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Tomorrow’s insurance
2McKinsey & Company
Macro-trends: we are the engine of growth in global insurance
SOURCE: McKinsey Global Insurance Pools, Economist Intelligence Unit
2,342
+2% p.a.
2013
2,013
2020
823413
2020
+10% p.a.1
2013
Mature marketsGWP, USD bn
Emerging marketsGWP, USD bn
1 GWP growth is 1-4% higher in local currencies due to FX effect 2 USA, Japan, UK, France, Germany, Italy3 China, Taiwan, India, South Africa 4 Top countries ranked by absolute growth 2013-2020
Top growth markets4:GWP GDP
Top growth markets4:
6%+10%+2% 3%
2%+14%+2% 2%
5%+7%+5% 3%
3%+7%+3% 1%
5%+12%+3% 3%
GDPGWP
• Remain the largest profit pools
• Top market position is not a must to achieve strong performance
• 6 countries represent 80% of total GWP2
• Driver of global growth
• Foreign ownership restrictions - local champions capture superior value
• Tailored skills required
• Long payback time
• 4 countries represent 80% of total GWP3 – 2 of which have limited accessibility (China, India)
3McKinsey & Company
We are the engine of growth in global insurance
SOURCE: IHS Global; McKinsey Analysis
+7% p.a.
+13% p.a.
2018
38.2
3.0
35.2
2017
36.9
2.9
34.0
2016
35.0
2.7
32.2
2015
32.9
2.6
30.3
2014
30.4
2.4
28.0
2013
27.7
2.3
25.5
2012
26.3
2.1
24.2
2011
23.3
1.7
21.6
2010
22.6
1.5
21.1
2009
18.2
1.2
17.0
2008
15.2
1.2
14.0
Indonesia, Malaysia,
Philippines and Thailand
Other Asian countries
Million
Today
33
38
Absolute growth, 2013-18%
New passenger vehicle sale in Asia (2008 to 2018)
4McKinsey & Company
The insurance industry’s business model has
remained stagnant for a very, very long time,
while the world around us was changing
immensely. It is vitally important to the future
of our industry that we re-examine our
customers, products and distribution models
to ensure we remain relevant to the
communities we serve. We can’t be trying to
sell the same products and services to people
that we sold to their parents and grandparents
5McKinsey & Company
A perfect storm for insurance?
Our evershifting customers
Digital as an opportunity: really?
Distribution: the big shift
War for talent: is insurance winning?
Public vs. private: new social contract?
6McKinsey & Company
Demographic trends – between now and 2020, the share of retirees will grow in all geographies
SOURCE: Population Reference Bureau; Global Insight (WMM), World Bank, European Commission Papers 2005
Percent of population by age
Ratio working age/retired1
1 Ratio of population in age group 20-65 to age group 65+
Europe US LatAm China Japan Asia
3.7 3.2 4.4 3.5 8.1 6.7 7.6 5.5 2.4 1.9 8.5 6.9
11
100% = (million)
2020e
744
21
21
27
19
2012
742
21
14
21
27
17
0-20 yrs20-30 yrs30-45 yrs45-65 yrs65+ yrs
2020e
338
26
13
19
25
17
2012
318
27
14
20
26
147 9
2020e
620
33
16
22
20
2012
570
37
17
21
18
9
2020e
1,433
24
13
23
28
12
2012
1,377
25
18
24
25
11
2020e
125
17
10
18
27
29
2012
127
18
21
26
24
7 9
16
22
22
2012
4,255
33
18
22
20
2020e
4,582
31
▪ Retirement age
populations (65+) will grow to ~20% of developed markets’ population by 2020
▪ Emerging markets will continue to be
much younger, despite increasing
longevity
7McKinsey & Company
Macro trends – in emerging markets, the middle class is capturing an increasing share of the total income pool
