsProducer of Automotive Components

Estimation results show that of the three industrial

sectors, the largest probability of default (PD) was

experienced by the paper and pulp subsector with a

Textile Industry Clothing Industry Leather IndustryWood Industry Wooden Furniture Industry Other Wood Industries

0

2

4

6

8

10

12

14

16


Cement ProcessingTile ProcessingBase Metals, Iron and Steel

Brick/Roof Tile ProcessingProcessing, excluding other Natural Oil ProduceOther Base Metals

0

2

4

6

8

10

12


Electronic Component IndustryOther Component Industry

Agcriculture of Goods Component IndustryOther Industry

0

5

10

15

20

25


Box Figure 1.1.2Mortality Rate of Industrial Sub-sectors based on Number of Debtors

Flour Industry Sugar IndustryRice Milling Crude Palm Oil IndustryPalm Oil Seed Industry Other Plant Oils

0

2

4

6

8

10

12


Paper and Paper ProductsPulp IndustryPharmaceutical Industry

Printing and PublishingFertilizers and PesticidesPlastics

0

2

4

6

8

10

12

14


2

4

6

8

10

12


Assembly of Automotive Foreign ComponentsAssembly of Agricultural Foreign ComponentsAssembly of Maritime Domestic Components

Assembly of Maritime Foreign ComponentsAssembly of Electronic Foreign ComponentsAssembly of other Foreign Components

PD in the range of 1.4% to 100%. Meanwhile, the

probability of default of the plastic and packaging

subsector was in the range of 1.4% to 33.7%.

19


Salt Industry Beverage IndustryTabaco Industry Cigarette IndustryOther Foods Livestock and Fish Industry

0

2

4

6

8

10

12

14


Other Chemical Products Remilling and SmokehouseCrumb Rubber Industry Other Rubber ProductsEssential Oils Chemicals, Natural Oil Produce, Coal

0

2

4

6

8

10

12

14

16

18


10

20

30

40

50

60

70

80

90


Assembly of Automotive Domestic ComponentsAssembly of Agricultural Domestic ComponentsProducer of Maritime Components

Assembly of Electronic Domestic ComponentsAssembly of other Domestic ComponentsProducer of Automotive Components

0

2

4

6

8

10

12

14

16


Textile IndustryLeather IndustryWooden Furniture Industry

Clothing Industry

Other Wood IndustriesWood Industry

0

2

4

6

8

10

12


Cement ProcessingTile ProcessingBase Metals, Iron and Steel

Brick/Roof Tile ProcessingProcessing, excluding other Natural Oil ProduceOther Base Metals

0

2

4

6

8

10

12

14

Electronic Component IndustryOther Component Industry

Agcriculture of Goods Component IndustryOther Industry


Grafik Boks 1.1.2Mortality Rate of Industrial Sub-sectors based on Number of Debtors (cont.)

20


Household Debt Service Ratio (DSR) in IndonesiaBox 1.2

Throughout 2010 consumption credit grew

significantly, achieving 25.0% (yoy) in June.

Consequently, a question emerged: What is the

resilience of households in terms of servicing their

debts, in particular in the face of economic shocks

(interest rates and income)?

One method that can be used to measure the

ability of households in repaying their debts is the debt

service ratio (DSR). DSR is the ratio between debt

payments and disposable personal income (after taxes).

This ratio shows total disposable income available in

one year to service debt (principal and interest

payments).

Based on the Survey of Household Balance Sheets

2009 conducted in nine provinces with 3,987

respondents, the DSR of Indonesian population was

below 10%. DSR in Indonesia is not significantly

different compared to the USA (12.13% in June 2010)

and Canada (7.8% in 2007).

Survey results indicate that the highest DSR in

Indonesia was found on the islands of Java and Bali.

The high level of DSR on the islands of Java and

Bali is attributable to the familiarity of communities in

these areas with banking products; hence, they meet

their funding requirements (primarily to buy assets)

with debt.

If only indebted respondents are considered, DSR

in the nine provinces falls within the range of 9.8% to

20.2% and the highest debt service ratio is still found

on Java/Bali. Only one province outside of Java/Bali

has a DSR of above 10%, namely South Sulawesi.

DKI Jakarta 77 15.05

West Java 523 14.76

Bali 41 20.18

Central Java 517 14.33

East Java 318 13.27

South Kalimantan 45 10.14

South Sulawesi 39 15.08

South Sumatra 58 10.42

North Sumatra 104 9.84

Box Table 1.2.2Indebted Respondents by Province

Province TotalRespondent

DSR (%)

*) Respondents are indebted

DKI Jakarta 183 7.80West Java 1050 8.71Bali 84 9.55Central Java 900 8.98East Java 1038 4.90South Kalimantan 92 5.85South Sulawesi 199 4.49South Sumatra 175 3.86North Sumatra 266 4.34

Boks Table 1.2.1DSR by Province

Province TotalRespondent

DSR (%) Hitherto, no precise figure has been given for a

safe DSR limit; however, research in the past has used

30% (Devaney, 1994) and 40% (Canadian Bank) as

safe limits. Based on these limits, DSR in Indonesia

indicates that its citizens are capable of repaying their

debts.

21


Capital Flows and Financial System Stability in IndonesiaBox 1.3

The torrent of capital inflows to Indonesia during

semester I-2010 helped strengthen the rupiah

exchange rate. The results of empirical research

conducted by Bank Indonesia demonstrating that such

conditions had a positive impact on the bank

intermediation function (credit growth and deposits)

as well as asset prices (share prices and the residential

property price index) in Indonesia. Conversely, the surge

in capital inflows also requires close monitoring because

past experience has shown that a deluge of capital

inflows can trigger a credit boom as well as asset price

bubbles (IMF 2004, 2007b).

The history of crises that have befallen Indonesia

show that the Asian financial crisis of 1997/98 and

global crisis of 2008 were marked by high net

outflows, after experiencing a period of strong net

inflows in the previous year. Further research has

shown that the largest outflows during the crisis

periods stemmed from portfolio (stock and securities)

or short-term investment. In contrast, FDI or long-

term investment was more resilient to the crises, in

particular the crisis of 2008 when no significant FDI

outflows were reported compared to portfolio

investment.

Box Figure 1.3.1Framework: Mechanism (excessive) Capital Inflows leading to Financial and Economic Crisis

Pull (domestic) factors

- Real GDP or IPI- Interest rate differential- Inflation- Current account balance- Trade openness (ratio export & import to GDP)- Stock price- NPL

Push (external) factors

- Real GDP or IPI (Regional/USA)- Stock price (Regional/USA)

CapitalInflow

IDRappreciation

Import cost decreaseAmount of Import increase

Consumptionincrease

Credit increaseAsset/ collateral price increase(eg.house price and stock price)

Credit boom/Asset priceinflation (bubbles)

Inflation increasePolicy Interest rate increase

Credit & EconomyslowdownMore vulnerable banking& financial system

Bubble bursts/Asset/collateralprice decrease

Corporates & HH financialconditions decrease and

borrowers» default increase

Banks» provision increaseBanks» capital is eroded henceneed to increase

Procyclicality impact of provision &capital buffer:Liquidity squeezeAmplify declining credit growth

Amplify economydownturn or lead todeeper recession

22


The two crisis periods were also marked by

relatively high credit growth. In 1997, the ratio of credit/

GDP achieved 60.2% and credit growth posted 29%

yoy. In comparison, the ratio of credit/GDP in 2008

was 26.5% and credit growth was also 29% yoy.

On the stock market, both crisis periods were

proceeded by a spike in the real Jakarta Composite

Index (JSX), namely from Q4 1996 √ Q2 1997 and Q4

2006 √ Q2 2008 as illustrated in Figure 1.3.4.

Furthermore, the spikes in credit growth and real

JSX indicated a credit boom as well as asset price

bubbles followed by an overheating economy and

soaring inflation. However, a slowdown in credit

growth and corrections to asset prices as a result of

policy measures taken to raise the interest rate

threatened financial system stability and economic

growth as illustrated in the framework presented.

The results of empirical research conducted

by Bank Indonesia indicate that expansive credit growth

(primarily consumption credit) as well as the return on

share prices and the residential property price index

significantly raise inflation. This demonstrates that a

surge in capital inflows must be monitored in order to

avoid asset price inflation and excessive consumption

credit growth due to the subsequent threat to financial

system and economic stability in the event of rising

interest rates. This was confirmed by the results of

empirical research performed by BI where a 1% rise in

the BI rate and interest rate differential would

significantly reduce credit growth by 1.42%, the return

on shares by 5.09% and the property price index by

0.14%. In addition, according to results of the Financial

Sector Assessment Program (FSAP) a hike in the interest

rate would precipitate a correspondingly 0.05% rise

in credit default risk. Furthermore, considering that the

volatility of portfolio flows exceeds that of FDI flows, it

is important to implement measures that alleviate the

volatility of portfolio flows making them more resilient

to shocks that are vulnerable to trigger a sudden

reversal in outflows.

Box Figure 1.3.2Ratio of Credit to GDP and Capital Flows to GDP

Credit/GDP (%, left axis)Net flow/GDP (%, right axis)

0

10

20

30

40

50

60

70 6.00

4.00

2.00

0.00

-2.00

-4.00

-6.00

-8.00

-10.00

-12.001995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Global Financial Crisis 2008

Asian Financial Crisis 97/98

Box Figure 1.3.3Short-term Capital Flows (portfolio) versus

Long-term (FDI)

FDI/GDP (%)Portfolio/GDP (%)

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

-20

-15

-10

-5

0

5

10

010301030103010301030103010301030103010301030103010301030103012010

Box Figure 1.3.4JSX Composite vs. Trend

0

500

1000

1500

2000

2500

3000

REAL JCITREND*

199519961997 1998 19992000 2001 20022003 2004 20052006 2007 200820092010

Before 97/98 AsiaFinancial Crisis Period

Before 2008 GlobalCrisis Period

Note : Trend is counted with Hodrick Prescott method

Q4 Q3 Q2 Q1 Q4 Q3 Q2 Q1 Q4 Q3 Q2 Q1 Q4 Q3 Q2 Q1 Q4 Q3 Q2 Q1

23


References

International Monetary Fund (2004), ≈Are credit booms

in emerging markets a concern?∆ World Economic

Outlook, April, pages 147-66.

International Monetary Fund (2007b), Global Financial

Stability Report, Chapter III, ≈Quality of domestic

financial markets and capital inflows∆, October.

Monetary and Economic Department (2008),

≈Monetary and financial stability implications of

capital flows in Latin America and the Carribean∆,

BIS Papers, No. 43.

24



25

Chapter 2 The Financial Sector

Chapter 2The Financial Sector

26



27


2.1. INDONESIAN FINANCIAL SYSTEM

STRUCTURE

No significant structural change in the financial

system of Indonesia occurred during the reporting

semester. The banking industry, which consists of

commercial banks and rural banks (BPR), continued to

dominate accounting for 80% of total assets in the

financial sector. In contrast, the share of other industries

in the financial sector, for example insurance companies,

pension funds, finance companies, securities and pawn

brokers remained relatively low.

The financial sector expanded during semester I-2010 and stability was

maintained, bolstered by conducive domestic economic conditions. Banks,

as the dominant industry in the financial sector, performed positively.

Meanwhile, the stock and SUN markets continued to recover, hence, piquing

the interest of foreign as well as domestic investors.

Accordingly, total assets of commercial banks

expanded by Rp144.2 trillion (5.7%) to Rp2,678.3 trillion

by the end of June 2010. Meanwhile, the non-bank

financial market during semester I-2010 also indicated

positive performance, as reflected by the Jakarta Composite

Index (JSX) which increased by 14.97% to 2,913.68 on

the back of positive sentiment on the domestic and global

stock exchanges. Furthermore, the IDMA index for

government bonds (SUN) rallied 9.34% to 103.14.

2.2. FINANCIAL SECTOR RESILIENCE

One of the indicators used to evaluate financial sector

resilience is the Financial Stability Index or FSI. During the

reporting period, financial sector resilience improved,

reflected by a decline in FSI from 1.91 (December 2009) to

1.87 (June 2010). The improvement in FSI was supported

by the quality of bank credit as well as less volatility on the

stock market and SUN market.

Similar to the findings presented in previous editions

of the Financial Stability Review or FSR, the maximum

indicative limit for FSI is 2.00. As a comparison, when the

Figure 2.1Asset Composition of Financial Institutions

Commercial Banks

Rural Banks

Insurance

Pension Funds

Finance Companies

Securities Companies

Pawnshops

79.50%

1.10% 8.80%

3.10% 4.40% 2.70% 0.40%

The Financial SectorChapter 2

28


recent global crisis spilled over into Indonesia FSI reached

2.43 in November 2008. However, at the peak of the 1997/

98 crisisFSI topped 3.23. The performance of FSI over time

reveals greater financial stability. Furthermore, it is worth

noting that in June 2010 FSI was 1.87, which is in line

with projections from December 2009.

As a result of the improvement in global conditions,

coupled with the conducive domestic market, FSI

projections made at the end of semester II (December)

2010 are in the range of 1.45 - 2.02 with a baseline of

1.74. These projections are based on the expectation that

risks associated with bank credit, the stock market and

the SUN market will ease. Greater stability on these two

markets is inseparable from the expectation of improved

fundamentals and the upgraded sovereign rating of

Indonesia, which is approaching investment grade.

deposits, the slowdown in deposit growth is a factor that

requires attention.

Figure 2.2Financial Stability Index

Figure 2.3Deposits by Component

During semester I-2010, banks managed to gather

Rp123.3 trillion of the public»s funds bringing the total to

Rp2,096.04 trillion at the end of the semester. This

represents an increase of 6.23% compared to the previous

semester. Annually (yoy), growth of deposits slowed in

semester I-2010. When compared to the same period of

the previous year, deposits in June 2010 grew by 14.9%

(yoy) in contrast to the 17.4% posted in June 2009.

Nevertheless, this decline in deposit growth is not of great

concern considering that it is only slightly below the annual

average of the past five years, namely 15.2%.

Figure 2.4Deposits by Bank Group

July 2010: 1.84

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50Crisis 1997/1998: 3.23

Global Crisis (Nov 2008): 2.43Mini Crisis 2005: 2.33

June 2010: 1.872.02

1.45

1.74

1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9 1 5 9

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 20091 5 9

2010

0

5

10

15

20

25

Aug'08 = 9.7%

Jun'09 = 17.4%

Feb'10 = 9.3%

Jun'10 = 14.9%

Jan Sep May Jan Sep May Jan Sep May

%

2005 2006 20082007 2009 2010

T Rp

0

200

400

600

800

State-Owned Private Regional Dev. Joint Venture Foreign Bank Branch

Dec-09Jun-102.3. BANKS

2.3.1. Funding and Liquidity Risk

Deposits

Up to the end of semester I-2010 bank funding

continued to depend on deposits. As of June 2010, the

share of deposits as a source of funds reached 91.8%.

Meanwhile, the shares of other sources of funds, for

example interbank borrowing, loans received and

securities amounted to 6.3%, 1.3% and 0.6%

respectively. Due to the high dependence of banks on

One contributing factor to the slowdown in deposits

in 2010 is the realisation of the state budget. Up to June

2010, government transactions contracted, which is in

stark contrast to the previous year.

29


during semester I-2010, the majority of which stemmed

from an increase in foreign exchange checking accounts

(US$2.6 billion).

Liquidity Risk

Bank liquidity risk during semester I-2010 was

moderate. In general, banks maintained sufficient liquid

assets to fulfil their liabilities. On the other hand, however,

growth of credit exceeded that of deposits, therefore,

liquidity pressures emerged, in particular for banks with

limited liquid assets1 (see Box 2.2). In addition, the plan to

change the rupiah statutory reserve requirement (GWM),

primary reserves as well as the method used to calculate

LDR, had the potential to affect the banks» liquidity

conditions.

Figure 2.5State Budget Surplus/Deficit January to July

If observed by bank group, the slowdown in deposits

was primarily attributable to slow growth at state-owned

banks that depend heavily on government funds for their

deposit component. Up to the end of the reporting period,

only the group of state-owned banks continued to

experience negative deposit growth, however, it was not

significant.

Based on currency, the increase in deposits during

the reporting period was dominated by growth in rupiah

deposits amounting to Rp107.8 trillion. Meanwhile,

deposits denominated in foreign exchange grew by a mere

4.81% or Rp15.2 trillion. Relatively conducive domestic

economic conditions in the first half of 2010 lead to

positive public expectations regarding the rupiah interest

rate. Consequently, the public»s preference towards

deposits denominated in foreign exchange has returned.

Foreign denominated deposits increased by US$3 billion

Figure 2.6Foreign Exchange Deposits √ IDR/USD

Exchange Rate

T Rp

20092010

Jan Feb Mar Apr May Jun Jul

Expansion

Contraction

30

25

20

15

10

5

0

-5

-10

-15

-20

1 Primary reserves include cash and the bank account held at BI. Secondary reserves are BICertificates (SBI), other placements at BI and SUN (trading and AFS); and Tertiary reservesare HTM SUN.

Figure 2.7Bank Liquid Assets by Component

T Rp

Dec2009 2010

600

650

700

750

800

0

100

200

300

400

500

600Primary Reserves Secondary ReservesTertiary Reserves LIQUID ASSETS (rhs)

Jan Feb Mar Apr May Jun

T Rp

Primary Reserves (5.00) (3.18)

Secondary Reserves 49.25 11.52

Tertiary Reserves (46.78) (36.83)

Total (2.52) (0.35)

Table 2.1Components of Liquid Assets

Growth of Semester I-2010

Nominal (T Rp) %Billion USD

Forex Deposits (lhs)Exchange Rate (rhs)

Dec8,000

9,000

10,000

11,000

12,000

13,000

22

26

30

34

38

42

Rupiah

Nov Feb May Aug Nov Feb May2007 2008 2009 2010

30


2.3.2. Credit Growth and Risk

Credit Growth

Credit growth, which slowed in 2009, began to show

signs of recovery in semester I-2010. In the reporting

semester, bank credit expanded by Rp148.6 trillion (10.3%)

or 18.8% yoy, which exceeded that during 2009

amounting to Rp130.2 trillion (10.0%). The growth in bank

credit was primarily attributable to a recovery in economic

conditions that enabled the business community to

rebound.

The recovery in the business climate, among others,

was reflected by growth in foreign denominated credit

during the first semester of 2010. After experiencing

negative growth (-17.4%) in 2009 as a result of a decline

in export credit as well as rupiah appreciation, foreign

denominated loans achieved 8.0% growth in semester I-

2010 in harmony with the recovery in domestic and global

conditions. Despite the return to positive growth in foreign

denominated credit, bank loans remained dominated by

rupiah based credit with a share of 85% of the total.

Rupiah denominated credit increased by Rp131.8 trillion

(10.7%) in semester I-2010 compared to Rp174 trillion

for the whole of 2009. Relatively stable rupiah credit

growth compared to foreign exchange was reflected by

the high level of prudence exercised by banks in the

allocation of credit, considering that foreign exchange

denominated credit is associated with higher risks due to

its inherent exposure to exchange rate risks, as occurred

during the crisis of 1997/98.

Although not yet optimal, signs of a recovery in the

business climate also stemmed from a rise in the extension

of working capital credit from banks. In 2009, working

capital credit grew by a mere 2.7%, significantly lower

compared to the 28.4% achieved in 2008. Comparatively,

working capital credit during the first semester of 2010

grew by 8.1%. In addition, with the ongoing intensification

Figure 2.8Liquid Assets by Bank Group

A Rp2.5 trillion decline was reported in liquid assets

during semester I-2010, especially in the form of tertiary

reserves. Nevertheless, an 11.52% shift occurred in the

form of secondary reserves. This, coupled with credit

growth outpacing that of deposits, ensured that there were

no indications of banks reducing their liquid assets to fund

loans. In addition to the fact that the decline remained

within normal limits, it also only affected foreign bank

branches. Conversely, regional development banks as well

as state-owned banks actually increased their liquid assets

during the reporting semester. Therefore, in general there

are no indications yet of liquidity pressures stemming from

strong credit growth.

2 Cash constitutes cash placements in supplementary cash with excess reserves in an accountheld at BI after calculating the minimum statutory reserve.

T Rp

Dec2009 2010

T Rp

Jan Feb Mar Apr May Jun200

250

300

350

20

40

60

80Regional DevelopmentJoint Venture

Foreign Bank BranchState-Owned (rhs)

Private (rhs)

Adequate bank resilience against the decline in

deposits was also evidence of stable bank liquidity risk. As

of June 2010, the ratio of liquid assets to deposits reached

33.8%. This ratio, and based on the results of simulations,

demonstrates that no banks are in danger of experiencing

liquidity shortfalls in the event that 5% of bank deposits

are withdrawn (which represents the highest historical drop

in deposits that occurred during the 2008 crisis).

In order to anticipate the requirement for short-term

liquidity, banks maintain cash liquid assets of a specified

amount. As of June 2010, the average cash2 ratio was 2.5%.

31


of business activities, the allocation of working capital credit

has the potential to increase further. The allocation of other

types of productive credit, in the form of investment credit,

grew by 13.1% during the first semester of 2010;

approaching total investment credit growth of 16.4%

posted in 2009. Despite remaining dominant the share of

productive credit (working capital credit and investment

credit) tended to decline; from 72% at the end of 2008 to

69% at the end of semester I-2010. This is inseparable

from the rapid growth in consumption credit.

as it was viewed to have lower risk. Consumption credit

grew by 19.0% in 2009. Although the pace of

consumption credit growth has declined slightly in line

with the increase in productive credit allocation,

consumption credit still recorded 12.1% growth in the

first semester of 2010. In order to control the risks

associated with consumption credit; banks must continue

adhering to prudential principles and not disregard

prevailing conditions/procedures that govern the

extension of credit.

Figure 2.9Credit Growth by Type (yoy)

Figure 2.10Increase in Credit by Type - Semester I-2010 (ytd)

60%

50%

40%

30%

20%

10%

0%

-10%

-20%

-30%2002 2003 2004 2005 2006 2007 2008 2009 2010

Working Capital Credit Investment Credit Consuption Credit

Working Capital Credit Investment Credit Consumption Credit0

20

40

60

80

100

120

140

160Rp T

2008 2009 2010 (Jun)151.4

69.7

84.6

18.3

42.0

69.956.8

38.952.8

The global economic crisis undermined business

activity. Consequently, the extension of credit to

productive sectors declined as a result of weaker demand.

Concomitantly, banks withheld credit due to the increase

in risk associated with the potential rise in business

defaults. Therefore, credit growth is mainly attributable

to consumption credit, which remained attractive to banks

Figure 2.11Credit Growth by Economic Sector √ Semester I-2010 (ytd)

Figure 2.12Share of Credit by Economic Sector

20092010 (until June)

-50 -35 -20 -5 10 25 40 55 70 85 100T Rp

41.7

69.3

(23.7)

10.6

5.5

10.2

(1.5)

1.3

10.7

6.1

(13.7)

97.8

17.5

3.5

(2.5)

4.5

(1.1)

32.1

9.6

0.9

Trade

Others

Industry

Transportation

Construction

Agriculture

Business Services

Social Services

Mining

Electricity

Trade

Others

Industry

Transportation

Construction

Agriculture

Business Services

Social Services

Mining

Electricity

18%

34%

17%

5%

4%5%

9%3%

3%2%

The widespread reliance on bank loans during 2009

and the first semester of 2010 to non-business sectors

was reflected by the allocation of credit by economic sector

with the majority extended to the others sector. In 2009,

credit to the others sector increased by Rp69.3 trillion as

compared to Rp130.2 trillion total credit increase of the

banking industry. Meanwhile, during semester I-2010,

32


credit to others sector increase Rp97.8 trillion, equivalent

to 66% of the total credit increase reported during the

first semester of 2009. Approximately 91% of credit to

the others sector consisted of consumption credit, with

53% apportioned to households. Accordingly, the

household sector plays a significant role in maintaining

financial system stability.

Despite a decline in the allocation of mortgages,

credit for real estate increased by Rp5.7 trillion (21.3%) in

the first semester of 2010. The share of property credit is

only 14% of total bank credit; therefore, bank exposure

to property credit remained limited. However, potential

risk will persist, thus necessitating prudence from the

banks.

Credit Risk3

After peaking at 4.1% in the middle of 2009 as a

result of the global economic crisis, credit risk pressures

began to ease slowly and gross NPL dropped to 3.0% at

the end of the first semester of 2010. This improvement

in the NPL ratio was not only due to greater credit extension

during semester I-2010 but also as a result of a decline in

nominal NPL.

Figure 2.13Increase in Property Credit

Figure 2.14Property Credit Growth (yoy)

Figure 2.15Gross NPL

Mortgage

Real Estate

Construction

T Rp(5) 0 5 10 15 20 25 30 35

2010 (until June)

20092008

28.5

7.0

11.9

18.0

(1.3)

3.5

(3.4)

5.7

(2.8)

-40%

-20%

0%

20%

40%

60%

80%

Mortgage

Real Estate

2002 2003 2004 2005 2006 2007 2008 2009 2010

30

35

40

45

50

55

60

65

70

75

-

1

2

3

4

5

6

7

8

9

2006 2007 2008 2009 2010

Loan Loss Provision (rhs)Nominal NPL(rhs)

NPL Gross (lhs)

Net NPL (lhs)

% (Rp T)

3 Excluding channeling unless otherwise stated.

Despite the general improvement in credit growth

during the first semester of 2010 compared to 2009, as a

whole, the performance of property credit actually followed

a reverse trend. Property credit during semester I-2010

experienced a decline of 0.2%, in contrast to positive

growth of 10.1% posted in 2009. This decline in property

credit stems from a slowdown in mortgage loans, which

accounted for around 63% of total property credit.

Mortgages contributed 14.7% growth to property credit

in 2009 as opposed to -2.4% in the first semester of 2010. A Rp0.2 trillion decline in nominal NPL was recorded

in the first semester of 2010 stemming from an

improvement in the quality of working capital credit, for

which nominal NPL fell by Rp0.8 trillion. Banks appeared

to be relatively successful in alleviating credit risk pressures,

in particular working capital credit by restructuring non-

performing loans in 2009 when the nominal NPL of

working capital credit totalled Rp3.7 trillion. Nevertheless,

33


carefully addressed by the banks, especially following the

recent outpouring of consumption credit.

nominal NPL did increase for investment credit and

consumption credit. Despite a slight decline in total, the

share of nominal NPL stemming from working capital credit

continued to dominate with 54.5% of total bank nominal

NPL. Concerning the gross NPL ratio, working capital credit

also accounted for the highest ratio with 3.4%, followed

by investment credit and consumption credit with 3.0%

and 2.3% respectively.

Figure 2.16Credit Share by Collectability

Figure 2.17Increase in Nominal NPL by Credit Type

89.8%91.1% 91.0% 89.9% 91.0% 91.3%

6.1%5.4% 5.8%

6.2%5.7% 5.7%

0.6% 0.6% 0.6%0.9% 0.7% 0.6%

3.1% 2.5% 2.2% 2.3% 2.1% 1.8%

84%

86%

88%

90%

92%

94%

96%

98%

100%

Dec Jun Dec Jun Dec Jun2007 2008 2009 2010

Current Special Mention Substandard Doubtful Loss

T Rp

3.1

(2.6)

0.71.1

3.7

0.1

1.9

5.7

(0.8)

0.5 0.1

(0.2)

(4)

(2)

0

2

4

6

8

Working Capital Credit Investment Credit Consumption Credit Total

2008 2009 2010 (until June) Based on economic sector, the largest decline in

nominal NPL during the first semester of 2010 affected the

manufacturing sector as well as the trade, hotels and

restaurants sector. This decline in nominal NPL precipitated

a corresponding downtrend in the gross NPL ratio of the

manufacturing sector from 7.4% in June 2009 to 3.9% in

June 2010. Meanwhile, the gross NPL ratio of the trade,

hotels and restaurants sector decreased from 4.2% to 3.7%

in the same period. Conversely, the others sector experienced

the largest increase in total nominal NPL, however, as this

increase was followed by sufficient credit growth, the gross

NPL ratio of the others sector remained relatively stable at

2.5%. Despite a relatively stable ratio, the increase in nominal

NPL of the others sector requires attention, particularly as

the majority of credit to this sector is for households.

Although the gross NPL ratio of consumption credit

was the lowest among other credit types, risk pressures

intensified. For three consecutive years (since 2008) total

nominal NPL for consumption credit has increased. Despite

only a small increase in nominal NPL of just Rp0.1 trillion

for consumption credit in the first semester of 2010

(compared to an increase of Rp1.9 trillion in 2009) it still

indicates a potential increase in future credit risk if not

Figure 2.18Gross NPL Ratio by Credit Type

Figure 2.19Increase in Nominal NPL by Economic Sector

3.4%3.8%

2.5%

4.7%4.3%

2.5%

3.8%3.3%

2.6%

3.4%3.0%

2.3%

0%

1%

2%

3%

4%

5%

6%

7%

8%

Working Capital Credit Investment Credit Consumption Credit

Dec08 Jun09 Dec09 Jun10

T Rp

2010 (until June)

2009

0.6

(0.1)

(2.3)

(0.0)

0.5

4.2

0.2

0.1

0.5

2.0

(0.6)

0.1

(1.9)

0.0

0.1

(1.5)

0.5

0.3

0.9

2.0

-3 -2 -1 0 1 2 3 4 5

Agriculture

Mining

Industry

Electricity

Construction

Trade

Transportation

Business Service

Social Service

Others

34


Figure 2.20NPL Ratio by Sector

oppositely, nominal NPL of rupiah denominated credit

increased by Rp1.2 trillion.

From a differentstandpoint, credit risk also intensified

stemming from property credit. Total nominal NPL for

property credit increased by Rp0.6 trillion during the first

semester of 2010, with a corresponding increase in gross

NPL ratio to 3.2% compared to 2.9% at yearend 2009.

The increase in nominal NPL of property credit affected all

types, including mortgages, real estate and construction.

Such conditions need to be addressed by the banks in

order to prevent any future emergence of problems.

Figure 2.22Gross NPL ratio by Currency

In terms of risk, foreign exchange denominated credit

had the highest risk compared to rupiah denominated

loans. At the end of semester I-2010 the gross NPL ratio

of forex credit reached 3.4% compared to just 2.9% for

rupiah based credit. Despite surpassing that of rupiah based

credit, the gross NPL ratio of forex credit has fallen

dramatically compared to the position in May 2009 at

5.8%. During the first semester of 2010, total nominal

NPL of foreign exchange credit decreased by Rp1.4 trillion,

0%

1%

2%

3%

4%

5%

6%

7%

8%Jun09 Dec09 Jun10

AgricultureMining

IndustryElectricity

ConstructionTrade

TransportationBusiness Service

Social ServiceOthers

3.0

4.13.7

5.4

3.1

4.3

2.93.4

%

Dec-09

Dec-08 Jun-09

Jun-10

Rupiah Foreign Exchange0

1

2

3

4

5

6

7

8

Figure 2.21Increase in Nominal NPL by Currency

1.3

(0.2)

7.1

(1.4)

1.2

(1.4)

(5)

(3)

(1)

1

3

5

7

9

Rupiah Foreign Exchange

T Rp

2008

20092010 (Jun)

Figure 2.24Gross NPL Ratio of Property Credit

T Rp

2.3%

4.5%

3.6%2.8%

4.7% 4.8%

2.3%

3.7%4.2%

2.5%

4.2%4.5%

0%

1%

2%

3%

4%

5%

6%

7%

8%

Mortgage Real Estate Construction


Figure 2.23Increase in Total Nominal NPL of Property Credit

Mortgage

Real Estate

Construction

T Rp

(0.01)

0.01

0.2

0.5

(0.3)

0.4

0.2

0.4

0.04

(0.5) (0.2) 0.1 0.4 0.7 1.0

2010 (until June)

20092008

In anticipation of a possible increase in credit risk,

the banks withheld allocating property credit as reflected

by a reduction in total property credit in semester I-2010.

Such developments illustrate that measures taken by the

banks in 2009 to mitigate a potential increase in credit

risk by withholding credit were successful. Slow, even

35


interest rate hike. The results of stress testing the banks»

interest rates show that bank CAR would decline by 105

bps if the rupiah interest rate increased by 500 bps.

Therefore, banks are required to immediately begin

anticipating the possibility of an interest rate hike in line

with potential increases in the future inflation rate.

negative, credit growth for working capital credit, credit

to the manufacturing industry and foreign denominated

credit successfully reduced total nominal NPL in the

respective sectors. Credit allocation to these sectors is

expected to rebound in 2010 due to the alleviation of credit

risk. Meanwhile, in anticipation of a potential increase in

credit risk from the others sector, banks must remain

prudent in the extension of credit to this sector.

Figure 2.25Credit Risk Stress Test

14%

15%

16%

17%

18%

First 1.25X 1.5X 1.75X 2.0X 2.5X

CAR

17.4% 17.4%17.2%

17.0%16.8%

16.3%

Scenario

This requires extra attention from the banks

considering that credit risk remains the primary risk to

banks. The results of stress tests indicate that a 2.5-fold

increase in the gross NPL ratio (assuming 0% GDP growth)

in June 2010 would have the potential to reduce bank

CAR by around 113 bps.

Market Risk

Economic stability in the first semester of 2010

helped ease market risk. A steady interest rate coupled

with rupiah exchange rate stability and strong SUN prices

influenced banks positive performance.

Despite the current relative stability congruous to

stable interest rates, interest rate risk in general requires

continual monitoring by the banks considering their

funding structure that is around 90% made up by short-

term funds (less than three months). This funding structure

leaves banks open to potential losses in the event of an

Figure 2.26Rupiah Maturity Profile

T Rp

(700)

(500)

(300)

(100)

100

300

500

700

Dec08 Jun09

Dec09 Jun10

until 1 month 1-3 months 3-6 months 6-12 months >12 months

Figure 2.27Foreign Exchange Maturity Profile

T Rp

(700)

(500)

(300)

(100)

100

300

500

700

until 1 month 1-3 months 3-6 months 6-12 months >12 months

Dec08 Jun09

Dec09 Jun10

Figure 2.28Interest Rate Risk Stress Test

First 1% 2% 3% 4% 5%14%

15%

16%

17%

18%

CAR

17.4%17.3%

17.1%16.9%

16.6%16.4%

Scenario

In contrast, exchange rate risk remained relatively low

as a result of limited bank exposure to foreign exchange,

36


10 bps. However, when available-for-sale SUN were

included in the stress tests the impact was relatively large

because the majority of SUN owned are in the form of

AFS, therefore, CAR could potentially decline by 176 bps.

reflected by a net open position in June 2010 of just 3.1%.

Such limited exposure shielded the banks from the impact

of rupiah exchange rate appreciation/depreciation. These

conditions were further confirmed by the results of stress

testing exchange rate risk,which demonstrated that the

CAR of no bank would dip below 8% in the event of rupiah

exchange rate depreciation/appreciation of up to 50%.

Figure 2.29Net Open Position

Figure 2.30SUN Share

0%

2%

4%

6%

8%

10%

12%

National Private Joint Venture Regional Dev. State-Owned Foreign All Banks


8.4%

9.8%

4.5%

2.8%

2.8% 3.

6% 3.7% 3.9% 4.1%

3.1%

2.4% 3.

0%

7.2%

6.4%

4.1% 4.

5% 4.8%

5.9%

4.8%

2.8%

6.2%

2.0%

4.1%

3.1%


0%

10%

20%

30%

40%

50%

60%

70%

80%

HTM AFS Trading

56.9

%

36.9

%

6.2%

51.2

%

43.1

%

5.7%

49.2

%

46.2

%

4.6%

34.0

%

62.0

%

4.0%

The upward trend in SUN prices also favoured banks

that held a trading SUN portfolio. SUN dominated the

ownership of bank securities excluding SBI, with a share

of around 83% of total bank securities. The majority of

SUN portfolio owned by the banks was available for sale

(AFS) with a share of 62% of the total, followed by held

to maturity (HTM) with 34%. In comparison, the share of

trading SUN was just 4% of the total. Therefore, SUN

exposure, in particular trading SUN exposed to mark to

market, was relatively limited; hence, according to stress

tests the impact of a decline in CAR was negligible at just

Figure 2.31Stress Test - SUN Price Decline (AFS + Trading)

14%

15%

16%

17%

18%

CAR

First 5% 10% 15% 20% 25%

17.4%17.2%

16.9%

16.5%

16.1%

15.6%

Scenario

2.3.3. Profitability and Capital

Profitability

Amid the nascent global economic recovery

subsequent to the debt crisis in Europe, bank profitability

in the first half of 2010 remained under control. In semester

I, banks successfully posted net profits of Rp29.3 trillion,

which is higher compared to the two previous semesters.

These net profits already account for 64.9% of total

recorded profit/loss after tax in 2009.

Table 2.2Bank Profit/Loss

Operational L/R 18.8 21.1 23.2

Non Operational L/R 12.7 9.2 16.1

Pre Tax L/R 31.5 30.3 39.3

After Tax L/R 23.3 21.9 29.3

Semester I-09 Semester II-09 Semester I-10

Trillion

Other profitability indicators, namely the ROA ratio,

demonstrated an increase from 2.6% at the end of 2009

to 2.9% at the end of the reporting semester. However,

business efficiency followed downward trend, as reflected

by the BOPO efficiency ratio from 81.6% (December 2009)

to 84.8%.

37


The increase in bank profitability during the first

semester of 2010, among others, was attributable to

relatively robust credit growth compared to the previous

period, as well as a widening interest rate spread amid a

stable BI rate.

trillion or 59% of total profit. However, a large correction

to loan loss provisions at the beginning of the year caused

non-operational profits to exceed operational profits.

Figure 2.32ROA and Efficiency Ratio

-

20

40

60

80

100

120

-

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

ROAEffciency Ratio

2001 2002 2003 2004 2005 2006Jan Feb Mar Apr May Jun Jul Aug Sep Oct

2007

Figure 2.33Credit interest rate and BI Rate

Figure 2.34Interest Rate Spread

20

2003

16

12

8

4

02004 2005 2006 2007 2008 2009 2010

MicroMiddleBI rate

SmallCredit

20

16

12

8

42007 2008 2009 2010

1 month deposits Credit Avg

%

Up to the end of the reporting period the composition

of bank profits was dominated by operational profits. As

of June 2010, bank operational profits reached Rp23.2

Figure 2.35Banking Profit/Loss Composition

2010

T Rp

0,0

1,5

3,0

4,5

6,0

7,5

9,0Operational L/R Non Operational L/R

Jan Feb Mar Apr May Jun

The dominance of operational profits was supported

by an increase in Net Interest Income (NII). Average monthly

NII during the reporting period achieved Rp12.2 trillion/

month; exceeding that of the two previous semesters,

namely Rp10.6 trillion/month in semester I-2009 and

Rp11.0 trillion/month during the following semester.

Relatively expansive credit growth in 2010 and widening

interest rate spread represent two factors that precipitated

an increase in NII.

Figure 2.36Composition of Operational Profit

2010

T Rp

Jan Feb Mar Apr May Jun(15)

(5)

5

15

Forex Transaction Profit/LossInterest L/ROthers L/R Total Operational L/R

In terms of the banks» sources of interest income,

that originating from credit interest continued to dominate

(with a share of 81.1% in June 2010), followed by securities

(9.4%), BI (6.4%) and others (3.1%).

38


By bank group, foreign bank branches maintained

the highest capital adequacy ratio, followed by joint-

venture banks. Conversely, state-owned banks were

responsible for the lowest capital adequacy ratio of any

bank group. Such conditions, among others, primarily

stemmed from state-owned banks increasing their

extension of credit more than the other bank groups, while

foreign bank branches as well as joint-venture banks

preferred to restrict their credit growth in line with the

global crisis that was affecting their respective central office

or parent company overseas.

In the past semester the shares of interest income

from credit, BI and SSB have all expanded. Oppositely, the

shares of interbank interest as well as others have

contracted.

Capital

The banks successfully maintained their capital up

to the end of semester I-2010. The average Capital

Adequacy Ratio or CAR of banks throughout the first

semester of 2010 was 18.7%, representing an increase

over the previous semester at 17.3%. This increase was

due to the rise in capital exceeding the escalation in risk-

weighted assets. On average, capital at the end of semester

I-2010 grew by Rp35.1 trillion or 13.4% compared to the

average of semester II-2009. In comparison, average risk-

weighted assets in the reporting period of 2010 increased

by Rp53.6 trillion or 3.4% over the previous semester.

Figure 2.37Share of Interest Income

0%

20%

40%

60%

80%

100%

Jan'10 Mar'10 Jun'10

79.4% 80.6% 81.1%CreditBISecuritiesInter BankOthers

5.7% 6.2% 6.4%8.7% 8.7% 9.4%

5.1% 3.8% 2.5%1.1% 0.6% 0.5%

Figure 2.38Capital, Risk-Weighted Assets and CAR

2010

Rp T

0.00

5.00

10.00

15.00

20.00

25.00

0

500

1000

1500

2000

2500%

CAPITAL RWA CAR

Dec Feb Apr Jun Aug Oct Dec Feb Apr Jun20092008

Figure 2.39CAR by Bank Group

State-Owned

40%

30%

20%

10%

0%PrivateForex

PrivateNon-Forex

RegionalDevelopment

Joint Venture Foreign BankBranch

Dec»09 Mar»10 Jun»10

With respect to CAR, it should be noted that in 2010

banks in Indonesia are obliged to maintain a capital reserve

against their operational risk. The size of the reserve is

based on the Basic Indicator Approach (BIA), more

specifically factor (alpha) multiplied by (positive) average

gross income for the past three years. The factor (alpha)

applied in the calculation of operational risk was 5% for

semester I-2010, and will be 10% from July 2010 and

15% from January 2011 (see Box 2.3).