China
Lowest
earning 40%
Middle 40%
(“Middle class”)41
3338
2012
42
2020E1
Highest
earning 20%
2521
ESTIMATES
India
Share of income Percent
Share of incomePercent
1 Projection until 2020 based on extrapolation of past trends 2 In constant 2005 USD
SOURCE: World Income Inequality Data, World Bank, Team analysis
Share of income Percent
Average annual middle class income2
USD thousand3.6 6.6 0.9 1.7 4.1 6.0
Total middle class income pool2
USD trillion1.8 3.9 0.4 0.9 0.3 0.5
36
2009
21
38
42
Lowest
earning 40%
Middle 40%
(“Middle class”)
Highest
earning 20%
23
41
2020E1
Lowest
earning 40% 15
2020E1
Highest
earning 20%
35Middle 40%
(“Middle class”)
50
12
57
31
2009
Brazil
8McKinsey & Company
Marco trends – in mature markets, shrinking middle class
United States
Lowest
earning 40%
Middle 40%
(“Middle class”)
Highest
earning 20%
2020E1
11
37
52
2011
12
37
51
ESTIMATES
Germany
Share of income Percent
Share of incomePercent
1 Projection until 2020 based on extrapolation of past trends 2 In constant 2005 USD
SOURCE: World Income Inequality Data, World Bank, Team analysis
Share of income Percent
Average annual middle class income2
USD thousand41.4 43.0 37.9 43.3 34.0 37.0
Total middle class income pool2
USD trillion5.2 5.7 1.2 1.4 1.7 1.8
37
41
Highest
earning 20% 40
41
22
Middle 40%
(“Middle class”)
2020E1
19
2011
Lowest
earning 40%
Lowest
earning 40%
2020E12009
20
3839
41Highest
earning 20%
19
Middle 40%
(“Middle class”)
42
Japan
9McKinsey & CompanySOURCE: Bundesamt für Statistik, McKinsey research
Generational divide – by 2024, almost half of the accessible customers (i.e., aged 25-65) will belong to Gen Y (i.e., born between 1981-2000)
1 Accessible customers defined as population aged between 25-65. Example shown based on Swiss demographics
Customer base today Customer base 2020-2030 Future
2024
2014
~60
Baby boomers1945-1960
26%
4%
• “Pull” use of digital
• Expect tailored
marketing
outreach
• Little brand loyalty
• TV remains
dominant media
~45
Gen X1961-1980
53%
49%
• “Pull” use of digital –
smartphones shift
behavior
• Value freedom of
choice
• Skeptical of brands
• Product research
takes place online
~25
Gen Y1981-2000
21%
47%
• Always “on” and
connected
• Value convenience/
friendly processes
• Engage with brands
• Most of the
buying journey takes
place online
~10
Gen Z 2001-
0%
0%
• Digital is seen as
tablestakes
• Strong bias to
social/mobile
media
• Social network is
key influencer in
buying decisions
Expected limit for
waiting time for banking services is down to 5 minutes from 15 minutes
in just 7 years
“On the average
Web page, users have time to read at
most 28% of the words during an
average visit;
20% is more likely.”
2020 12% 52% 36% 0%
Cohort
Character-istics
Cohort share of accessible customers1
10McKinsey & Company
Multi-channel expectations – new technologies are reshaping consumer expectations and creating a need for multi-channel services
SOURCE: McKinsey research
75% of online customers expect help within 5
minutesSpeed
Customization61% of customers are more likely to buy
from companies delivering custom content
75% of consumers have used shopping apps
for consumer goodsPurchasing
79% of consumers trust online reviews as
much as personal recommendationsSocial
Emerging market customer adoption is even faster e.g.