2.4. NON-BANK FINANCIAL INSTITUTIONS AND

THE CAPITAL MARKET

2.4.1. Finance Companies

The performance of finance companies improved

during the first semester of 2010. Growth in financing

39


reached 14.50%, which enabled finance companies to

increase their asset base by 15.55%. The growth in

financing offered by finance companies was facilitated by

an increase in balanced funding sources as well as

supplementary capital. The sources of funds available to

finance companies in the first semester of 2010 increased

by 15.15% while capital grew by 2.67%.

Referring to the source of funds, declining interest

rates failed to encourage finance companies to boost their

funding sourced from the capital market. The preferred

source of funds is still concentrated from bank loans

(domestic and foreign). In the first semester of 2010, loans

from domestic banks increased by 20.37%. In contrast,

funds sourced from the issuance of bonds remained

relatively low at just Rp5.1 trillion, of which a part consisted

of refinancing mature corporate bonds.Figure 2.40

Business Activity of Finance Companies

0.00

50.00

100.00

150.00

200.00

250.00

Assets Financing Funding Capital

15.55%

14.50%

15.15%

2.67%

June 2009 December 2009 June 2010

In terms of the type of financing, consumer finance

remained dominant. In semester I-2010, consumer finance

offered by finance companies grew rapidly, achieving

19.59%, however, credit cards experienced negative

growth of -8.21%. Accordingly, the share of consumer

finance, which accounts for the largest portion, remained

the most prodigious in the range of 68%.

Figure 2.41Composition of Finance for Finance Companies

120,000

140,000

160,000

100,000

80,000

60,000

40,000

20,000

0

Jun»09Dec»09Jun»10

131,905 46,655 2,005 1,012 82,234142,539 46,528 2,027 930 93,054163,201 48,985 2,084 854 111,279

up 14.50 %

TotalFinancing Leasing Factoring Credit Card Consumer

Financing

tide 30.01%up 5.28%

tide 1.28%up 2.79%

tide 0.52%up 8.21%

tide 68.19%up 19.59%

Billion Rp

Figure 2.42Finance Companies» Source of Funds

Billion Rp

140,000

120,000

100,000

80,000

60,000

40,000

20,000

0

20.37%

7.81%

17.47%

15.15%

Domestic BankLoans

Foreign BankLoans

IssuedSecurities

Total Source of Fund*

Total Source of Fund*: Securities, Subordination Loans and Total Domestic and Foreign Bank Loans

Jun»09Dec»09Jun»10

The improvement in finance company performance

was also evidenced by an increase in profit before tax,

which was proportional to the growth in assets.

Consequently, ROA and ROE were successfully maintained

at 0.03% and 0.14% respectively. As mentioned, the

finance offered by finance companies concentrated on

Assets 161,813 174,442 201,570Debt 112,686 115,555 133,057Obligation 126,895 134,354 158,180Capital 34,918 40,088 43,390Profit Before Tax 5,010 10,421 5,869Profit After Tax 3,789 7,827 4,637ROA 0.03 0.06 0.03ROE 0.14 0.26 0.14BOPO 0.74 0.74 0.71Debt/Equity 3.23 2.88 3.07Obligation/Equity 3.63 3.35 3.65

Table 2.3Finance Ratios of Finance Companies

in Billion Rp Jun-09 Dec-09 Jun-10

40


consumer finance, in particular to finance the purchase of

motor vehicles. Strong demand for motor vehicle finance

was reflected by the revised sales target for motor vehicles,

which was raised 20% by the Combined Motor Vehicle

Industry of Indonesia (GAIKINDO).

Regarding efficiency, finance company performance

improved as shown by the BOPO efficiency ratio that

declined to 0.71% (previously 0.74%). The boost in

efficiency of finance companies was primarily the result of

lower operational costs.

With reference to the quality of finance, the

performance of finance companies experienced a slight

decline as evidenced by the rise in nominal NPL to Rp2.9

trillion. However, persistently strong growth in finance

actually brought down the NPL ratio to 1.72% (from

1.91% in semester II-2009).

In the first semester of 2010 indications emerged

of an increasing number of banks affiliated with finance

Table 2.4NPL of Finance Companies

NPL

Dec 09 Jun 10 Sem I 10

Changes of NPL Nominal (in Thousand Rp)

Leasing Factoring Credit CardFinance

Companies

Growth ofFinance Activity

1 19.81% 16.22% - - - - 22.14%2 0.10% 0.40% - - - 11,961 43.31%3 0.00% 0.00% - - - - - 80.29%4 0.06% 0.00% - - - -84 28.45%5 0.00% 0.25% - - - 387 55.12%6 1.51% 0.83% -2,138 - - -11,327 13.45%7 7.58% 6.08% - - - -296 12.77%8 0.55% 0.08% - - - -2,810 13.93%9 0.06% 0.03% - - - -285 20.03%10 3.90% 1.32% - - - -51,279 14.99%11 0.00% 0.00% - - - - - -2.33%12 0.00% 0.00% - - - - - 1.49%13 0.00% 0.00% - - - - - 3.61%14 0.00% 0.00% - - - - - 18.73%15 0.00% 0.51% 5,418 - - - 9.93%16 0.37% 0.24% - - - -298 14.88%17 0.00% 0.00% - - - - - 12.98%18 0.01% 0.07% 285 - - - 86.46%19 88.67% 88.67% - - - - - -2.12%20 0.05% 0.03% - -184 - -192 36.35%21 0.00% 0.00% - - - - - -22 0.00% 0.00% - - - - - 19.56%23 0.00% 0.00% - - - - - -42.28%24 20.65% 22.27% 54 - - 786 -7.25%25 0.00% 0.00% - - - - - -5.96%

companies. At the end of the semester as many as 25

finance companies were affiliated with banks. This

number has increased compared to the 14 recorded at

the end of semester II-2009. The majority of finance

companies affiliated with banks experienced a decline in

their NPL ratio, notwithstanding the five finance

companies that suffered a deterioration in their NPL ratio

Leasing 743.03 730.03 714.49Factoring 247.82 126.34 123.01Credit Card 44.08 40.84 47.01Consumer Financing 1,789.27 1,932.14 2,016.96Total Pembiayaan 2,824.20 2,829.34 2,901.47

Table 2.5NPL of Finance Companies

Nominal NPL (billion Rp) Jun-09 Dec-09 Jun-10

% NPL Jun-09 Dec-09 Jun-10

Leasing 35.37% 11.96% 46.13%Factoring 1.52% 2.72% 0.86%Credit Card 0.77% 0.00% 1.17%Consumer Financing 62.34% 85.31% 51.85%

41


the other hand, financial market strengthening, which was

predominantly supported by short-term inflows has the

potential to become a source of financial system instability,

particularly if accompanied by a sudden capital reversal.

Throughout the first semester of 2010, interest of

foreign investors to invest in short-term investments in

rupiah financial assets remains high. This was observed

from a Rp50.26 trillion surge in short-term inflows for the

purchase of rupiah financial assets (a Rp52.38 trillion

increase was reported in semester II-2009). Foreign inflows

rapidly swelled the foreign SUN portfolio by Rp46.42 trillion

in addition to net stock purchases of Rp6.22 trillion.

Meanwhile, foreign SBI portfolio declined by Rp2.38 trillion.

Short-term inflows, in turn, helped strengthen the Rp/USD

exchange rate by 3.5% and bolstered foreign-exchange

reserves that expanded by 21%.

as a result of the increase in nominal NPL exceeding

growth in finance.

In addition, five finance companies experienced

negative growth financing, however, their respective NPL

ratio and nominal NPL remained relatively unchanged. Just

one finance company experience an increase in NPL with

a simultaneous decline in finance activity growth.

2.4.2. Capital Market

Risk Potential and Foreign Investment

During semester I-2010 the prospect for a stable

domestic interest rate reinforced the financial market and

attracted the interest of foreign investors in rupiah financial

assets, in particular stock and SUN. This bolstered the

continuation of short-term inflows that strengthened the

Rp/USD exchange rate and foreign exchange reserves. On

Figure 2.44Foreign Investment in SBI, SUN and Stock

23.0019.0015.00

11.00

7.003.00

-1.00-5.00

-9.00-13.00-17.00

-21.00-25.00

Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

2008 2009 2010

T Rp

SBI Government Bonds Stocks

Figure 2.45Foreign Portfolio in Rupiah Financial Assets

(SBI, SUN, Stock)T Rp

46.0040.00

34.00

28.00

22.00

16.00

10.00

4.00

-2.00

-8.00

-14.00

-20.00Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

2008 2009 2010

-0.84

-17.29

-0.77

16.63

28.6323.74

44.77

5.50

Figure 2.43Composition of Nominal Finance

by Finance Companies

23.0019.0015.00

11.00

7.003.00

-1.00-5.00

-9.00-13.00-17.00

-21.00-25.00

Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

2008 2009 2010

T Rp

SBI Government Bonds Stocks

Figure 2.46Stock Market

20.00

15.00

10.00

5.00

0.00

-5.00

-10.00

30

20

10

0

-10

-20

-30

-40Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun

2009 2010

Rp/US$ (%)IDMA Index (%)

JCI (%)Total INFLOS (trillion Rp)

42


The Jakarta Composite Index continued a bullish

trend during the first semester of 2010 buoyed by positive

sentiment regarding a rebound on global and regional

stock exchanges. Positive sentiment stemmed from

indications of an economic recovery in the US as well as

detailed fiscal stimuli and a banking sector rescue package

in Europe to alleviate the European debt crisis.

In addition, there was an improvement in the financial

performance of several global issuers, for instance

Citigroup, GM, Ford, Toyota and Motorola boosted investor

optimism regarding a global financial market recovery. The

Jakarta Composite Index rallied 14.97% to achieve

2,913.68 as a result of positive sentiment from global and

domestic stock exchanges. Domestically, positive sentiment

principally emanated from Indonesia»s net positive trade

balance amounting to US$518 million, a strong consumer

confidence index and annual GDP growth (yoy) totalling

4.55% in 2009 (4.4% expected). Furthermore, the Japan

Credit Rating Agency upgraded Indonesia»s sovereign

rating from BB+ to BBB- for foreign currency long-term

senior debt (with a stable outlook) and Fitch Ratings

upgraded the local currency credit rating from BB+ to BB.

By sector, nearly all sectoral indices improved with

the consumption sector posting the best performance (up

42.86%) followed by the miscellaneous industries sector

(up 34.54%). The gains in these two indices were

principally spurred by positive sentiment regarding

persistently high GDP growth in 2010, which is expected

to strengthen demand for consumer goods as well as

motor vehicles. Conversely, the agricultural sector index

experienced a decline (-5.20%) due to relatively stable

commodity prices on the international market and a steady

oil price at US$81 per barrel. The infrastructure sector

index also slumped (down 6.92%) affected by negative

sentiment driven by uncertainty regarding the

governments plan to reduce the budget deficit as well as

the impact of planned infrastructure development by the

government.

Table 2.6Indices of Regional Markets

JCI 2,026.78 2,534.36 2,913.68 14.97% 43.76%FSSTI 2,333.14 2897.62 2835.51 -2.14% 21.53%SET 597.48 734.54 797.31 8.55% 33.45%KLCI 1,075.24 1,272.78 1,314.02 3.24% 22.21%PCOMP 2,437.99 3,052.66 3,372.71 10.48% 38.34%NKY 9,958.44 10,546.44 9,382.64 -11.04% -5.78%Hang Seng 18,378.73 21,872.50 20,128.99 -7.97% 9,52%KOSPI 1,390.07 1,682.77 1,698.29 0.92% 22.17%NYA 4,249.21 7,184.96 6,469.65 -9.96% 52.26%UKX 5,905.15 5,412.88 4916.87 -9.16% -16.74DJIA 8,447.00 10,428.05 9,774.02 -6.27% 15.71%

GrowthJun 09 Dec 09 Jun 10

Sem I 10 Dec09-Jun10

Figure 2.47JCI as well as Global and Regional Indices

2.20

1.70

1.20

0.70

0.20

IHSGPCOMPNYA

FTSENKY

KLCIDJA

FSTTISETHangSeng

KOSPI

Jun Jul Aug Sep Nov Dec Jan Feb Mar Apr Mei JunOct

2009 2010

JCI 2,026.78 2,534.36 2,913.68 14,97% 43.76%

Financial 243.66 301.42 377.18 25.13% 54.80%

Agriculture 1,527.00 1,753.09 1,660.50 -5.28% 8.74%

Basic Industry 192.92 273.93 312.02 13.90% 61.73%

Consumption 495.73 671.31 959.04 42.86% 93.46%Property 144.79 146.80 163.38 11.30% 12.84%Mining 1,848.54 2,203.48 2,238.86 1.61% 21.11%Infrastructure 610.53 728.53 678.12 -6.92% 11.07%Trade 217.84 275.76 317.02 14.96% 45.53%Miscellaneous Industries 416.21 601.47 809.20 34.54% 94.42%

GrowthJun 09 Dec 09 Jun 10

Sem I 10 Jun09-Jun10

Table 2.7Sectoral Indices

In semester I-2010 volatility on the domestic stock

exchange intensified from 18.45 (December 2009) to

32.88 (June 2010) due to negative sentiment from the

43


(21,57%), Danamon (18,66%) andBNI (18,69%).

Oppositely, the prices of shares from BII and NISP slumped

by 13.64% and 8.00% respectively.

Government Bonds (SUN) Market

Based on the SUN price index (IDMA), the price of

SUN soared 9.34% in semester I-2010 to 103.14 (increased

by around 4% in semester II-2009) on the back of stable

interest rates projected until year end 2010. The SUN price

peaked in semester I-2010 at 105.22 (on 23rd June 2010).

debt crisis in Europe that triggered outflows and a

sufficiently deep correction in the JSX to around 2,500.

However, the favourable performance of domestic

economic indicators as well as the positive prospects of a

global market recovery (after receiving assurance that the

debt crisis in Europe will be resolved) encouraged foreign

investors to return and actively purchase stock in emerging

markets, including the domestic stock exchange, thus

strengthening the JSX.

Figure 2.48Volatility of several Asian Bourse Indices

45

40

35

30

25

20

15

10

5

0

MalaysiaSingapore

ThailandIndonesiaJapan Hongkong

%

Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun2009 2010

Figure 2.49Bank Share Prices

Niaga (LHS)Bukopin (LHS)BRI (RHS)

Permata (LHS)BCA (RHS)Danamon (RHS)

Panin (LHS)Mega (RHS)BNI (RHS)

BII (LHS)Mandiri (RHS)NISP (LHS)

1,600

1,400

1,200

1,000

800

600

400

200

0

10,000

9,000

8,000

7,000

6,000

5,000

4,000

3,000

2,000

1,000

001/04 06/04 11/04 16/04 21/04 26/04 01/05 06/05 11/05 16/05 21/05 26/05 05/0631/05 10/06 15/06 20/06 25/06 30/06

2010

The prospects of a stable interest rate up until year

end 2010, buttressed by sound bank performance, shored

up bank share prices. In semester I-2010, the majority of

bank shares rallied, more specifically BCA (22.68%), Mega

(15.22%), CIMB Niaga (50,70%), Permata (48,75%), Panin

(34,21%), Mandiri (27,66%), Bukopin (78,67%), BRI

Figure 2.51Average Monthly SUN Price

Jun Jul Aug Sep Nov Dec Jan Feb Mar Apr May JunOct

120

110

100

90

80

70

60

Short-Term <5 years

Short-Term >7 years

Middle-Term 5 until 7 years

Monthly 2 times average

2009 2010

Figure 2.50Percentage Change in Bank Share Prices

80.00%

70.00%

60.00%

50.00%

40.00%

30.00%

20.00%

-20.00%

-10.00%

0.00%

10.00%

BCA Mega Niaga Permata Panin BII Mandiri Bukopin BRI Danamon BNI NISP

Throughout semester I-2010, the average monthly

SUN price for short tenure (<5 years) and long tenure (>7

years) gained the most, namely 389 bps (up 4.18%) and

737 bps (up 9.17%) respectively. In contrast, medium-

tenure SUN (5-7 years) slipped 190 bps (down 0.23%).

Nonetheless, based on a VaR analysis the potential liquidity

risk of SUN for all tenures eased significantly.

44


During the same period the issuance of SUN by the

government increased 6.79% to Rp621.23 trillion with

bank ownership diminishing significantly from Rp254.36

trillion (December 2009) to Rp232.67 trillion (June 2010).

Notwithstanding, banks remained the primary investor in

SUN with a share of 37.45% (in December 2009 the share

was 43.72%). Foreign investors also accounted for a large

share of SUN ownership, as well as insurance companies

and mutual funds with respective shares of 26.08%,

12.47% and 7.86% in June 2010 (in December 2009 the

particular shares were18.56%, 12.48% and 7.77%).

Performance in the first semester of 2010 indicated a

significant increase in foreign SUN ownership, up 50.05%,

in comparison to just 6.70% and 8.01% for insurance

companies and mutual funds respectively.

Figure 2.52SUN VaR

5.000

4.500

4.000

3.500

3.000

2.500

2.000

1.500

0.000

1.000

0.500

Middle-Term

Short-Term

Long-Term


2009 2010

Table 2.8VaR by SUN Tenure

June 09 2.168 3.071 4.526

July 09 2.168 3.063 4.523

Aug 09 2.169 3.061 4.517

Sep 09 2.124 2.957 4.354

Oct 09 1.335 2.094 2.637

Nov 09 0.974 1.645 2.088

Dec 09 0.757 1.293 1.560

Jan 10 0.625 1.201 1.412

Feb 10 0.514 1.028 1.229

Mar 10 0.399 0.846 0.908

Apr 10 0.384 0.835 0.919

May 10 0.384 0.899 1.001

June 10 0.361 0.808 0.930

Tenor ShortTerm

MiddleTerm

LongTerm

Table 2.9SBN Ownership

Banking 254.36 232.67 -21.69

BI 22.5 19.12 -3038

Mutual Fund 45.22 48.84 3.62

Insurance 72.58 77.44 4.86

Foreign 108 162.05 54.05

Pension Fund 37.5 36.48 -1.02

Securities 0.46 0.13 -0.33

Others 41.12 44.49 3.37

Total 581.74 621.22 39.48

T RpSBN Ownership (Nominal)

Dec 09 Jun 10 Change

Figure 2.53SUN Maturity Profile (June 2010)

60

50

40

30

20

10

-

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

2030

2037

2038

T Rp

Fixed Rate Variable Rate

The maturity structure of fixed-rate SUN indicated

an uneven liquidity distribution. SUN liquidity was

concentrated around short-tenure SUN (<5 years) and long-

tenure SUN (>7 years) amounting correspondingly to

Rp133.64 trillion and Rp197.90 trillion with respective

shares of 52.67% and 35.56% of all fixed-rate SUN. The

position of medium-tenure SUN (5-7 years) was just

Rp44.22 trillion or 11.77% of all fixed-rate SUN.

Mutual Funds

In semester I-2010 the number of mutual funds

declined from 610 units (December 2009) to 598 (June

2010), among others, because protected funds completed

their contractual term. However, the prospect of a stable

45


interest rate piqued the interest of investors, hence,

augmenting the performance of mutual funds. The NAV

of mutual funds increased by 8.52%, primarily stemming

from fixed-income funds and protected funds, for which

their respective NAV increased by 13.25% and 6.35% to

Rp22.75 trillion and Rp36.82 trillion, accompanied by a

rapid increase in money market funds, which grew 41.65%

to Rp15.53 trillion.

accounted for the largest portion of NAV with 30.03%

(the largest portion of NAV in December 2009 was

29.66%). Conversely, the portion of NAV for equity funds

slipped to 29.33% after making up the largest portion in

December 2009 with 31.28%.

Figure 2.54Performance of Mutual Funds

140.00

120.00

100.00

80.00

60.00

40.00

20.00

0.00

620

Dec Jan Feb Mar Apr May Jun

615

610

605

600

595

590

585

No. of Mutual FundsNAV, trl Rp No. of Stocks/Unit-Billion

2009 2010

Table 2.10Issuances of Corporate Bonds and Value of Mature Corporate Bonds

1 BFI Finance Indonesia 200

2 Astra Sedaya Finance 1500

3 BCA Finance 600

4 North Sulawesi Regional Bank 500

5 Federal International F 1500

6 Bank Tabungan Pensiunan Nasional 1300

7 Titan Petrokimia Nusantara 300

8 Oto Multiartha 1300

9 Bank Tabungan Negara 1650

10 Bank OCBC NISP 1000

11 Telkom Indonesia 3000

12 Bank CIMB Niaga 1380

13 Perusahaan Listrik Negara 3000

14 Sarana Multigriya Finansial 727

15 Lembaga Pembiayaan Ekspor Indonesia 3000

16 Selamat Sempurna 240

Total 21197

Companies Value of Bond Issuances

in billion Rpin billion Rpin billion Rpin billion Rpin billion Rp

1 PTPN 450

2 BCA F. 125

3 Obligasi Astra Sedaya 28

4 Bank Ekspor Indonesia 200

5 Obligasi Astra Sedaya 334

6 Indosat 640

7 Obligasi Bhakti 144

8 Jasa Marga 650

9 Obligasi Oto Multiartha 200

Total 2771

Companies Value of Matured Bonds

in billion Rpin billion Rpin billion Rpin billion Rpin billion Rp

Figure 2.55Net Asset Value by type of Mutual Fund

0.00

10.00

20.00

30.00

40.00

50.00

Dec Jan Feb Mar Apr May Jun2009 2010

StocksFixed IncomeETF-Stocks

Money MarketProtectedETF-Fixed Income

MixedIndexSharia

The rapid escalation of these three types of mutual

funds offset the impact of a 1.48% decline in the NAV of

equity funds. Accordingly, in June 2010 protected funds

Financing through the Capital Market and other

Financial Markets

In the first semester of 2010, growth in financing

through the issuance of shares remained low as

demonstrated by the small increase in the value of shares

46


Figure 2.56Capitalisation and Stock Issuances

3,000.0

2,500.0

2,000.0

1,500.0

1,000.0

500.0

0.0

3,500.0

3,000.0

2,500.0

2,000.0

1,500.0

1,000.0

500.0

0.0

T Rp Issuer


2009 2010

Issuance Value JCI (RHS)Capitalization Value (JSX)

Figure 2.57Issuances of Corporate Bonds

190

185

180

175

170

165

160

155

150

145

86

85

84

83

82

81

80

79

78

77

76

(Issuance in Trillion) (Issuer)


2009 2010

Issuance (LHS)Issuer (RHS)

issued of just 4% to Rp437.59 trillion (up 2% in semester

II-2009). Similarly, the amount of issuers remained relatively

limited, with an additional five companies bringing the total

to 502. Slow growth in stock issuers amid rapid market

capitalisation (up 14%) was due to investors becoming more

active in short-term transactions in order to seek capital

gains. Such investor behaviour, which was not offset by

stock issuers, could potentially spark an asset price bubble

that would leave the stock market vulnerable to instability.

The stable and low interest rate is yet to have any

significant impact on the issuance of corporate bands on

the domestic capital market. In semester I-2010 the value

of bond issuances increased by around 7.84% to Rp187.38

trillion. The growth in issuers was also low with just two

additional companies bringing the total to 185. Sixteen

companies issued corporate bonds in the first semester of

2010 to the tune of Rp21.19 trillion. The majority of

corporate bond issuances, in particular issuance by finance

companies, were refinanced. Five finance companies issued

corporate bonds in the same period with a value of around

Rp5.1 trillion as well as two special financial institutions

valued at Rp3.73 trillion.

47


Statutory Reserve Requirement (SSR) – Loan to Deposit Ratio(LDR)

Box 2.1

On 3rd September 2010, Bank Indonesia

announced a new policy regarding the statutory reserve

requirement (SSR) in rupiah using the following

equation:

Rupiah SSR = 8% of primary reserves + 2.5% of

secondary reserves + LDR SSR

The new policy initiated a change in the

calculation of SSR, in particular relating to 8% primary

SSR and LDR SSR. On the other hand, the 2.5%

secondary SSR did not experience any change.

The primary SSR policy of 8%, at its foundation,

represents an adjustment of the current regulation

from 5% to 8%. This was implemented because the

banking sector continues to experience widespread

excess liquidity. The additional 3% in rupiah primary

SSR against bank»s third party rupiah deposits will

earn interest at 2.5%However, interest will not be

paid to banks holding primary statutory reserves

below 8%.

The LDR SSR in rupiah is set within a range that

is considered to encourage the bank intermediation

function and maintain prudential principles. The LDR

target range is set with a lower limit of 78% and an

upper limit of 100%. Banks with a loan to deposit ratio

that falls outside of this range will face disincentives as

follows:

Banks with a loan to deposit ratio below the lower

limit will face an additional 0.1 SSR from rupiah

deposits for each 1% short of the target.

Banks with a loan to deposit ratio exceeding the

upper limit and with CAR below 14% will face an

additional 0.2 SSR from rupiah deposits for each

1% short of the target.

Banks with a loan to deposit ratio in excess of the

upper limit but which maintain CAR of 14% or

above and will not face any disincentives.

It is not the first time that this form of LDR SSR

has been applied. In the final quarter of 2005, Bank

Indonesia promulgated a regulation regarding the

application of LDR SSR that remained effective until

2008. Nevertheless, there are a number of differences

between these two policies. The LDR SSR policy

implemented in 2005 only contained instruments that

provided banks with incentives to increase their LDR,

there were no mechanisms, however, to impose

disincentives should the loan to deposit ratio become

too high.

The new LDR SSR policy incorporates a target

range. If the loan to deposit ratio of a bank falls below

the target there is incentive to the bank in order to

increase its LDR. Conversely, if the loan to deposit ratio

of a bank exceeds the target an incentive is provided

that encourages the bank to pay attention to its liquidity

risk by adjusting LDR. Therefore, there is a self-

correction mechanism for the banks to optimize their

allocation of credit, which adheres to prudential

principles.

The LDR target is applied based on

macroeconomic and micro-banking objectives. In

macro terms, the LDR target is a reflection of the credit

required to bolster economic growth. In contrast,

regarding the micro objectives, the LDR target is applied

considering the banks» liquidity and LDR conditions.

Notwithstanding, banks are permitted to extend credit

in excess of the upper LDR limit as long as adequate

capital is maintained.

The impact of this policy is expected to beminimal

on the banks» credit interest rates. In addition to high

bank excess liquidity, the banks» interest rate spread is

also relatively high at 5%.

The amendment to the primary SSR will come

into effect on 1st November 2010, while the application

48


of LDR SSR will commence on 1stMarch 2011. A 2-

month transition period will be provided after the

introduction of the primary SSR, which will give the

banks time to adjust their liquidity portfolios in line

with the fasting month of Ramadan and Idul Fitri public

holiday. Additionally, bank liquidity will increase in

harmony with the rapid expansion planned for the

government account in the fourth quarter. Meanwhile,

a longer transition period will be provided for the LDR

SSR policy, which is expected to allow banks to adjust

their asset liability management in order to meet the

new policy requirement.

49


Indicators of Bank Liquidity ResilienceBox 2.2

Ideas have emerged since the global financial

crisis in 2008 to reconsider the coverage of risk

management applied by banks. Before the global

financial crisis bank risk management tended to focus

on aspects of credit risk and market risk. Meanwhile,

not much attention was given to liquidity risk because,

basically, exposure to liquidity risk was relatively low

and stable. By applying prudential liquidity

management, banks were able to overcome mismatch

issues through interbank borrowing. Consequently,

close correlation emerged between the liquidity of one

bank and that of another (interconnectedness).

High interconnectedness between banks

accelerates contagion among banks as a result of default

at one or more banks in the system. Such circumstances

were evident during the financial crisis in 2008, tight

market liquidity due to an increase in exposure to market

risk as well as widespread interconnectedness between

the banks accelerated contagion stemming from the

crisis. This could become permanent, which would

undermine bank performance, if not handled

immediately through central bank intervention.

By observing the behaviour of liquidity risk,

especially the systemic impacts, the Basel Committee

of Banking Supervision (BCBS) designed two indicators

of liquidity resilience consisting of quantitative

standards that provide a reference for bank liquidity

resilience. Accordingly, the two indicators of liquidity

resilience are as follows:

A.A.A.A.A. Liquidity Coverage Ratio (LCR), Liquidity Coverage Ratio (LCR), Liquidity Coverage Ratio (LCR), Liquidity Coverage Ratio (LCR), Liquidity Coverage Ratio (LCR), is an indicator of

short-term liquidity resilience, indicating the ability

of a bank»s liquid assets to cover the possibility of a

cash flow deficit due to an abnormal withdrawal

of liquidity (stress) for 30 days; and

B.B.B.B.B. Net Stable Funding Ratio (NSFR), Net Stable Funding Ratio (NSFR), Net Stable Funding Ratio (NSFR), Net Stable Funding Ratio (NSFR), Net Stable Funding Ratio (NSFR), is an indicator of

long-term liquidity resilience, indicating the stability

of bank funding to offset investment in several

financial assets of varied maturity.

Calculation tests of LCR using data from 14 large

banks in Indonesia indicate that the majority of banks

have a liquidity coverage ratio of less than 1. Therefore,

the liquid assets of banks available to meet the liquidity

requirement for 30 days under stress conditions in

Indonesia need to be improved. This is primarily because

banks in Indonesia, in general, apply an aggressive

liquidity management strategy and cover their liquidity

mismatch through interbank lending and borrowing.

This strategy is openly applied by banks during

conditions marked by low interest rates and stable

interbank interest rates. Nevertheless, this liquidity

management strategy has the potential to intensify

liquidity risk if interest rates climb.

Tests of long-term bank liquidity resilience

performed by calculating NSFR showed that the value

of NSFR of 14 large banks is above 100%, which

denotes sustainable long-term liquidity resilience. The

NSFR of several large banks, consisting of transactional

banks, achieved 300%. Therefore, in general, the 14

large banks tested have a funding structure that is

stable and can adequately cover liquidity risk

originating from a decline in asset value of up to

around 100%.

Box Figure 2.2.1Liquidity Coverage Ratio of Large Banks

2008 √ June 2010

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6

2008 2009 2010

Bank 1 Bank 2 Bank 3 Bank 4 Bank 5 Bank 6 Bank 7

Ratio

2.00

1.80

1.60

1.40

1.20

1.00

0.80

0.60

0.40

0.20

0.00

50


Box Figure 2.2.2Liquidity Coverage Ratio of Large Banks

2008 √ June 2010

Box Figure 2.2.4NSFR of Large Banks 2008 √ June 2010

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6

2008 2009 2010


Ratio

1.60

1.40

1.20

1.00

0.80

0.60

0.40

0.20

0.001 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6

2008 2009 2010


3.50

3.00

2.50

2.00

1.50

1.00

0.50

0.00

Ratio

Box Figure 2.2.3NSFR of Large Banks 2008 √ June 2010

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6

2008 2009 2010


Ratio4.00

3.50

3.00

2.50

2.00

1.50

1.00

0.50

0.00

51


Implementation of Operational Risk Capital ChargeBox 2.3

Congruent to the planned implementation of

Basel II, Bank Indonesia introduced the calculation of

risk-weighted assets (RWA) for the operational risk of

banks through Bank Indonesia Circular No. 11/3/DPNP

dated 27th January 2009 regarding the Calculation of

RWA for Operational Risk using the Basic Indicator

Approach (BIA). BIA is the simplest approach and does

not require any special requirements compared to

calculating operational risk using the Standardised

Approach or Advanced Measurement Approach

(AMA).

Bank RWA can be calculated using BIA through

the following formula:

Operational risk RWA = 12.5 x operational risk

capital charge

Where:

Operational risk capital charge is (positive)

average gross annual income for the past three years

multiplied by factor (alpha) of 15%.

In the calculationof the minimum capital

requirement, the portion of operational risk RWA has

the second largest contribution to total risk-weighted

assets after credit risk RWA (as presented in Figure

2.3.1). This suggests that applying this method to

calculate operational risk RWA places pressures on bank

capital.

Accordingly, the introduction of operational risk

capital charge for banks will be performed gradually

from 2010. In the calculation of operational risk capital

charge, factor (alpha) will be 5% from January 2010,

10% from July 2010 and then 15% from January 2011

onwards.

A simulation follows to investigate the impact of

operational risk RWA on bank capital (position as of

April 2010):

Based on the results of simulations, in general

the application of operation risk RWA will place

additional pressures on bank capital, including

reducing the value of bank CAR by 2.6% if the gross

income factor is multiplied by (alpha) 15%. Therefore,

intensive monitoring is required by supervisors, in

particular for banks with CAR just slightly above 8%

in order to prevent CAR dropping below the minimum

level when the basic indicator approach is applied fully

in 2011.

Box Figure 2.3.1Comparison of Bank RWA

10%

1%

89%

Credit Risk RWA

Market Risk RWA

Operational Risk RWA

April 2010 Position 17.56% 16.60% 15.74% 14.96% 1,540,284,185 89,319,743 178,639,485 267,959,227.81

Changes -0.96% 1.82% -2.60% 5.8% 11.6% 17.4

Box Table 2.3.1Operational Risk Simulation

CAR

Credit andMarket Risk

Oprisk(α =5%)

Oprisk(α =10%)

Oprisk(α =15%)

Credit andMarket Risk

Oprisk(α =5%)

Oprisk(α =10%)

Oprisk(α =15%)

RWA

52


Financial System Reform to Enhance Financial SectorResilience

Box 2.4

The global financial crisis made various countries,

including Indonesia, realise that financial sector resilience

requires strengthening through the implementation of

financial system reforms,. Although the financial system

in Indonesia is relatively strong compared to other

countries, Indonesia cannot remain silent in the global

financial reform process because robust, stable and

competitive economic growth requires a solid and

efficient financial and banking sector.

Primary Considerations for Financial System

Reform

Lessons learned from the global financial crisis

include the importance of macro-prudential and micro-

prudential integration when maintaining financial

system stability. The current financial system and

supporting infrastructure is unable to withstand a crisis

shock, therefore, several countries are introducing

reforms to their financial sectors. In general, the financial

reforms are based on three considerations, namely:

Include the task of maintaining financial system

stability, in particular related to handling systemic

impacts;

Include an integrated macro and micro-prudential

function; and

Include consumer protection.

Financial system reforms in a number of countries

generally involve providing greater authority to the

central bank in order to maintain financial system

stability and facilitate the supervision function of

financial institutions, as has occurred in Britain, France

and the United States. Greater authority for the central

bank does not merely imply the application of micro

supervision at the central bank or under coordination

with the central bank but also includes the central

banks as a systemic regulator. As an example, England

has transferred the bank supervision function from the

Financial Supervisory Authority (FSA) to the central bank

(Bank of England/BOE) in the form of a BOE subsidiary

tasked with supervising banks and non-bank financial

institutions. Meanwhile, in France the Prudential

Supervisory Authority was established in January 2010

at the central bank, responsible for the supervision of

financial institutions and insurance companies. This

authority is below the central bank (Banque de France/

BDF) in order to simplify coordination when conducting

micro and macro-prudential supervision. Likewise,

financial reform in the US, as detailed in the Obama

Plan, gives authority to the central bank as a systemic

regulator. The systemic regulator is responsible for

regulating all financial institutions that significantly

affect the financial system.

Box Figure 2.4.1Microprudential Supervision, Monetary Stability and Financial System Stability

MONETARY STABILITY(Macroprudential Supervision)

FINANCIALSYSTEM STABILITY

MicroprudentialSupervision

53


Financial System Reform in Indonesia

The 1997/98 crisis provoked widespread thinking

regarding the separation of bank supervision from Bank

Indonesia, which was realised through the

promulgation of article 34 in Act No. 23, 1999,

regarding Bank Indonesia amended by Act No. 6, 2009

(The BI Act). Article 34 stipulated that the task of

supervising banks will be the responsibility of an

independent supervisory institution in the financial

services sector, established no later than 31st December

2010. Financial system reforms are formulated by

reviewing the fundamental problems and issues faced

by the financial sector. In line with the current

conditions of Indonesia»s financial system, the basic

problem in the financial sector is sub-optimal efficiency.

The mandate of Article 34, which aimed to

improve supervision, avoided a conflict of interest with

monetary policy and included the supervision of

conglomerates in the financial sector. However, it is

critical to be aware that Article 34 of the BI Act is not

a final objective; there is another more important goal,

namely reinforcing financial sector resilience in the

future. Will the formation of a financial supervisory

authority in Indonesia resolve the problems of sub-

optimal efficiency in the financial sector? Referring to

the primary considerations of financial system reform,

the core problems faced by the financial sector cannot

be resolved merely through the establishment of a new

institution to supervise financial services activity. To

overcome this problem, the most appropriate efforts

should concentrate on institutional building in the

financial sector. Accordingly, the main priority of

institutional building in the financial sector is to

strengthen the function of authorities that play a role

in maintaining financial system stability. Institutional

building in terms of financial system reform covers three

aspects.

First is institutional building relating to all

processes and the formation of regulations in the

financial sector purposefully created to provide optimal

results for the national economy. To this end, optimal

regulations in the financial sector must refer to the

development level of financial transactions in the

economy and anticipate changes as well as other

developments that may occur looking ahead. In

addition, regulations in the financial sector principally

have to be in the interest of the owners of funds, not

only the financial institutions.

Second is institutional building in the supervision

process pursuant to prevailing regulations. The

supervision of financial practices, in addition to

enforcing existing regulations, is also intended to

guarantee financial system stability. In this category,

supervisory efforts require a shift in balance from a focus

on the old paradigm oriented towards compliance to

risk prevention measures. Balanced supervisory efforts

between compliance and risk prevention will produce

a more solid financial sector resilient to crisis pressures.

It was already proven during the 1997/8 crisis that points

of vulnerability are often not considered factors of risk

originating from new information.

Third is institutional building in terms of

developing and deepening the financial market.

Regulatory assurance as well as optimal financial sector

supervision open doors to financial market

development and deepening. Financial market

deepening is directed towards nurturing the

development of financial products and can

simultaneously be used by banks and financial

institutions as alternatives for fund distribution and

placement, productively to the real sector.

Other important considerations in the decision-

making process of financial system reform are the

principles of least social cost and maximum social

benefit. Least social cost implies that the reforms

implemented do not trigger any adverse impacts in

the economy. By comparison, maximum social benefit

implies propagating favourable consequences from the

reforms, for instance bolstering financial sector

resilience on top of adding value to measures taken to

enhance the progress, prosperity and welfare of the

community.

54


Looking ahead at the increasingly arduous

challenges faced, the best way to strengthen financial

sector reform is by reinforcing and synergising the task

implementation and goal achievement of authorities

in the financial sector. In this context, Bank Indonesia

as the central bank must underpin various

comprehensive policy instruments through a macro and

micro-prudential approach in order to issue policies that

are responsive to the individual needs of the financial

institution as well as preserve the soundness of the

financial system and monetary stability as a whole.

Accordingly, a key measure required in the financial

system reforms in Indonesia is the integration of macro

and micro-prudential supervision as an integral task of

Bank Indonesia in terms of monetary, payment system

and financial system stability under a framework of

achieving and maintaining rupiah exchange rate

stability.

Financial System Reform to Strengthen

Financial System Stability

Experience gleaned from the 2007/08 crisis in

countries that applied separate macro and micro-

prudential supervision indicated that central banks

without the authority to conduct micro-prudential

supervision suffered constraints in implementing their

role as lender of the last resort. This was because the

central bank did not have access to accurate

information in real time despite prevailing regulations

legislating the exchange of information among micro-

prudential supervisory institutions. Accordingly,

research by Nier (2009) found that during the global

crisis countries with central banks that had the

authority to supervise banks bore fewer economic costs

compared to those without. Therefore, it is important

to note that the government»s plan to reformat the

supervision system of financial institutions in Indonesia

by separating bank supervision from the central bank

will result in lost direct access to micro data. During

the global crisis, integrated macro and micro-

prudential supervision conducted by Bank Indonesia

was proven to detect potential crises in the financial

system, thus, the policy that was introduced

successfully minimized the impact of the global crisis

on the domestic economy.

Furthermore, the combination of macro and

micro-prudential supervision supported the function

of Bank Indonesia as lender of the last resort in order

to overcome emergency liquidity conditions at the

banks. Accurate, adequate and timely data and

information regarding the financial conditions of a bank

and the conditions of the financial system as a whole

provided Bank Indonesia with the possibility of

appropriately treating and, hence, minimizing the

negative effects that could appear from the policy

taken.

Article 34 of the BI Act should be implemented

with careful consideration so that the supervision of

financial institutions can be performed optimally and

contribute to the national economy. The urgency of

Article 34 implementation should be reconsidered

because it is already irrelevant considering that the

causes of the banking crisis in 1997/98 differ from

banking conditions today. Financial system reforms

must answer the current problems faced by Indonesia»s

inefficient financial sector and lessons should be learned

from the experience of other countries that have

reformed their financial system. Nevertheless, if a

financial supervisory authority is formed, Bank

Indonesia in principle supports these efforts to

strengthen financial sector resilience as one aspect of

financial system reform. However, it is important that

financial system reform can provide optimal results for

the financial system of Indonesia; accordingly there are

at least four aspects that need to be monitored:

The benefits of institutional building in the financial

sector are intangible in the short term because it

involves more than just institutional aspects; it also

incorporates aspects of human resources as well

as methods of support.

55


The implementation of Article 34 must be

synergised with current problems in the global and

national economies.

The application of least social cost and maximum

social benefit is necessary in the reformation of

financial institute supervision in order to achieve

optimal results.

The trend in several parts of the world that tends

to return the bank supervisory function to the

central bank in order to strengthen the macro-

prudential supervision function under a framework

of maintaining financial system stability.

56


Impact of PSAK 55 (2006 revision) Implementation onBanking in Indonesia

Box 2.5

In line with G-20 commitment to ensure the

convergence of global accountancy standards, the

Financial Accountancy Standards Board of the

Indonesian Institute of Accountants (DSAK-IAI) has

committed to converge financial accountancy standards

in Indonesia with the International Financial Reporting

Standards (IFRS). The application of IFRS is expected to

enhance the quality of financial accountancy standards,

improve the credibility and usefulness of financial

reports by ameliorating their comparability, as well as

concomitantly reducing the cost of compiling financial

reports because the accountants can present their

financial statements based on a unified global

accountancy standard.