Kenyan mobile payment penetration grew from zero to 51% in 2007-2011
11McKinsey & CompanySOURCE: LIMRA, “The Role of the Internet in the United States,, N=2100, McKinsey research on customer centric transformation; Discover Deliver
Design Marketing ”
Multi-channel expectations – multi-channel engagement tends to correlate with satisfaction and hence with loyalty/advocacy
5
7
5
5
7
5
6
5
4
9
5
3
5
6
10
9
11
7
7
14
20
3
16
3
10
10
8
16
6
15
1453 1
Change name,
beneficiary, etc.58
Check on
claims status
Pay premiums 61
New product
information64
2
Request forms 65
Access my
current policy268
Obtain general
information
2
68
PhoneMobile apps/site Agent
MailEmailCompany website
Availability of multi-channel touch points is a customer expectation, driving satisfaction
Most preferred insurance service channels, percent
90
70
40
20
0
60
80
50
30
10
100
Overall Satisfaction/experience rating
1087641-3 95
Stated IntentPercent
Example: US Car Insurance
Research shows that satisfied customers show string loyalty and advocacy
Repurchase: % of
respondents that if
needed would buy
from the same
carrier1
Retention: % of
respondents that
are not likely to
switch1
Recommend: % of
respondents that
are likely to
recommend1
Cross-Sell: % of
respondents that
are likely to buy
another product2
Multi-channel excellence can boost revenue up to 20 percent and reduces service costs by an equal amount
12McKinsey & Company
As consumers approach the tipping point in ease of access, a new integrated network economy is emerging
SOURCE: McKinsey Panorama
24/7 connected
Expectation of simplicity and immediacy
High emotional connections
Self-perception of
intelligence
Extreme e-tribalism
Zero tolerance for bad customer
experience
Expectation and appreciation of proactivity
Less desire for
personal possessions
NETWORK ECONOMY
Individual value chains collapse into one integrated network economy
• Higher competition
• Widening inequality
• More integration and
partnerships
• More emphasis on
distribution
• More emotional
• Highly data driven
• Strongly globalized
13McKinsey & CompanySOURCE: McKinsey, expert interview
OUTSIDE-INPing An with its successes and failures provides an interesting example of ecosystem building
Cornerstones of the Ping An approach
▪ Strong control of the brand
▪ Large operational and business
independence for individual
businesses (incl., IT, HR)
▪ Continuous experimentation,
willingness to rapidly change
direction (e.g., trying e-
commerce, selling to WalMart,
or trying Auto greenfield, than
buying Autohome)
▪ Strong personal connectivity
(Cross-Board members) and
personal ownership
(executives owning shares)
▪ Leverage offline channel (~1
mn agents) for building online
scale
▪ Buy-in to key assets early e.g.,
Chinese Soccer League
▪ Collect data from inside and
outside of ecosystem (e.g.,
WiFi, social security)
▪ Do not bet on one platform
piece – (e.g., One Account has
not yet fully taken up, but
ecosystem works already)
INSURANCE BANKING
Gaming
HousingAutoHealth cloud
60 mln users
150,000 doctors
LUFAX
Other Financial
Services
P2P, AM,
Wholesale
Yiwallet
Ping-An pay
Control CRM, Joint data for
finance, 200 data scientists
Collect data
One account
PING An 3.0 – open platform, open marketplace
~250 million
online users
Food
CASE STUDY
14McKinsey & Company
Telecom sales
Logistics
Autoinsurance
Business administration
Job markets
Other content
Advertisement
Management of companies
Remote retail
Passenger travel sales
Home security
Industrial M2M
Machinery and equipment
Goods wholesale
Gen. merch.
Materialsand furniture
Retail payments
Clothing
Food and beverage
Cons. lending
E-government
E-Utility
Architect and engineering
Retail deposits
Auto and gasoline sales
Travel services
Legal
Agroproducts
Business travel
Materials and supplies
Repair andmaintenance
Transport support activities
Mortgage
Homeinsurance
Capital markets
Retail housing brokerage
Accounting
Auto rental&leasing
Wholesale brokerageCorporate banking
Mutual funds
Energy&smart grids
User generated content
Consultation
Corporate finance
System integration and data
Social care
Publishing
Restaurants
Gaming
E-education
Recreation and culture
Telecom services
Hotels
Other direct B2B
Life insurance
Private and digital health
Sex & datingRetail brokerage
Health and care stores
B2B insurance
In this new network economy, large ecosystems develop naturally along the main client need groups with many having a clear insurance relevance
SOURCE: McKinsey, IHS World Industry Service
USD 62 trillion integrated network economy
Utility
Government Education
Health
Pharma
Content
Telecomnetworks
MiningConstruction
Software development
Agriculture production
Manufacturing
AM factory
ALM
Retail client
Wholesale client
AUTO
B2B SERVICES
B2B COMMERCE
B2C COMMERCE
HOUSING
CONTENT
GLOBAL CORP.