The target of IFRS convergence in 2012 is a

revision of the Financial Accountaning Standards (PSAK)

so that the material is congruous with version 1 of

IFRS dated 1st January 2009 and will be applied for the

compilation of financial statements commencing 1st

January 2012. IFRS convergence began with the

compilation of PSAK 55 (2006 revision) regarding

Financial Instruments: Recognition and Measurement

as well as PSAK 50 (2006 revision) concerning Financial

Instruments: Presentation and Disclosure, which refer

to International Accountancy Standard (IAS) 39 and

IAS 32. These two standards are viewed as the most

complex standards and substantially alter the view and

mechanism of recording bank business activity. The

implementation of PSAK 55 and 50 also requires

refinement in terms of information technology, human

resources, policy/standard operating procedure, and

various other infrastructure deemed necessary.

Initially, PSAK 50/55 was applied to financial

statements commencing 1st January 2009.

Nevertheless, several constraints were faced when

compiling the financial statement, therefore, DSAK-

IAI decided to postpone the introduction of PSAK 50

(2006 revision) and PSAK 55 (2006 revision) to 1st

January 2010 pursuant to No.1705/DSAK/IAI/XII/2008.

As an entity with a balance sheet dominated by

financial assets and financial liabilities, the

implementation of PSAK 55 and 50 will have a

significant impact on the banks compared to other

reporting entities with a balance sheet structure not

dominated by financial instruments.

One of the challenges facing banks in the

implementation of PSAK 55 is inadequate historical

data to calculate collective impairment. Therefore, Bank

Indonesia together with DSAK-IAI and the Board of

Professional Public Accountants provide a special

transition period. For banks that do not have sufficient

historical loss data and have not yet estimated their

collective impairment, the calculation of collective

impairment can refer to the formation of general

reserves and special reserves as legislated by the Bank

Indonesia regulation regarding Evaluating Asset Quality

for Commercial Banks up to 31st December 2011. A

bank with no limitations must still apply the calculation

of collective impairment pursuant to PSAK 55.

Another challenge faced is the significant

change based on the method to measure and clarify

financial instruments, which affects their handling by

the bank. Financial instrument classification will be

measured by Fair Price through the Profit/loss

Statement, which previously only applied to securities,

but will now be applicable to all financial instruments

including credit.

The banks also face challenges regarding credit,

which is a significant financial instrument for the banks.

There is a distinct possibility that credit will be included

in the loans and receivables category measured by

amortised cost. To this end, banks must readjust their

57


measurement from previously based on a credit ceiling

to currently based on amortised cost.

In addition, the presentation of financial

statements in accordance with IFRS has not fully

adopted the importance of prudential banking. As an

example, the impairment concept in accounting is

based more on incurred loss, where the new entity

reports loss in the face of objective evidence of

impairment of financial assets that effectuates a change

in projected cash flow. The reserves are the difference

between initial estimate cash flow and estimated cash

flow after there is objective evidence of impairment.

Meanwhile, according to prudential banking principles,

reserves are based on incurred loss and expected loss,

hence, bank capital is expected to cover any potential

losses that occur. To overcome this problem the

calculation of reserves congruous with prevailing Bank

Indonesia regulations will be used in the context of

calculating capital, while the banks» financial

statements will be presented calculating reserves

according to PSAK.

In order to monitor the preparedness of banks in

terms of PSAK 55 application, Bank Indonesia has

requested the banks to submit an action plan covering

aspects of human resources, system and process.

Additionally, Bank Indonesia has also conducted on-

site visits to several banks to monitor directly the

preparations made by the banks.

58



59

Chapter 3 Financial Infrastructure and Risk Mitigation

Chapter 3Financial Infrastructureand Risk Mitigation

60



61


3.1. PAYMENT SYSTEM PERFORMANCE

Up to semester I-2010, the value of non-cash

transactions in the payment system was dominated by real-

time gross settlement transactions (BI-RTGS) accounting

for 93%. The types of transactions settled through BI-RTGS

include interbank money market transactions, fund

transfers from the trade of securities, rupiah currency

transactions, fund settlements from monetary operations/

open market operations, government transactions, and

settlement of the clearing system. The high value of

transactions settled through BI-RTGS demonstrates its

significant role in the national payment system, hence, BI-

RTGS is categorised as a systemically important payment

system (SIPS).

In terms of transaction volume, the greatest volume/

frequency of non-cash transactions in the payment system

up to the end of semester I-2010 originated from card-

based payment instruments, consisting of credit cards, ATM

cards and ATM/debit cards, accounting for 95% of total

transaction volume.

The payment system remained secure and was operated without any

disruptions during semester I-2010, which underpinned financial and monetary

stability and ultimately contributed positively to economic activity. In support

of financial stability, a number of measures were implemented to mitigate

settlement risk as well as operational risk in the form of policies and regulations,

system development and the application of operational procedures.

Figure 3.1Nominal Transaction Value (in billions of rupiah)

Figure 3.2Transaction Volume (in thousands of rupiah)

86.0%

88.0%

90.0%

92.0%

94.0%

96.0%

98.0%

100.0%


National Clearing System Card-Based Payment InstrumentsRTGS

National Clearing System Card-Based Payment InstrumentsRTGS


0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%

Financial Infrastructure and Risk MitigationChapter 3

62


BI-RTGS system liquidity remained adequately loose

during the reporting semester as reflected by the liquidity

usage indicator1 and turnover ratio2. During semester I-

2010 the liquidity usage indicator was in the range of 30-

35%, which denotes that there was sufficient liquidity in

the BI-RTGS system to settle transactions. Furthermore,

the turnover ratio was 1.45 on average for the semester,

which generally indicated the preference of banks to rely

on incoming transfers from other banks.

One bank took advantage of the intraday liquidity

facility (FLI-RTGS) during semester I-2010. The availability

of an intraday liquidity facility is in line with the risk

mitigation measures introduced by BI to mitigate temporary

bank funding shortages during the operational hours of

the BI-RTGS system in order to avoid gridlock.

3.1.3. Bank Indonesia Scripless Securities

Settlement System (BI-SSSS)

Transactions

Total value and volume of transactions on the BI-

SSSS during the reporting semester amounted to Rp6,700

trillion and 60,800 transactions respectively. This indicates

growth of 31.4% and 11.7% when compared to the same

period of the previous year (yoy).

3.1.1. Bank Indonesia Real-Time Gross Settlement

System

Transactions

Up to the end of semester I-2010, total value and

volume of transactions settled through the BI-RTGS system

achieved Rp25.30 trillion and 6.4 million transactions

respectively. When compared to the same period of the

previous year (yoy), nominal value and transaction volume

experienced a respective increase of 19.3% and 21.4%.

This increase was primarily due to additional transactions

for monetary management as well as customer transactions,

which grew by 118.1% and 25.6% respectively.

Figure 3.3BI-RTGS System Transactions

3.1.2. Operational Activity and Liquidity

Management

The BI-RTGS system performed well throughout

semester I-2010 as a whole with more than 99% of

transactions settled. Similar to the previous semester the

most common disruptions were in the form of network

communication disruptions in addition to system

application and hardware issues. Nevertheless, operational

risk was successfully mitigated through the Business

Continuity Plan (BCP)/Disaster Recovery Plan (DRP), which

periodically initiates system-wide testing on Saturdays and

Sundays as well as the use of DRP infrastructure for work

day activities (live).

1 Indicator of liquidity tightness in the system ranging from 0 √ 1, where a value closer to1 indicates tighter liquidity in the system.

2 Turnover ratio is a comparison between outgoing transactions settled through a bank»saccount balance at the beginning of the day. A high turnover ratio indicates that themajority of banks wait for incoming transfers from other banks to pay off their liabilitiesinstead of using their own capital.

0

200

400

600

800

1,000

1,200

1,400

0

1,000

2,000

3,000

4,000

5,000

6,000Value (trillion Rp)Volume (thousand)


Value Volume

Figure 3.4BI-SSSS Transactions

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000Nominal (trillion Rp.)Vol


-

200

400

600

800

1,000

1,200

1,400

1,600

Value Volume

63


3.1.4. Bank Indonesia National Clearing System

(BI-NCS)

Transactions

Total value and volume of transactions processed

through the BI-NCS during the reporting semester

amounted to Rp831.4 trillion and 43.2 million transactions

respectively, which indicates growth of 11.1% and 8%

when compared to the same period of the previous year

(yoy).

Operational Activity and Liquidity Management

Similar to the BI-RTGS system, the performance of

BI-NCS up to the end of semester I-2010 was secure with

no disruptions, as was the case in the previous semester.

During semester I-2010 there was adequate liquidity in

the national clearing system, as reflected by the availability

of a prefund (cash or collateral) as a precondition applicable

to all banks using the clearing system.

3.1.5. ATM and ATM/Debit Cards

The value and volume of ATM and ATM/debit card-

based transactions during the reporting semester totalled

Rp919.4 trillion and 838 million transactions respectively.

This represents an increase of 2.4% and 16.1% compared

to the same period of the previous year (yoy).

Figure 3.6ATM/Debit Card Transactions

-

20

40

60

80

100

120

140

160

180

-

20

40

60

80

100

120

140

160

180

Value Volume

2009 2010Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun

Nilai (trillion Rp) Volume (million)

3.1.6. The Credit Card Industry

Total value and volume of credit card transactions

during the reporting semester amounted to Rp76.9 trillion

and 96 million transactions respectively. This indicates

growth of 22.1% and 9.4% when compared to the same

period of the previous year (yoy). Such positive growth in

credit card transactions continued the upward trend

Figure 3.5BI-NCS Transactions

Value (trillion Rp) Volume (thousand)


0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

Value Volume

Figure 3.7Credit Card Transactions

-

2

4

6

8

10

12

14

16

-

2

4

6

8

10

12

14

16

18

20Value (trillion Rp)Volume (million)


Value Volume

Figure 3.8E-Money Transactions

-

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000


Value (million Rp)Volume

-

500,000

1,000,000

1,500,000

2,000,000

2,500,000

Value Volume

64


Industry Dynamic Authentication Engine as an alternative

form of security for credit card transactions using the card-

not-present mechanism for internet, e-commerce, mail

order and telephone order transactions. In addition, in

order to enhance the security of credit card transactions

and prevent fraud, CCAI are conducting trials of a neural

technology as a fraud detection system that can detect

abnormal behaviour.

In order to boost the efficiency of card-based

payment instruments, a number of reviews and persuasive

measures are currently being implemented relating to

interoperability and standardising instruments among

administrators of ATM cards and e-money. Particularly for

ATM/debit cards, chip and PIN technology is currently being

implemented.

To maintain a stable, efficient and reliable financial

system in the ASEAN region, ministers of finance and

central bank governors in the region have agreed to the

creation of the ASEAN Economic Community. One point

of agreement is the formation of a Working Committee

on ASEAN Payment and Settlements (WC-PSS). This

working group will operate for two years from April 2010

to March 2012. A representative from Bank Indonesia has

been appointed Chairman of WC-PSS with a Co-chairman

from the Bank of Thailand. The preliminary step of the

work program of WC-PSS is to conduct reviews and suggest

recommendations to develop, coordinate and harmonise

payment and settlement systems in the ASEAN region.

In terms of improving government payment services,

ISO 9001:2008 has been implemented in order to enhance

the quality management system.

3.1.9. Business Continuity Plan

To guarantee the smooth operation of the payment

system, IT devices at the DRC site were calibrated and

tested during semester I-2010. From 7-18th June 2010

reported in semester II-2009 and is congruent to the

aggressive marketing strategy followed by credit card

issuers, which ultimately leads to increase customer

transactions

3.1.7. Electronic Money

Up to the end of the reporting period, total value

and volume of electronic money transactions amounted

to Rp336.9 million and 12 million transactions respectively.

This indicates expansive growth of 88.7% and 114.1%

when compared to the same period of the previous year

(yoy). Similar to the credit card industry, such substantial

growth is the result of an aggressive marketing strategy

by the issuers of electronic money.

3.1.8. Payment System Development and Risk

Mitigation

Observing fund transactions/transfers, which have

experienced a persistent upward trend from year to year

in line with economic growth and the emergence of new

financial instruments and products, Bank Indonesia

consistently applies policies that aim to ensure a secure,

smooth and efficient payment system and which adhere

to aspects of consumer protection.

Referring to the efficiency and risk mitigation of

foreign exchange transactions, on 9th July 2010 the USD/

IDR Payment versus Payment (PVP) mechanism was

officially launched between the BI-RTGS system and the

RTGS system in Hong Kong. The benefits of this system

include minimising foreign exchange settlement risk and

supporting risk management as well as the management

of capital and liquidity. Bank Indonesia also introduced a

number of measures and coordination with relevant

stakeholders to develop the payment system, including

the Credit Card Association of Indonesia (CCAI). Currently,

efforts are underway to encourage use of the Collective

65


payment system operational activities were performed live

using IT and the DRC site. Critical payment system

applications involved in these activities included BI-RTGS,

BI-SSSS and BI-NCS. In general, all operational activities

associated with the calibration and testing were

successfully completed without any significant

disruptions. In conclusion, the back-up infrastructure at

DRC is reliable and can guarantee the continuity of the

payment system.

3.2. CREDIT BUREAU

The formation of the Credit Information Bureau (CIB)

is part of Pilar V of the Indonesian Banking Architecture

(IBA), namely to strengthen infrastructure in order to create

a sound, robust and efficient banking system. The

embryonic form of CIB was established in 1975 through

management of the Credit Information System (CIS). CIS

management has continued to develop into its current

iteration as the Debtor Information System (DIS), which

manages debtor data from financial institutions (bank and

non-bank) through a web-based system. Therefore, data

reports are submitted online and information can be

accessed online in real-time.

The main product of the DIS is Individual Debtor

Information (IDI), which is a historical track record of debtor

quality for the past 24 months. Among financial

institutions, this DIS product is known as Historical IDI or

BI Checking. Financial institutions primarily use the

information contained in historical IDI to evaluate potential

debtors applying for the financing facilities available. The

utilisation of historical IDI continues to experience

significant developments. In the past three years demand

for historical IDI has increased on average by 38% annually,

which illustrates that financial institutions are becoming

more aware of the importance of the information

contained within historical IDI.

Membership of DIS is reciprocal, where only financial

institutions that submit a debtor report to Bank Indonesia

are permitted to access historical IDI data. Currently, there

are 1,058 financial institutions that report to DIS, consisting

of 121 commercial banks, 927 rural banks, and 10 non-

bank financial institutions (NBFI). Based on type of

membership, DIS membership is split into two categories,

namely obligatory and voluntary. Obligatory members

include commercial banks, rural banks with assets totalling

Rp10 billion for six consecutive months, and credit card

companies. In contrast, voluntary members include rural

banks not meeting the requirements for obligatory

members, NBFI, as well as savings and loans cooperatives.

Table 3.1Demand for Historical IDI

December 2008 2,050,957 1,833,158 206,255 10,915 30%December 2009 2,667,770 2,523,105 102,141 41,864 46%July 2010 3,900,728 3,698,402 144,754 56,930 1,232,958 46%

TotalPeriod CommercialBank

PercentageRuralBank

FinanceCompanies

Growth

Based on the profile of DIS members, it can be seen

that not all financial institutions that provide incorporated

funding services are DIS members. On the other hand,

there remains the requirement to create more

comprehensive data to support the process of analysing

prospective debtors. To overcome this problem Bank

Indonesia is working with the Indonesia Capital Market

and Financial Institution Supervisory Agency (Bapepam-

Table 3.2Profile of DIS Members

1. Commercial Bank 121 Compulsory2. Rural Bank 927 Compulsory & Voluntary3. Non-bank Credit Card

Issuers 1 Compulsory4. Finance Companies 9 Voluntary

TotalTotalTotalTotalTotal 1,0581,0581,0581,0581,058

No Type ofMembership

Financial Institution TotalDIS Members

66


LK), as the authority ofNBFIs, to improve the scope of data

originating from NBFIs in order to utilize historical IDI

integrated with DIS. This was undertakenconsidering that,

hitherto, NBFI membership is voluntary.

Broadening the scope of DIS members and data is

one important part of CIB development. This is based on

the consideration that comprehensive DIS data will

enhance the accuracy of credit analysis by financial

institutions. The development process implemented by CIB

aims at international standards of credit bureau

management in Indonesia, among others, enhancing data

accuracy and system performance.

3.2.1. Role and Development of Credit

Information Bureau

The establishment and development of CIB in

Indonesia is designed to support the function of BI as the

monetary and banking authority, as well as reinforce

financial system infrastructure in Indonesia under a

framework of minimising asymmetric information between

institutions supplying funds and the beneficiaries.

As one form of infrastructure in the analysis of the

provision of funds, CIB has an important role in supporting

economic growth in Indonesia. The debtor data and

information made available by CIB can assist financial

institutions to preliminary analyse the quality and reputation

of a potential borrower. Subsequently, based on this quality

and reputation the financial institution can determine the

amount of collateral required or the appropriate interest

rate to be applied. Such conditions will make it easier for

quality prospective borrowers to obtain loans from financial

institutions because a good credit reputation is another

form of collateral (reputational collateral) other than

conventional collateral, and determines risk-based pricing.

Simplifying the management and evaluation of

potential debtors will enhance the efficacy of risk

management for financial institutions and lower the level

of non-performing loans. Accordingly, the bank

intermediation function will improve and create a sound

and efficient credit system climate, and economic growth

will be achieved with the support of a solid and stable

financial system.

To create aCIB that adheres to international

standards, gradual development is required of CIB

management, including the scope and quality of data,

products and services, technology as well as regulations.

Successful CIB development will lead to the availability of

more comprehensive data, unified outputs or products as

well as information technology that supports CIB

operational activities.

The scope of data stored by CIB at the initial stage

will be expanded for non-bank financial institutions (for

which membership is still voluntary). Looking ahead, the

scope of data will be extended to include public utilities»

data (Telkom, PLN and PDAM). In terms of products and

services, CIB is expected in the future to support the

availability of additional products in order to bolster the

operational business of the financial industry and to assist

the task and function of BI in terms of maintaining financial

system stability.

Figure 3.9The Role of CIB

ECONOMIC GROWTH

Macro

Micro

Financial SystemStability

Increase of IntermediationFunction

Low NPL

Risk ManagementEfectivity

Risk-Based Pricing

Reputational Collateral

67


IT infrastructure requires further development in

order to support CIB operations considering the ever

increasing amount of data stored from financial institutions

as well as to expedite the services offered to end users.

3.2.2. Development Stages

In the development of CIB there are two stages

outlined. The first stage includes preparations for follow-

up development processes, followed by the second stage,

which is the process of developing CIB as a whole.

Preparations in the preliminary stage consist of improving

the DIS and the debtor data submitted; therefore, in the

second stage the quality of debtor data contained within

the DIS is of higher quality and can be integrated with the

new system.

Development in the first stage will focus on improving

data accuracy as well as system performance, and several

features to support the financial industry»s requirements.

Improving data accuracy and system performance is the

main focus because of the need to analyse debtor data

with higher data quality, as well as simpler and faster

access. This initial development stage will be achieved by

creating and optimizing DIS applications that have so far

been used to support CIB operations, as well as refining

the applications used to improve data quality. Other efforts

implemented by Bank Indonesia include improving

supervision and the inspection of DIS report data submitted

by financial institutions as well as enhancing the service of

the DIS help desk.

The second stage of CIB development will commence

following the satisfactory completion of the initial

development stage and includes significant changes in

support of industry requirements. The creation of a credit

bureau industry in Indonesia that can manage data from

various institutions as well as manage the creation of useful

products is expected from the second stage of

development.

3.2.3. Public»s Role in the Credit System

The achievement of a sound and efficient credit

system does not only depend upon the development of

CIB and the awareness of data providers in their reporting,

the public must also be aware of the importance of

maintaining its credit reputation. Through the knowledge

that their credit history will be recorded at CIB and can be

accessed by all participating financial institutions,

borrowers are expected to maintain their credit reputation

(one way is through the timely repayment of instalments).

A number of measures have been taken to raise

public awareness regarding the presence of CIB, among

others, through socialisation activities consisting of

seminars in various regions, as well as public education

through advertorials in the national mass media. The

impact of which has been an increase in demand for

historical IDI data through the help desk at Bank Indonesia

from the public. This is positive for the future development

of CIB because greater public access to DIS output will

boost demand to raise data quality in debtor information.

68


The liberalisation of financial services can greatly

benefit a country, however, conversely it can also have

a number of adverse effects. It depends on the level of

economic development and the preparedness of the

country to embrace trade liberalisation. Indonesia, as

a member of liberalisation forums such as WTO and

other liberalisation forums, negotiates bilaterally and

multilaterally with other countries in the interest of

Indonesia. Accordingly, Bank Indonesia actively and

routinely participates in several liberalisation and

negotiation forums in order to safeguard the interest

of the banking sub-sector in Indonesia.

The meetings and negotiations to which

Indonesia attends include the following:

World Trade Organisation (WTO): is one

organisation that has experienced development

negotiations through many rounds. One important

development is the inclusion of the services sector into

the General Agreement on Trade in Services as a part

of the core negotiations pioneered at the Uruguay

Round. The Doha Development Agenda (DDA) was

agreed as a new reference point to rescue trade

negotiations, which have been in a vacuum for a while,

as important momentum for the development of the

WTO.

ASEAN Framework Agreement on Services

(AFAS) under the ASEAN Economic Community (refer

to Box 3.2).

Free Trade Area (FTA) √ Agreement is a preferential

agreement in its position with respect to the WTO,

aimed at overcoming a number of constraints including

tariffs and non-tariffs for all countries or a specific few.

FTAs can be arranged bilaterally or regionally. In the

context of trade in services, the legality of bilateral and

regional FTAs is recognised by the WTO through Article

V GATS. In the process of liberalisation negotiations

through various FTA forums attended by Indonesia,

particularly for the services sector, the structure and

modalities used are set forth in WTO GATS because

the structure adopted in WTO GATS provides ample

space, especially for developing countries, to prepare

each sector before ultimately implementing full

liberalisation (progressive liberalisation).

Asia Pacific Economic Cooperation (APEC), with

21 member countries in Asia/Pacific, APEC discusses

three main pillars, namely Trade and Investment

Liberalization, Business Facilitation as well as Economic

and Technical Cooperation. Nevertheless, there are

many fundamental differences between APEC, the

WTO and FTAs in general, primarily that APEC is

voluntary and non-binding while the WTO and FTAs

are legally binding.

General Agreement on Trade in Services (GATS)

WTO is one product that emerged from negotiations

at the Uruguay Round, which has become an integral

part of multilateral agreements under the WTO. Its

position is parallel with the General Agreement on

Tariffs and Trade (GATT). GATS aims to bolster trade

in services between each member state by increasing

transparency and assurance based on progressive

liberalization. The banking sub-sector has been

classified into Financial Services-GATS. Four modes of

supply are under GATS:

Mode 1: Cross-border trade. This is equivalent

to cross-border trade in the goods sector, where

physical presence is not required in order to offer or

provide certain services to consumers outside the

territory of the service providers. The rapid

development of information technology is driving this

mode.

Mode 2: Consumption abroad. Can be

interpreted as service users who are outside of their

own countries» borders. A simple example is that of

foreign students studying abroad.

Overview of Liberalisation Forums Participated by IndonesiaBox 3.1

69


Mode 3: Commercial Presence. This mode refers

to the establishment or setting up of an office or

business outside the borders of the originating country.

Mode 4: Movement of natural persons (MNP).

Through this mode the delivery of services is possible

by individuals who directly visit the export destination

country. Related to the commitment to use foreign

workers, as noted in the general conditions, the

banking sub-sector of Bank Indonesia is only committed

to foreign workers at a managerial level with the

condition that they must have already understudied

the position to be filled. Indonesia is not bound by the

modality of employment, except under horizontal

commitments that refer to labour laws.

The banking sector, as part of the overall services

sector, is effectively opened by trade liberalisation

between Indonesia and its trading partners, through

multilateral WTO forums and in the smaller context of

regional FTA or bilateral cooperation. In principle,

commitment garnered at the WTO forum is a basic

reference point for all other cooperation agreements

(for instance FTAs), which in general are characterised

by GATS plus. Put simply, the basic logic for GATS plus

is that it makes sense if agreements signed outside of

the WTO have more liberal commitments.If not then

the states involved no longer need to sign agreements

outside of the WTO and it would be sufficient to use

WTO-based commitments.

Banking sub-sector commitment under the

framework of services sector liberalisation is divided

among several positions, namely:

Foreign Equity Participation (FEP)

The limitation of FEP for the banking sub-sector

in Indonesia, as detailed in the schedule of specific

commitment for the GATS-WTO forum, stipulates that

the acquisition of a local bank through stock purchases

on the capital market is no more than 51%.

Scope of Geographical Area for Foreign Bank

Branches» Operations

The geographic area for a foreign bank branch

and joint venture bank is only in 11 large Indonesian

cities(Jakarta, Surabaya, Semarang, Bandung, Medan,

Makasar, Denpasar, Batam, Padang, Manado and

Ambon). There are three additional cities included in

the ASEAN - Australia & New Zealand (AANZ) √ FTA

and AK - FTA (Balikpapan, Banda Aceh andJayapura).

Meanwhile, the total number of offices is very limited

(2 sub-branches and 2 auxiliary offices) for foreign bank

branches and joint venture banks.

70


Overview of ASEAN Economic Community (AEC)Box 3.2

AEC Background

The ASEAN Economic Community (AEC) began

with a concept first conceived in Bali at the Declaration

of ASEAN Concord II in 2003. In general, AEC aspires

to the realisation of economic integration among

ASEAN countries in 2020 pursuant to Vision 2020.

However, The Cebu Declaration, announced at the

beginning of 2007 at the 12th ASEAN Summit

expedited the formation of AEC to 2015 by

strengthening the competitiveness of ASEAN against

global competition, in particular China and India.

AEC is established based on a strategic

framework to achieve a common market and unified

production base, a competitive economic region, as

well as balanced economic growth integrated with the

global economy. With the formation of AEC, in addition

to strengthening the international negotiating position

of ASEAN, competitiveness will also increase, thus

contributing positively to ASEAN as a whole as well as

individual member states including Cambodia, Laos,

Myanmar and Vietnam, often referred to in the context

of ASEAN as CLMV.

Services Sector Blueprint

The free flow of services is an important element

in the establishment of ASEAN as a common market

and unified production base as set forth in the goals

of AEC 2015. The AEC blueprint for service sector

liberalisation is designed to remove barriers to the

supply of services and the establishment of new service

businesses in the ASEAN region. Liberalisation will be

achieved through negotiation mechanisms like the

ASEAN Framework of Agreement on Services (AFAS).

Through this processall member states are prohibited

from withdrawing previous commitments (as well as

in WTO) and pre-agreed flexibilities are determined,

namely the disclosure of issues that have the potential

to become commitments for liberalisation and cannot

be changed, for instance prevailing regulations and

prudential principles.

A number of measures and strategic targets are

detailed in the blueprint for the services sector, AEC

2015, in order to drive the liberalisation process in

realising the free flow of services in the region in 2015.

Each stage of liberalisation gradually opens up market

access by loosening regulations legislating foreign

ownership of stock in four priority sectors up to 51%

in 2008 and then to 70% in 2010.

The liberalisation of services is conducted in three

steps, namely first to inventory barriers to trade in

services in 2008. Subsequently, up to 2009, establish

liberalisation parameters for the four modes, and

limitations on horizontal commitments and national

treatment for each negotiation round. Then, from

2010 until 2015, hold discussions/negotiations based

on the parameters previously set.

Several Prevailing Principles

Taking into consideration the differing

characteristics of ASEAN countries and relating to

prudential regulations and balance of payments

safeguards, the liberalisation of financial services is

separate from other services sectors with the following

principles:

Liberalisation uses the formula ASEAN minus x,

which allows countries that are prepared to

liberalise early with the remaining countries

catching up when they are ready.

The liberalisation process is implemented taking

into account national interests and the level of

economic and financial sector development in each

member state.

71


Subsectors to be Liberalised

In general, ASEAN has agreed to liberalise the

financial services sector by 2015, incorporating the

subsectors of insurance, the capital market and other

financial services. Nevertheless, each ASEAN member

state has a different liberalisation commitment

congruent to their level of economic preparedness and

the preference of each country involved. Currently,

Indonesia is only committed to two subsectors, namely

insurance and the capital market. The banking

subsector will be liberalised in 2020, with the exception

of CLMV, which will be liberalised in 2015.

ASEAN Framework Agreement on Services

(AFAS)

The negotiation process for the services sector is

unique compared to the goods sector. In the goods

sector, liberalisation is achieved through the removal

of tariff and non-tariff barriers. In contrast, negotiations

in the services sector focus on reducing barriers to the

four modes of supply.

In ASEAN, the liberalisation negotiation process

is achieved through the ASEAN Framework Agreement

on Services. This agreement was signed by ASEAN

economic ministers at KTT ASEAN V in Bangkok in

1995. The goal of AFAS is to enhance the efficiency

and competitiveness of the services industry by

diversifying production capacity, increasing the supply

and distribution of services among service providers,

intra and extra ASEAN, as well as removing barriers to

trade in services among members.

AFAS Principles

In the liberalisation of services, AFAS utilises the

principles applied by the WTO, namely: i) most favoured

nation: the facilities provided to one nation are

applicable to all other nations; ii) non-discriminative:

the constraints applied to all states; iii) transparency:

each member state is obliged to publish all rules and

regulations, implementation guidelines and decisions

issued by the central and local governments; and iv)

gradual liberalisation: in accordance with the economic

development level of each member nation.

According to AFAS, ASEAN members are

encouraged to provide a greater level of commitment

to all other member states compared to commitments

set forth in GATS-WTO and open up more sectors and

subsectors (commonly known as GATS plus).

Source: ASEAN Economic Community 2015:

Strengthening ASEAN Synergy amid Global

Competition (Sjamsul Arifin, Rizal A. Djaafara, Aida S.

Budiman).

72



73

Chapter 4 Indonesian Financial System Outlook

Chapter 4Indonesian FinancialSystem Outlook

74



75


4.1. ECONOMIC PROSPECTS AND RISK

PERCEPTION

Economic growth in Indonesia in the medium term

has the opportunity to accelerate. Such optimism stems

from robust growth in 2009 of 4.5% yoy and 6.2% in

quarter II-2010. Overall, the domestic economy is expected

to expand in the range of 6.0-6.3% in 2010. This

favourable achievement would not be possible without

well-maintained macroeconomic and financial system

stability.

Meanwhile, global economic growth is predicted at

around 4.6% in 2011. Nevertheless, this is a multispeed

economic recovery with the pace varying between

countries. Economic growth in emerging and developing

countries is expected to remain robust compared to

developed countries that are restrained by relatively languid

economic growth.

Figure 4.1Comparison of Economic Growth Projections

for several Country Groups

Table 4.1Economic Indicator Projections

GDP (% yoy) 4.5 6.0 - 6.3 6.0 - 6.5

Inflation (%. last periode) 2.78 5 ± 1 5 ± 1

2010*

* Bank Indonesia Projection

2009 2011*

The domestic economy is projected to expand in the

range of 6.0-6.5% in 2011 on the strength of better

fundamentals and a more conducive macroeconomic

environment. The most important fundamental factor is

investment growth, which has rebounded strongly since

the global economic crisis of 2008.

On the demand side, economic growth in 2011 will

be driven by investment activity, for which growth are

projected to exceed 10%, as well as solid household

consumption growth in the range of 5.0-5.5%. Externally,

exports are estimated to achieve growth in excess of 7%

on the basis of more conducive global economic conditions

and greater export competitiveness. In addition, imports

are expected to increase in concurrence with strong

domestic and export demand.

Nonetheless, the Indonesian economy remains beset

by a number of risks. Externally, risk factors stem from

uncertainty in the global economy regarding the pace and

strength of the global economic recovery process. There

are concerns that the global recovery may stutter due to

slow economic activity in US, China, Japan and problems

in the Euro zone.

Source: World Economic Outlook Update, IMF, July 2010

2010 20112009

World Growth Advanced Economies Emerging and DevelopingEconomies

ASEAN-5

8

6

4

2

0

-2

-4

Indonesian Financial System OutlookChapter 4

76


Domestically, the greatest challenge is how to

maintain national economic momentum far in excess of

the other countries mentioned.

Inflation in 2010 and 2011 is projected in the range

of 5%±1%. Slightly more intense inflationary pressures

are expected in 2010 triggered by high inflation of volatile

foods due to prolonged weather anomalies. In addition,

government policy to raise the basic electricity tariff will

also exacerbate inflationary pressures from administered

prices. For 2011, the increase in inflationary pressures will

be harmonious with rising inflation in trading partner

countries and global economic growth as a whole. In terms

of non-fundamental factors, inflationary pressures will

emerge from administered inflation due to a plethora of

information regarding the government»s policy of reducing

the difference between the selling price and actual

economic price of LPG and electricity.

Meanwhile, foreign investors consider Indonesia»s

prospects to be extremely promising, as reflected by

Moody»s upgrading Indonesia»s sovereign credit rating

outlook from stable to positive. Moody»s also upgraded

the foreign currency bond ceiling rating to Ba1 and the

foreign currency deposit ceiling to Ba3. In addition, several

months beforehand S&P upgraded its rating to BB/positive

and Fitch to BB+/stable.

A decline in credit default swap and bond yield spread

indicated an improvement in risk perception concerning

the Indonesian economy. The return on investment in

Indonesia remains high, coupled with well-maintained

macroeconomic fundamentals and financial system

stability, which is appealing to investors..2

Indo 27 Ba3 (Moody's) 7.389 594.09 594.56

Indo 31 Ba3 (Moody's) 7.949 567.41 522.83

Indo 50 Ba3 (Moody's) 9.246 608.93 537.47

Table 4.3Indonesian Risk Perception

Bond Rating Ytm (%)Yield Spread (bps)

Maret June2009 2009

Source: Bloomberg

Figure 4.2Credit Default Swap and Bond Yield Spread

Jan Apr2009 2010

Nov Dec Feb Mar May Jun Jul Aug Sep

10 Year Yield Spread Global Bond RI vs US T Notes (LHS)CDS Ind (RHS)

100

120

140

160

180

200

220

240

260

280

3007.0

6.5

6.0

5.5

5.0

4.5

4.0

Private Consumption 4.9 4.9 √ 5.2 5.0 √ 5.5

Government Consumption 15.7 4.2 √ 4.5 2.3 √ 2.8

Domestic Demand 3.3 9.9 √ 10.2 11.7 √ 12.2

Export of Goods and Services -9.7 13.4 √ 13.7 7.3 √ 7.8

Import of Goods and Services -15.0 17.9 √ 18.2 8.8 √ 9.3

Table 4.2Domestic Economic Growth according to Demand

2009

*) Bank Indonesia Projection

2010* 2011*

% yoy, base year 2000 % yoy, base year 2000 % yoy, base year 2000 % yoy, base year 2000 % yoy, base year 2000

77


4.2. BANK RISK PROFILE: LEVEL AND DIRECTION

The improvement in macro conditions, as indicated

by robust economic growth, widespread investor

confidence buoyed by a stable exchange rate, as well as

an upgrade in Indonesia»s debt rating, underpinned

financial system stability. According to the Financial

Stability Index (FSI), financial system resilience declined

from 1.91 (December 2009) to 1.87 (June 2010). Up to

August 2010, FSI had declined further to 1.84. Pressures

are expected to continue easing in the financial system

during semester II-2010 with FSI projected in the range

of 1.45-2.02 and a baseline of 1.74. The expectation of

low bank credit risk, as well as stable volatility in terms

of share prices and bond yield will contribute to the

alleviation of pressures in the financial system of

Indonesia.

Greater financial system stability will primarily be

supported by sound bank performance as reflected by

banking industry CAR of 17.4% in June 2010. By August

2010 CAR had declined slightly to 16.3% as a result of

the rise in risk-weighted assets used to calculate operational

risk since May 2010 in accordance with Basel II. However,

the level of CAR remains far in excess of the minimum

requirement, which denotes solid bank performance and

resilience.

The structure of the bank asset liability profile, for

which funds tend to be short term (less than 3 months),

helped control market risk pressures in line with the stable

interest rate trend during semester I-2010. However,

expectations of higher inflation approaching yearend will

potentially limit the opportunity to lower interest rates and

hence, compound interest rate risk pressures. On the other

hand, exchange rate risk pressures are low due to exchange

rate stability as well as low bank net open position (NoP)

exposure at just 3.1% (down from 4.1% in December 2009

and far below the upper limit of 20% of capital).

Bank liquidity risk management remains sound amid

the onset of rapid credit growth. Bank liquid assets up to

the end of Semester I-2010 declined by Rp2.5 trillion,

however, this is still within normal limits and, thus, does

not indicate any signs of liquidity pressures stemming from

excessive credit growth or a decline in deposits.

Improved bank liquidity management is also

evidenced by interest rates and transactions on the

interbank money market, which remained stable during

the reporting semester. Nevertheless, expeditious credit

growth compared to growth in deposits has the potential

to trigger liquidity pressures, especially amid the unresolved

global crisis, which requires closer monitoring.

Credit risk was well managed during the first

semester of 2010, which is indicated by low NPL supported

by a decline in total nominal non-performing loans amid

an improvement in domestic and global economic

conditions. Meanwhile, the expectations of more intense

inflationary pressures as well as fewer opportunities to

reduce interest rates towards the end of the year have the

potential to spark credit risk pressures in the second half

of 2010 despite remaining at a moderate level. The

relatively large amount of credit in the special mention

category (group 2), around Rp90.7 trillion as of June 2010,

requires attention due to the high likelihood of greater

credit allocation in the future. This confirms that credit

risk remains the main risk faced by banks, where stress

tests reveal several banks with low CAR.

4.3. POTENTIAL VULNERABILITIES

In general, financial system stability was well

maintained during semester I-2010 amid aglobal and

domestic economic recovery. Global financial pressures

stemming from the Greek debt crisis did not significantly

impact the domestic financial sector. Exchange rate

volatility was controlled, while conditions on the stock

78


market and bond market rebounded to bullish after

dramatic declines in February 2010. The stable domestic

financial sector and robust economy managed to withstand

pressures of a sudden reversal in short-term capital flows,

which peaked in May 2010. The outlook for Indonesia»s

financial sector up to yearend 2010 will remain stable

despite a slight increase in domestic inflationary pressures.

Against this backdrop, uncertainty remains regarding

the condition of financial systems in several countries in

the Euro zone, especially Ireland and Spain, as well as the

slow US recovery, which requires constant monitoring. This

is particularly pertinent due to the increased possibility of

a sudden reversal of foreign funds and bank liquidity risk

pressures amid uncertainty surrounding global financial

stability.

Meanwhile, credit growth is supported by

consumption credit while credit extended to the productive

sector is following a downward trend indicating a sub-

optimal business climate and the high-risk perception of

banks towards business activity. Notwithstanding, the

potential to extend credit to productive sectors remains

high. However, regarding a likely corresponding increase

in credit risk, the banks will have to continue heeding

prudential principles in the extension of credit to these

sectors.

As a mitigation measure against vulnerabilities in

the financial sector, a number of agendas emerged to

enhance bank resilience in semester I-2010, including

capital provisions against operational risk (size of reserves

based on a specified percentage of average gross income

for three years) pursuant to Basel II, as well as the

application of accounting standards PSAK No 50 and 55.

The other main agendas deal with banks looking forward,

including a transparent prime lending rate and the

application of LDR-SRR to enhance the prudent allocation

of credit.

Figure 4.3Bank Risk Profile and Future Direction

Market Risk Liquidity Risk Credit Risk Operational Risk

Inhe

rent

Ris

k

Hig

hM

oder

ate

Low

StrongAcceptableWeak StrongAcceptableWeak StrongAcceptableWeak StrongAcceptableWeak

ExchangeRate

InterestRate

GovernmentBond Price

79

Article I - Determinants of Capital Reserves at Indonesia’s Banks

Ar t ic les

80



81


Article I

Determinants of Capital Reserves at Indonesia’s Banks

Agustinus Prasetyantoko1, Wahyoe Soedarmono2

This paper investigates whether factors such as financial ratios, the business cycle and institutions affect

the capital reserves of banks in Indonesia. Monthly data is used in this research taken from the balance sheets

and financial statements of 99 commercial banks in Indonesia for the period 2004 √ 2007. In addition, this

research also demonstrates that the capital reserves of banks in Indonesia are procyclical. This is different if the

analysis is based on bank groups according to size and market discipline. The capital reserves of large and listed

banks are countercyclical. In other words such banks increase their capital reserves during periods of optimism

(economic booms) and decrease them during a recession. Therefore, a policy of small bank consolidation as well

as strengthening market discipline is recommended to support the application of Basel II, particularly in overcoming

the procyclical effect of statutory capital regulations. Furthermore, this research finds that the capital reserves of

Indonesian banks can be determined by the magnitude of non-interest income.

Keywords: bank, capital reserves, Basel II, procyclical effect, Indonesia

JEL: G21 G28

1. BACKGROUND

The minimum statutory capital reserve requirement

is an important regulation for banks in Indonesia. For the

past two decades, based on Basel I, commercial banks have

been obliged to maintain minimum statutory capital

reserves of 8% of total capital (Tier 1 and Tier 2). This

ratio is known as the capital adequacy ratio (CAR). The

regulation was initially designed to overcome the impact

of bank competition subsequent to financial deregulation

in the 1990s. However, commercial banks at that time

tended to violate the regulation and responded to

competition by extending credit to high-risk projects, where

most bad loans were found in the non-tradable sector, for

example real estate, property and construction. Although

capital reserves continued to erode due to excessive bad

loans, banks continued to operate and ultimately a financial

crisis was inevitable (Creed, 1999).

Not long after the financial crisis of 1997/98, Bank

Indonesia (BI) realised the threat of economic recession

and accordingly instituted policy to reduce the capital

adequacy ratio from 8% to 4%. Together with the

International Monetary Fund, the Government of Indonesia

introduced special bank supervision on the basis of prompt

1 Atma Jaya Catholic University, Jl. Sudirman 51, Jakarta, 12930, Indonesia,E-mail: [email protected]

2 Universite de Limoges, LAPE, 5 rue Felix Eboue, 87031 Limoges, France,E-mail: [email protected]

82


institutional variables, as well as bank type based on asset

size and market discipline.

This paper is divided into several sections. The second

section contains the literature review pertaining to capital

reserves. Section 3 explains the methodology and data

used in the empirical study. The fourth section discusses

the estimation results of the empirical study and the final

section is the conclusion and policy recommendations.

2. LITERATURE REVIEW

Through Basel II, banking regulators in several

countries have tried to achieve financial stability that

concomitantly stimulates economic growth. In the

achievement of financial stability, the capital adequacy ratio

is used as an indicator of bank soundness, where in Basel

II this ratio corresponds closely to bank risk. However, when

risk cannot be observed but must be predicted using the

standard method to estimate risk will return risk estimation

that are higher during an economic recession. Or,tighter

credit quality standards, in turn, prevent the economy

running risky projects except those that are socially

productive.

Under such circumstances, the requirement for the

capital adequacy ratio will appear higher. Therefore, in

meeting this requirement banks reduce the availability of

credit because the cost of raising equity is relatively

expensive. This type of behaviour has the potential to

deepen an economic recession and can also affect financial

stability. This is known as the procyclical effect of bank

capital.

There are at least two types of bank behaviour in

terms of controlling their capital. First, banks that are

backward looking will reduce their capital reserves (capital

buffer) during boom periods in order to increase credit

activity. Consequently, they fail to consider using their

capital reserves to cover credit risk and, therefore, they

are forced to increase capital reserves during a recession

corrective action. In parallel, the government also

established the Indonesian Bank Restructuring Agency

(IBRA) under the Department of Finance, which has

operated since September 1998. IBRA in collaboration with

BI is tasked with restructuring and supervising bank as well

as dividing commercial banks into three groups as

presented in Table 1. Banks in Category A have a capital

adequacy ratio of 4% or more. Banks in Category B (with

CAR between -25 and 4%) have the opportunity for

recapitalisation, and banks in Category C have a CAR of

below -25%. Banks in Category C are taken over by IBRA

unless they are able to deposit more capital.

At the end of 2001, the capital adequacy ratio was

restored to 8% on the consideration that bank conditions

had improved. At the beginning of 2004, BI reinforced

bank capital regulations, which became known as the

Indonesian Banking Architecture (IBA). IBA mandates a

minimum capital of Rp3 trillion to establish a new bank.

Meanwhile, existing banks must meet a minimum capital

requirement of Rp100 billion up to the end of 2010. In

order to strengthen IBA, BI applied new consolidation

legislation in June 2005, with commercial banks obliged

to maintain Rp8 billion in capital up to the end of 2007.

The strengthening of bank»s capital related

regulations demonstrate efforts by Bank Indonesia to

prepare for the implementation of Basel II. In Basel II, the

procyclical effect of bank capital is an important issue that

remains unresolved at the global level. In the context of

Indonesia, there has yet to be found research that analyse

the determinants of capital reserves; therefore, discussions

regarding the procyclical effect of capital reserves remain

untouched by academics and policymakers. This paper aims

to fill this gap, considering that the capital reserves of

Indonesian banks reached a level of 27.26% during the

period 2004 - 2007, when regulations only stipulated 8%

of total assets. This paper also extends the literature

regarding capital reserves and investigates regulatory and

83


(Borio et al., 2001). Secondly, forward-looking banks

anticipate an upcoming economic recession by increasing

their capital reserves during boom periods.

Ayuso et al. (2004) provided empirical evidence of

backward-looking bank behaviour in Spain by

demonstrating that bank capital is procyclical. Lokipii and

Milne (2008) found similar results where the capital reserves

of European banks were procyclical during the period from

1997 to 2004.

Conversely, some research has indicated that the

capital ratio might be countercyclical. This is because

forward-looking banks will anticipate economic recessions

by using boom periods to increase profits but also

ameliorate capital reserves to avoid larger losses during a

recession (Rajan 1994; Borio et al 2001). Berger and Udell

(2004) argued that the capital ratio could be countercyclical

due to balance sheet performance during an economic

boom.

In parallel, research has analysed determinants of

capital reserves in addition to analysing issues of

procyclicality. Clear predictions relate to the size of the

bank. Consensus has been reached that large banks tend

to maintain a lower capital ratio than small banks due to

the characteristic of being too big to fail (TBTF) (Kane 2000;

Mishkin 2006). In addition to TBTF, large banks have

comparative advantage in terms of overcoming

information problems by redoubling monitoring efforts,

which encourages them to balance the cost of supervision

with the cost of equity. In turn large banks reduce the cost

of equity by decreasing capital reserves.

Meanwhile, Berger (1995) confirmed that banks

could reserve capital to exploit unexpected investment

opportunities. This argument is congruous with Palia and

Porter (2004), where the capital ratio is used by banks to

reinforce their market value. Schaeck and Cihak (2007)

also found that banks tend to increase their capital ratio

when they are operating in a more competitive market. In

this context the capital ratio is a signal used by banks to

receive a sound evaluation from the market. Additionally,

Nier and Baumann (2006) explicitly confirmed the

importance of market discipline in monitoring the capital

ratio of banks. Memmel and Raupach (2007) also showed

that private banks in Germany tend to have lower capital

reserves than listed banks.

In addition to market discipline, intervention and

regulators can explain why banks store capital. One

possible reason is that capital reserves play an important

role because violations of capital adequacy regulations may

raise the cost of intervention by the regulators, which is

passed on to the banks (Milne, 2002). Numerous research

papers support this provisioning, where minimum capital

regulations that are tightened are often followed by a

corresponding increase in the capital reserves of banks

(Rime, 2001; Aggarwal and Jacques, 2001; Bischel and

Blum, 2004).

3. METHODOLOGY AND DATA

3.1. Methodology

To analyse the determinants of capital reserves

maintained by banks in Indonesia, the following regressive

equation is used:

(1)

Lags are applied to the independent variables in order

to avoid the problem of simultaneity. At the first stage,

analysis of all banks is conducted. Subsequently, during

the second stage analysis is performed based on bank

groups, which are divided into two categories as follows:

SizeSizeSizeSizeSize: Small (large) banks are those with average total

assets for the period of 2004-2007 of less (more) than

the average total assets of all banks in the banking

industry for the same period.

84


Market DisciplineMarket DisciplineMarket DisciplineMarket DisciplineMarket Discipline: Market discipline is represented by

two subcategories, namely those listed and not listed

on the stock exchange. Listed banks must maintain

good market discipline so that their activities can be

monitored.

3.2. BANK CAPITAL RESERVES

The banks» capital reserves or capital buffer (BUFF) is

defined as the difference between the capital adequacy

ratio (CAR) and the statutory minimum of 8%. Table 1

indicates that the level of capital reserves differs for each

bank category, which is justification that analysis based

on bank group is required.

3.3. INDEPENDENT VARIABLES

Several variables are studied in order to observe which

factors influence the capital reserves of banks in Indonesia.

SIZE (logarithmic value of total bank assets) is considered

because larger banks can reduce their capital reserves due

to the too-big-to-fail nature of large banks (Jokipii and

Milne, 2008; Ayuso et al., 2004). LLP (ratio of loan loss

provisions to credit) is also considered to control credit

risk (Ayuso et al., 2004; Nier and Baumann, 2006). LPP as

an indicator of ex-post risk is expected to have a negative

correlation with BUFF because banks incur costs for credit

restructuring. In addition to credit risk, risk of asset is also

considered. As the frequency of data in this research is

monthly, the calculation of asset risk is based on Boyd et

al. (2006) in order to maintain the number of observations.

Asset risk is calculated using the following formula:

(2)

ROA is the ratio of income before tax divided by

total assets and T is the period of observation used in

this analysis, namely 48 months. LNSDROA, as an

indicator of ex-ante risk, is expected to have a positive

correlation with BUFF because banks always strive to

anticipate loss.

Based on Jokipii and Milne (2008), the cost of equity

is also considered as an independent variable. ROE is used

as a proxy of cost of equity. ROE is expected to have a

negative correlation with BUFF. Considering that capital

reserves are also a function of bank income, ROA and NNI

are also considered as independent variables. NNI is non-

interest income against total assets.

Nier and Baumann (2006) underlined that market

discipline is a determinant of capital reserves. Therefore,

financing from the financial market (MD) is also considered

an independent variable. MD is defined as the ratio of

financing excluding deposits divided by total assets. MD is

expected to have a positive correlation with BUFF because

the Deposit Insurance Corporation (DIC) does not

guarantee funds originating from the financial market;

hence, investors encourage banks to increase BUFF in order

to maintain bank stability.

The power of bank monopoly (MPOW) is also

considered an independent variable because banks with

greater market power find it relatively easier to earn a

profit, thus, the bank is subsequently encouraged to

increase its capital reserves by exploiting this profit. MPOW

is defined as the ratio of total bank assets to total assets in

the banking system.

Growth of the ratio of credit to total assets (VLOAN)

is also considered in the analysis. VLOAN is expected to

have a negative correlation with BUFF because as more

capital is allocated as credit the bank»s capacity to increase

its capital reserves decreases. In addition to credit growth,

this research also observes the affect of economic growth

(GDPG) on BUFF. Through this variable pro-cyclical or

countercyclical behaviour of capital reserve can be

observed.

Banking regulations such as the Indonesian Banking

Architecture (IBA) and Single Presence Policy (SPP) are also

85


analysed. IBA (and SPP) are dummy variables with a value

of 1 for all observations after June 2005 (and July 2006)

and 0 for all observations before June 2005 (and July 2006).

Regulatory efficacy in terms of disciplining bank

behaviour is inseparable from the effectiveness of

supervision and institutions. Following Berger et al. (2009),

we include an index of legal rights, as a measure of the

extent to which collateral and bankruptcy laws facilitate

lending. However, this index is constant for the period of

2004-2007. Therefore, a different proxy is used, namely

rule of law (LAW) developed by Kaufmann et al. (2008).

An index of corruption (CORRUPT) and government

effectiveness (GOV) are also considered, both of which

are taken from Kaufmann et al. (2008).

3.4 DATA

This research uses monthly data from 99 commercial

banks for the period 2004-2007, including five state-

owned banks, 65 private banks, 18 joint-venture banks

and 11 foreign banks, which represent more than 96% of

total assets in the Indonesian banking system. Data

regarding the balance sheet and profit/loss statement is

taken from Bank Indonesia, while macroeconomic and

institutional data is taken from the Central Bureau of

Statistics and Kaufmann et al. (2008) respectively. Table 2

presents the descriptive statistics of all independent

variables used in this research.

4. ESTIMATION RESULTS

4.1. Total Sample

The estimation results for the whole bank sample

are presented in Table 3. Based on too big to fail, the size

of the bank (SIZE) has a negative correlation with capital

reserves (BUFF). Additionally, ex-post credit risk (LPP) also

has a negative correlation with BUFF, which confirms the

findings of Nier and Baumann (2006) as well as Ayuso et

al. (2004). This relationship is due to the inability of banks

to immediately adjust their capital when credit risk

intensifies, with banks facing adjustment costs or market

liquidity. In addition, with the assumption of asymmetric

information, an increase in capital can transmit

inauspicious signals, thereby making banks reluctant to

react quickly in the event of a capital shock (Myers and

Majluf, 1984).

Conversely, ex-ante credit risk (LNSDROA) has no

correlation with BUFF. Departing from previous literature,

it was evidenced that the cost of equity (ROE) correlates

positively with BUFF. This indicates that the shareholders

play a role in disciplining the bank. Shareholders tend to

increase BUFF in order to maintain market value (charter

value) of the bank (Park and Peristiani, 2007).

Accordingly, market power (MPOW) also correlates

positively with BUFF. MPOW facilitates the banks to take

advantage of investment opportunities that can reap

future profit and, therefore, reinforce capital reserves.

However, banks in Indonesia tend to avoid bolstering

reserves using retained earnings because there is no

significant correlation between ROA and BUFF. In contrast,

banks do tend to shore up their reserves through non-

interest income.

Financing from the capital market (MD) has a

negative correlation with BUFF. A possible reason is because

term deposits and Bank Indonesia Certificates dominate

the funding structure of banks in Indonesia. Meanwhile,

uninsured debt, like subordinated debt, only makes a tiny

contribution to total bank financing. Therefore, financing

from the capital market tends not to have a significant

disciplinary effect of banks in terms of maintaining capital

reserves. VLOAN also has a negative impact on BUFF. This

demonstrates that as a bank extends more credit it has

less capital to put into its reserves. In relation to the

procyclical effect, the capital reserves of banks are clearly

procyclical, which is evidenced by the negative correlation

between GDPG and BUFF.

86


In addition, the IBA and SPP variables do not have a

significant impact on BUFF. Oppositely, all institutional

variables have a significant influence over the formation

of capital reserves. LAW has a negative correlation with

BUFF, while corruption (CORRUPT) and government

intervention effectiveness (GOV) correlate positively with

BUFF.

From the estimation results, the cost of equity, non-

interest income, market power, a low level of corruption

and government efficacy all positively affect capital reserves

(BUFF). In contrast, size of assets, ex-post credit risk, market

funding, credit growth, economic growth and upholding

the rule of law undermine capital reserves.

4.2. Subsample Analysis based on Size of Bank

In this section, the analysis is based on a subsample

according to the size of the bank, namely large bank

and small banks. Table 3 presents the estimation results

of the subsample analysis. The size of the bank (SIZE) is

only an influential factor in the group of small banks,

where SIZE has a negative correlation with BUFF.

Furthermore, LLP also has a negative impact on BUFF for

small banks but a positive correlation for large banks. In

this context, large banks tend to have more capacity to

increase their capital reserves when credit risk intensifies

compared to small banks. However, there is no significant

relationship between ex-ante credit risk (LNSDROA) and

BUFF.

Shareholders also play a role in disciplining the

behaviour of banks, both for small banks and large banks.

This is indicated by the positive correlation between ROE

and BUFF. These results are congruent to the argument of

Park and Peristiani (2007), where shareholders tend to

maintain capital reserves in order to preserve market value.

Meanwhile, large banks can increase their capital reserves

through retained earnings, while small banks tend to

depend more on non-interest income (NNI). Financing from

the capital market (MD) has a negative correlation with

BUFF and market power is only positive for large banks.

Additionally, the ratio of credit growth to total assets

(VLOAN) has a negative correlation but only for small

banks. Economic growth (GDPG) has a negative correlation

for small banks but positive correlation for large banks.

This indicates that the procyclical effect of capital reserves

only affects small banks.

IBA did not show a significant impact on BUFF in

either bank group, while SPP has a negative correlation

with BUFF for large banks. LAW displayed a negative impact

on BUFF for small banks, while CORRUPT has a positive

impact for both bank groups. When the eradication of

corruption (CORRUPT) is essential to raise BUFF in both

bank groups, then the rule of law (LAW) at small banks is

more significant than at large banks. Rule of law relates to

the responsibility of borrowers to service their loans, hence

weak rule of law could increase non-performing loans (NPL)

and would ultimately erode capital reserves if NPL became

too large (Demirguc-Kunt and Detagriache, 1998). GOV

has a positive correlation with BUFF for small banks but

negative for large banks. Therefore, the effectiveness of

government intervention to ensure prudent banks is only

applicable to small banks.

The analysis based on bank groups according to size

of assets indicated that for small banks, capital reserves

have a positive correlation with the cost of equity, non-

interest income, corruption control, and government

intervention. Meanwhile, capital reserves will decline if size

of assets, ex-post credit risk, financing from the financial

market, credit growth, economic growth and rule of law

increase. For large banks, capital reserves will grow if ex-

post credit risk, cost of equity, retained earnings, market

power, economic growth and corruption increase.

Conversely, only financing from the financial market and

government intervention can erode the capital reserves of

large banks.

87


4.3. Subsample Analysis based on Market

Discipline

Table 3 indicates that in the two groups of listed and

non-listed banks, SIZE correlates negatively to BUFF. Ex-

post credit risk (LPP) also negatively correlates to BUFF for

both bank groups. In contrast, ex-ante credit risk

(LNSDROA) does not have a significant impact on BUFF.

The cost of equity (ROE) only correlates positively with BUFF

for non-listed banks, while retained earnings (ROA) has a

positive correlation with only the group of listed banks.

Non-interest income (NNI) is a determinant of both bank

groups.

Financing from the financial market (MD) correlates

negatively with BUFF for both bank groups, indicating that

financing from the financial market does not discipline

bank behavior. Credit growth (VLOAN) has a negative

correlation with BUFF for the group of non-listed banks.

Capital reserves are procyclical for non-listed banks but

countercyclical for listed banks. The positive and negative

signs respectively indicate this for GDPG. Accordingly, it

can be concluded that the financial market is influential in

disciplining the behavior of banks to become more prudent

in reserving capital during economic booms. Conversely,

direct intervention in the capital management of the bank

(IBA) will erode the capital reserves of listed banks. This is

not the case for small banks.

Institutional factors are only important for non-listed

banks. LAW has a negative correlation with BUFF, however,

CORRUPT and GOV have a positive correlation.

In brief, the capital reserves of non-listed banks are

influenced positively by the cost of equity, non-interest

income, controlling corruption and the efficacy of

government intervention; and negatively affected by the

size of assets, ex-post credit risk, market financing, credit

growth, economic growth and the rule of law. Retained

earnings, non-interest income and economic growth,

however, positively influence the capital reserves of listed

banks; but the size of assets, ex-post credit risk, market

financing and IBA undermine the capital reserves of listed

banks.

4.4. Sensitivity Analysis

Several sensitivity analyses are explained in this

section to ensure the robustness of the results presented

in sections 4.1 to 4.3. First, we found that the level of ROE

and ROA is very biased, not normally distributed, and

outliers on the left and right-hand side of the probability

distributions. Accordingly, we excluded the values of ROE

and ROA if they fell below the 2.5% percentile or above

the 97.5% percentile. Using this new «variable» we re-

estimated Equation (1) for all banks as well as bank types

that were based on asset size and market discipline.

Consequently, the results found in 4.1 to 4.3 did not

change.

Second, we omitted the variables of banking

regulation like IBA and SPP because they continue to this

day. By estimating equation (1) again without the

regulation variables, we found that the determinants of

capital reserves remained consistent with our analysis in

sections 4.1 to 4.3.

Third, we changed the definition of large and small

banks pursuant to Bank Indonesia»s policy, where large

banks have total assets in excess of Rp10 trillion, while

small banks have total assets of less than Rp10 trillion. We

introduced a dummy variable with a value of 1 for large

banks and 0 for small banks. Using this criteria we ran the

estimations again and found that our results were

consistent with those presented in section 4.2.

5. CONCLUSION AND POLICY

RECOMMENDATIONS

After the application of Indonesian Banking

Architecture at the beginning of 2004, commercial banks

in Indonesia, in general, maintained a very high capital

88


adequacy ratio despite the statutory minimum of only 8%.

Bank reforms in Indonesia through IBA were basically

designed to prepare a robust banking market ready for

Basel II implementation. In Basel II, the statutory minimum

(Pillar 1) plays an important role in protecting the banks

from default. To this end, the next question is which factors

encourage banks in Indonesia to maintain capital reserves

well above the minimum 8% level? Without understanding

this question it is difficult to predict how bank capital will

react to changes in the economy and regulations, for

example Basel II (Berger et al., 2008). This research fills

this gap by testing several factors made up from indicators

of financial ratios, the macro economy, regulations and

institutions, which can explain the behavior of banks in

terms of managing their capital.

In addition to analyzing these factors for all

commercial banks in the sample, analyses were also

conducted based on bank groups. Bank groups were

observed based on the size of assets as well as market

discipline. One important finding from this research is that

procyclicality only affects the capital reserves of small banks

and non-listed banks. In contrast, large banks and listed

banks have countercyclical capital reserves. Through this

finding we recommend policies directed towards Basel II

including, among others, consolidation of small banks,

providing space for banks to become involved in financial

market activities and reinforcing market discipline.

Furthermore, it was found that non-interest income is a

contributing factor to the capital reserves of commercial

banks in Indonesia. Therefore, supervision of non-interest

activities needs to be enhanced considering that non-

interest income is a source of bank risk (Stiroh and Rumble,

2006; Lepetit et al. 2008). In the context of Indonesia

further research regarding these issues is required.

89


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91


Article I - Attachment

SIZE 9.4657 19.53 14.5455 1.9732

LLP 1,13E-05 2,0791 0.0248 0.0524

LNSDROA -13,82 -1,5701 -7.3099 1.4752

ROE -22,6992 0,0355 -0.0173 0.4691

ROA -0,13268 0,2068 0.0019 0.0070

NNI -0,06558 0,0865 -0.0026 0.0044

MD -0,9993 38,1997 -0.2076 0.8257

MPOW 0,000011 0,2258 0.0103 0.0272

VLOAN -0,95974 191,9 0.0547 1.5791

GDPG 0,003542 0,0708 0.0463 0.0185

IBA 0 1 0.6458 0.1233

SPP 0 1 0.3750 0.1250

LAW -0,86 -0,71 -0.7900 -0.7900

CORRUPT -0,92 -0,72 -0.8250 -0.8250

GOV -0,46 -0,41 -0.4350 -0.4350

Table A1.2Descriptive Statistics

VariableMin

2004

St.DevMeanMax

Table A1.3Determinants of Capital Reserves held at Banks in Indonesia

Table A1.1Mean Test of Bank Capital Reserves

This test was constructed using the null hypothesis:

≈the mean value of capital reserves is not different in the

two bank sub-groups (high and low)∆. (***) indicates that

the t-statistic is significant at the 1% level to reject the

null hypothesis.

SIZE -0.17929*** -0.171172*** -0.022605 -0.195476*** -0.066157***LLPt-1 -0.85223*** -0.865304*** 1.490457*** -1.290105*** -0.676817***LNSDROAt-1 -0.001813 -0.002426 0.001014 -0.001607 0.000819ROEt-1 0.049391** 0.071132** 0.005856** 0.050326** -0.13307ROAt-1 -1.08356 -1.463646 4.477566*** -1.838971 6.044162**NNIt-1 4.233191** 5.355279** 0.825891 5.065307** 2.599108**MDt-1 -0.06304*** -0.062324*** -0.174287** -0.060466*** -0.100714***MPOWt-1 0.84966*** -19.46917 1.130398*** 4.092566 0.112012VLOAN -0.00599*** -0.006004*** -0.017714 -0.005977*** -0.004846GDPG -0.327763** -0.409201** 0.108142** -0.455092** 0.098269**IBA -0.004914 -0.007997 -0.005699 -0.006093 -0.012523*SPP 0.001163 0.001862 -0.007973** -0.001764 -0.001021LAW -1.033143** -1.210726** 0.271761 -1.427777** 0.162382CORRUPT 0.508756** 0.515466* 0.200589* 0.589204** 0.083997GOV 2.616215*** 3.10298*** -0.577391** 3.549343*** -0.038159Constant 3.69815*** 3.605754*** 0.607335 4.023385*** 1.48329***

Jumlah Observasi 3824 3068 756 2734 1090Adjusted-R 2 0.813892 0.812586 0.728987 0.803056 0.937919X 2-statistic (Tes Hausman) 78.51209*** 66.231831*** 22.922772* 52.924*** 522.696***

Independent VariableSmall Bank

Assets Size

Closed BankOpened BankMajor Bank

Market DisciplineAll Bank

2004 Size 0,1151 0,3629 6,232***Market Discipline 0,1686 0,3636 5,317***

2005 Size 0,4491 0,2783 4,861***Market Discipline 0,1466 0,2804 -4,335***

2006 Size 0,1363 0,2715 5,714***Market Discipline 0,1236 0,2872 -7,584***

2007 Size 0,1464 0,2833 -5,516***Market Discipline 0,1297 0,2872 -7,249***

Year BankMean

t-statisticLowHigh

92


The dependent variable is bank capital reserves (BUFF),

calculated as CAR minus 8%. The model is estimated using

fixed effect panel data analysis. The regression coefficient is

corrected using White heteroskedasticity, which is consistent

with the deviation. (***) indicates that the t-statistic is

significant at a level of 1%, meanwhile (**) and (*) indicate

that the t-statistic is significant at the 5% and 10% levels

respectively. Characters in bold typeface represent the

different signs for the regression coefficient between the

bank sub-groups within one type of related bank.

93

Article II - Procyclicality of Loan Loss Provisioning in Indonesia

Article II

Procyclicality of Loan Loss Provisioning in Indonesia

Wimboh Santoso, Ita Rulina, Elis Deriantino

1. INTRODUCTION

The term «procyclicality» refers to dynamic interaction

(positivefeedback mechanism) between the financial sector

and real sector. Such interaction has the potential to

exacerbate fluctuations in the business cycle as well as

create or compound uncertainty in the financial system.

During economic boom conditions commercial banks

tend to reduce their loan loss provisions, thereby ensuring

more funds are available to allocate. On a competitive credit

market, banks will tend to relax their requirements to

extend credit and offer more competitive/lower lending

rates. Such conditions open the possibility of intensifying

credit risk when the economy enters a period of

contraction. Previous studies by Angklomkliew, et al (2009),

LaevenandMajnoni (2003), Davis and Zhu (2005)

andBikkerandMetzemekers (2005) demonstrate that banks

tend to increase their loan loss provisions when economic

conditions deteriorate due to a corresponding decline in

credit quality, or greater credit risk. The practice

subsequently erodes bank capital and compels regulators

to force banks to increase their capital up to a level which

can absorb the unexpected losses that could emerge.

However, during a period of economic downturn it is

difficult and expensive for banks to find supplementary

capital because of limited liquidity available on the market.

This encourages banks to withhold or cease credit

allocation, which in turn can undermine economic

conditions that are already deteriorating because the credit

required to catalyze economic growth is now only available

in a limited amount. The banking practice of increasing

provisions during an economic slowdown and reducing

provisions during a boom period is known as procyclical.

Borio et al. (2001) stated that banks should actually

begin to confront an increase in credit risk when the

economy is still robust and not during a recession.

Accordingly, forward-looking banks will begin to increase

their provisions while the economy is still performing

soundly, thus, the opportunity for these banks to absorb

losses increases during a recession period. Prudent loan

loss provisioning encourages the creation of a financial

system more resilient to shocks.

This research aims to explore how bank provisions in

Indonesia respond to changes in the business cycle for the

period from 1995-2009, which covers one business cycle

and three crises periods in Indonesia, namely the Asian

Financial Crisis 1997/98, the mini crisis of 2005 and the

global crisis of 2008, as well as how these responses

affected the stability of economic growth and the financial

system in Indonesia. The practice of prudent provisioning

is often known as income smoothing; namely withdrawing

provisions from the reserves if the actual losses exceed the

expected losses during an economic slowdown and adding

94


3. The importance of reviewing Basel II to reduce or

remove disincentives in the establishment of

«appropriate provisions for loan losses».

2. LOAN LOSS PROVISIONING FRAMEWORK IN

OTHER COUNTRIES

The financial authorities in several other countries

have tried to overcome procyclicality of provisioning in the

banking sector. The Bank of Spain applied Dynamic General

Provisioning in 2000. This provisioning framework obliged

banks to form provisions based on a given ratio of their

credit growth, thus, availing the possibility of banks forming

larger provisions during periods of sound economic

conditions as a buffer for when conditions deteriorated.

This framework was proven to effectively help banks

in Spain during the latest crisis, when banks did not have

to allocate larger provisions than the period prior to the

crisis, hence, alleviating the impact of the recession on

Spanish banks. Nevertheless, this framework failed to

prevent excessive lending by Spanish banks, primarily to

the property and construction sector from 2005-2007, thus

triggering a property bubble. The impact of the global crisis

in 20088 caused this bubble to burst and seriously

undermine Spanish economic performance, which relied

heavily on property and construction growth. Such

circumstances lead to numerous houses not being sold

and a dramatic drop in property prices, thus eroding bank

asset quality (McGovern, 2010).

3. PROCYCLICALITY OF LOAN LOSS

PROVISIONING IN INDONESIA

Overview of Loan Loss Provisioning in Indonesia

In December 1998, Bank Indonesia mandated that

banks form loan loss provisions based on a specific

percentage of asset quality (credit), which was divided into

five categories: pass, special mention, sub-standard,

doubtful and loss. In 2005 Bank Indonesia tightened this

provisions to the reserves if the actual losses are lower

than the expected losses, which generally occurs as

economic conditions improve. The result is that the banks»

provisions increase during boom periods and decrease

during a recession (Laeven and Majnoni, 2003). This is

prudent risk management because banks allocate more

provisions during good economic times to absorb losses

that could emerge when the economy becomes sluggish,

otherwise known as dynamic (statistical) provisioning

(Saurina et al., 2000).

However, from an accounting standpoint, that

prioritizes the accurate measurement of a bank»s financial

conditions at specific times, the practice of income

smoothing is deemed as the banks attempting to modify

their reported revenues in order to minimize fluctuations

in earnings √ particularly when economic conditions

deteriorate and business earnings can fall sharply √ in the

interest of the manager and shareholders who receive

incentives based on company earnings.Current

international accountancy standards restrict the recognition

of ≈likely to be incurred loss∆ likely to be incurred (expected

or future or not yet to exist) loss. From the regulators

perspective, a good loan loss provisioning framework must

be able to identify ≈identified∆ (realized) and likely to be

incurred (expected or future or not yet to exist) loss.

Hence, based on the different perspectives of

financial regulators and accounting standards, the Financial

Stability Forum explained three important issues relating

to the procyclicality of loan loss provisioning:

1. The importance of accommodating expert judgment

when setting «incurred loss for provisioning of

loanlosses».

2. The importance of considering the «incurred loss

model» with an alternative analysis approach to

acknowledge and measure «loan losses» by

accommodating «a broader range of available credit

information».

95


regulation by reducing the number of days past due (credit)

for non-performing loans categorized as sub-standard,

doubtful and loss. This tighter regulation concerning the

assessment of credit quality is expected to encourage more

prudent risk management by the banks.

Literature Review

A number of studies have been conducted regarding

the procyclicality of loan loss provisions. Angklomkliew et

al. (2009) using annual data for the period 1998-2008 to

explore the procyclicality of loan loss provisions in eight

Asian countries, including Indonesia. The research found

evidence for the presence of procyclicality of provisions in

the eight countries but no indication of income smoothing

or prudent provision behavior in the sample countries.

The practice of income smoothing was found in more

advanced countries in Europe, USA, Japan and Latin

America by research conducted by Laeven and Majnoni

(2003) using data from 26 countries in Europe, US, Asia

(minus Japan), Japan and Latin America for the period of

1988-99. The practice of prudent provisioning helped

dampen the impact of procyclical provisions, which

occurred simultaneously in these countries.

A similar occurrence happed in Australia and New

Zealand. Hess et al. (2008) using data from 32 banks in

Australia and New Zealand for the period 1980-2005

found a negative correlation between GDP growth and

provisions, which indicated the presence of procyclicality,

and a positive relationship between earnings and loan loss

provisions that confirmed banks in Australia and New

Zealand were concomitantly performing income

smoothing. This research also found that rising property

and stock prices reduced bank provisions in Australia,

which indicated that movements in asset prices or collateral

(house prices were a proxy of collateral) in turn affect the

bank provisioning cycle in Australia, thus contributing to

the emergence of procyclicality in the sample period.

Data and Methodology

In order to explore behavior provisioning by banks

in Indonesia this research adopts the model of Laevan and

Majnoni (2003). There are three factors hypothesized to

affect the decision of loan loss provisioning by banks:

Ratio of earnings (before tax and provisions) to total

assets (EBP/TA)

The relationship between earnings and provisions

determines how far a bank will practice income

smoothing. A positive relationship between these two

indicates that a bank is implementing prudent risk

management from the perspective of regulators

because the bank has a buffer of provisions which

exceeds that formed when the bank»s earnings

increase in order to absorb risk that tends to increase

when conditions deteriorate and undermine bank

earnings (Bikker and Metzemakers, 2005).

Real credit growth (year-on-year)

Real credit growth is a proxy for cyclical bank

indicators. Excessive credit growth is suspected to

intensify future credit risk. This positive relationship

between credit growth and credit risk is supported

by empirical studies, including Hess et al. (2008),

which indicated that excessive credit growth

intensifies credit risk for the subsequent 2 to 4 years

for banks in Australia and New Zealand. Therefore,

prudent banks will begin increasing their provisions

during the expansionary stage of the credit growth

cycle as a buffer to absorb losses that could emerge

at a future date, or a positive correlation between

provisions and credit growth.

Real GDP growth (year-on-year)

Real GDP growth is a proxy of the business cycle.

Prudent banks will increase their provisions when the

economy is in an expansionary cycle in order to have

an adequate buffer to overcome risk that tends to

increase as the economy enters a contractionary cycle,

96


or a positive correlation between provisions and

economic growth.

Based on Laevan and Majnoni (2003), the correlation

between these three variables and loan loss provisions

can be modeled as follows:

LLP/TA it = .i0 + .i1EBP/TAt + .i2GDPt+ .i3Creditt + Ait (1)

Furthermore, considering that Bank Indonesia

promulgated tighter regulations regarding the

evaluation of credit quality at the beginning of 2005,

the model presented in equation 1 was extended by

adding a dummy variable to differentiate the periods

before and after the new regulation was introduced.

Therefore, the model can be written as follows:

LLP/TA it = .i0 + .i1EBP/TAt +n.i2GDPt + .i3Creditt + .i4

DUMMY + Ait (2)

Where:

LLP/TAit : the ratio of loan loss provisions to total

assets of bank i in year t

EBP/TAit : the ratio of earnings (before tax and

provisions) to total assets of bank i in year t.

Creditit : real credit growth (yoy) bank i in year t.

GDPt : real GDP growth (yoy) in year t.

DUMMY : 0=before, and 1=during and after 2005.

Leaven and Majnoni (2003) stated that from the

perspective of regulators, the practice of provisioning

will be procyclical or imprudent if one of the following

three criteria is met:

The ratios EBP/TA and LLP/TA correlate negatively

or a bank reduces its provisions when its revenues

or profits are high.

Credit growth and the ratio LLP/TA correlate

negatively or a bank reduces its provisions when

credit growth is strong.

GDP growth and the ratio LLP/TA correlate

negatively or a bank reduces its provisions when

the business cycle is expansionary.

This research uses annual data from 120 banks in

Indonesia for the period 1995 to 20091. The model in

equation 2 is estimated using the Panel General Least

Square-Fixed Effect2 approach with White Period Robust

standard errors and covariance to correct serial correlation

and time varying variances at the disturbance or error.

Before estimating the model data stationarity was tested.

Im-Pesaran-Shin unit root tests indicated that all variables

were stationer.

Empirical findings

The estimation results are as follows:

LLP/TAit = 2.09 + 0.02EBP/TAit√√√√√ 0.19GDPt √ 0.004Creditit √

0.17dummy, Adj R-sqr: 0.36 DW: 1.52

[9.82]*** [0.46] [-5.56]*** [-1.85]* [-1.82]*

Note:

*, ** and *** refers to a significance level at 90%, 95%

and 99% respectively.

The model indicates that banks in Indonesia increase

their provisions when the economy and credit are in

decline; or a negative correlation between the ratio of

provisions (LPP/TA) to economic and credit growth.

Elasticity of the ratio of provisions to GDP growth is -

0.65, which strongly indicates a cyclical impact.

Meanwhile, the elasticity of the ratio of provisions and

credit growth amounting to -0.04 indicates a weaker

cyclical impact. Banks in Indonesia do not practice income

smoothing or prudent provisioning as indicated by the

ratio between provisions and earnings (EBP/TA), which is

insignificant.

These results indicate that the provisions formed by

banks in Indonesia tend to be procyclical; or that banks in

Indonesia are basically risk sensitive and insufficiently

1 Source of data: Bank Indonesia2 The model is also estimated using the random effect approach, however the Hausman

test indicated that estimation results using the fixed effect were more efficient comparedto the random effect.

97


forward-looking in their evaluation of credit risk to

accommodate the business cycle and credit cycle from

1995 to 2009.

The impact of procyclicality from loan loss

provisioning on financial system stability and

the economy of Indonesia

It is empirically proven that the provisioning practiced

by banks in Indonesia tends to be procyclical with the

business cycle. Figure A2.1 illustrates the development of

loan loss provisions, the business cycle and credit risk in

Indonesia for the period 1995 to 2009.

highest level since the Asian financial crisis in 1997/98 √

and also undermine credit quality with the NPL ratio

jumping from 4.50% in 2004 to 7.59% in 2005. Such

conditions forced the banks to form larger provisions

and slow their extension of credit, thereby restricting

credit growth, which contracted sharply (26.63% in

2004, to 26.61% in 2005 and 13.71% in 2006). During

this crisis the sharp decline in credit growth did not have

any significant impact on economic growth in

general.

Figure A2.1Estimation Results of Share Signals

-60

-40

-20

0

20

40

60

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

credit_yoy( %) GDP_yoy(%)

NPL(%) LLP/TA(%)

During the Asian financial crisis in 1997/98, bank

credit risk soared dramatically with the NPL ratio reaching

47.43%, therefore, banks were forced to allocate much

larger provisions, where LLP/TA peaked at 13.11%. The

extension of credit plummeted to its nadir of -31% and

the economy experienced a recession with growth of

around -13% at the end of 1998. When the economy

began to recover and credit risk began to ease due to

internal consolidation and a restructurization program, the

ratio of provisions subsequently declined.

At the end of 2005, Indonesia entered a mini crisis

attributable to the government»s decision to liberalise

domestic fuel prices. This adjustment triggered inflation

to skyrocket from 6.4% in 2004 to 17.11% in 2005 - its

Figure A2.2Estimation Results of Share Signals

-60

-40

-20

0

20

40

60

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

credit_yoy( %) GDP_yoy(%)

NPL(%) LLP/TA(%)

From 2007 to the middle of 2008 was a period of

recovery when the economy and credit grew expansively

and credit quality improved (NPL declined). During this

period, banks once again reduced their provisions. This

indicates that banks in Indonesia tend to be risk

sensitive.

Nevertheless, the global crisis of 2008 did not overly

affect the stability of bank performance, especially when

compared to conditions a decade ago. Credit risk remained

manageable (NPL ratio of below 5%) and the ratio of bank

provisions only increased from 1.12% in 2007 to 1.28%

in 2008. Despite the capital adequacy ratio declining from

19.3% in 2007 to 16.2% in 2008, in general bank

resilience remained high (compared to the minimum

regulatory standard CAR of 8%). However, this crisis

encouraged banks to become more cautious in the

98


extension of credit, hence precipitating a steep decline in

credit growth from around 30% in 2008 to 10% in 2009.

The sharp decline in credit growth contributed to the

decline in economic growth where GDP grew by just

4.55% in 2009 (compared to 6.35% in 2007 and 6.01%

in 2008). Despite the decline, the Indonesian economy

still managed to post positive growth exceeding 4% in

2009. Furthermore, economic performance and the

extension of bank credit recovered quickly following the

crisis. Recent data indicates that in June 2010, the

Indonesian economy grew by 6.2% and credit by 18.8%

(yoy). This indicates that the impact of provision

procyclicality has remained manageable and has not

affected economic performance through a decline in credit

allocation in the two latest crisis periods. Such conditions

are attributable to stronger bank and economic

fundamentals.

3. CONCLUSION AND POLICY

RECOMMENDATIONS

Estimation results indicate a reasonably large cyclical

impact from the business cycle on bank provisions, where

bank provisions in Indonesia tend to be procyclical and

the banks tend to be risk sensitive. However, such

conditions do not adversely affect economic performance

in general, with GDP in Indonesia persistently in excess of

4% during the last two crisis episodes. Furthermore, the

Indonesian economy and credit extension recovers

expeditiously in subsequent years due to stronger bank

and economic fundamentals. However, a loan loss

provisioning framework that is forward-looking and

counter cyclical can be considered to nurture a more stable

financial system, in particular in terms of the bank

intermediation function to help create more robust and

sustainable economic growth.

99


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68

Bab 4 Prospek Sistem Keuangan Indonesia

DIRECTOR

Wimboh Santoso

COORDINATOR & EDITOR

Agusman Henry R. Hamid

WRITERS

Ardiansyah, Anto Prabowo, Linda Maulidina, Ratih A. Sekaryuni, Pungky Purnomo, Imansyah,

Boyke Wibowo Suadi, Henry R. Hamid, Bambang Arianto, Ita Rulina, Noviati, Januar Hafidz,

Cicilia A. Harun, Sagita Rachmanira, Reska Prasetya, Heny Sulistyaningsih, Mestika Widantri,

Elis Deriantino, Hero Wonida, Primitiva Febriarti, Herriman Budi Subangun, Khairani Syafitri

COMPILATORS, LAYOUT & PRODUCTION

Henry R. Hamid Januar Hafidz

CONTRIBUTORS

Directorate of Banking Supervision 1



Directorate of Sharia Banking

Directorate of Credit, Rural Bank Supervision and SMEs

Directorate of Bank Licensing and Banking Information

Directorate of Accounting and Payment Systems

Directorate of Reserve Management

Directorate of Economic Research and Monetary Policy

DATA SUPPORT

Suharso I Made Yogi

Financial Stability ReviewNo. 15, September 2010

Documents

Financial Stability Review (FSR) - bi.go.id · 1.17.2 DER and TL/TA of Non-Financial Public Listed Companies 14 ... 2.48 Volatility of several Asian Bourse Indices 43 2.49 Bank Share