SERVICES
TRAVEL & HOSPITALITY
BANKING
E-HEALTH
Circle size proportionalto revenue pool
Revenue pool smallerthan USD 100 billion
NETWORK ECONOMY
1 Estimations based on corporate sales data, GDP industry breakdowns and expert assumptions. Circle sizes show approximate revenue pool sizes, smallest circle meaning less than USD 100 billion in revenues. Not all industries and subcategories are shown.
15McKinsey & Company
Most economic profits in the integrated network economy will migrate to ecosystem orchestrators and those brands with truly emotional connection
Far Mid Close
Low
Moderate
Strong
Proximity to customer in value chain
Far Mid Close
Emotional connectionwith customers
2015 2025
Beloved brands Ecosystem
orchestrators
SOURCE: McKinsey analysis
White labelled back office with minimal profits
Economic “winner”’
Distribution of economic profits
ILLUSTRATIVE
16McKinsey & CompanySOURCE: McKinsey Panorama analysis
ILLUSTRATIVE
Value chain
Primarily front end
Full
Primarily back end
Typical broad insurance spectrumNarrow spectrum Broader than insurance
Offering
Niche player Ecosystem orchestrator
White label back-office operator
Fully digitized universal insurer
� Possible to maintain margins
� Substantial reduction in scope� Global specialist incumbents
exist
� Possible to increase margins� Grow customer base through
increased intermediation� Highly challenging
� Build off core capabilities
� Thin margins and globalcompetition
� Substantial downsizing
� Constant downward pressure
on cost, impossible to keep margins
� Complexity challenges
The options for insurers: there are only a few real alternatives to an ecosystem orchestrator strategy
Today’s insurers Tomorrow’s insurers
17McKinsey & Company
What are the specific elements of digital?
Automation(Process redesign and enablement)
Connectivity (Online, Mobile, Social)
Decisioning(Big data, enterprise data)
Innovation (Idea factor)
Customer insight & advice
Mobile
Enterprisedata
New business models
Inno-vationculture
‘App’-Ification &
omni-channel
Social & ecosystem
100%imaging and STP
Real timeMIS
Advanced Analytics
Distribution transformati
on
Eco-system,
rapid digitizatio
n
▪ Regulatory compliance
▪ Single source of truth
▪ Personalized journeys
▪ UW
▪ Fraud detection
▪ ‘Fresh off the line’ reporting to key stakeholders
▪ Paperless
▪ Superior workflow
▪ Agent engagement
▪ Lead management
▪ Peer management
▪ Process apps enhancing customer experience, productivity, compliance
▪ Underwriting
▪ PR
▪ Inforce
▪ Mobile statements
▪ Mobile app
▪ Mobile engagement
▪ Customer need analysis
▪ Right place right time offer
▪ Innovation at scale
▪ Talent attraction
▪ 22nd century organization
▪ Peer to peer?
▪ Hook customeraacqusition ▪ Product embedded into others
▪ Benefits beyond insurance
18McKinsey & Company
If we were to redesign life insurance products based on consumer behaviors...
New world of insurance then should be revamp the design from the consumer design journey…
A Paperless end-to-end experience
B On the spot underwriting
C Modular approach in product designs
D “Whitespace” of insurance products
E Peer to peer insurance
F Low cost or free premium as “hook” to acquire
G Multi-offer propositions
H Direct to customers propositions
I Addressing customers holistic financial investment needs
J Trending into untraditional spaces to improve connectivity with customers
H Fully integrated to customer’s daily life via “ecosystem”
Consumers want the following features…
▪ Social
▪ Anywhere anytime access
▪ Pay for it as I need it
▪ Convenience
▪ Simplicity
▪ Personalization
19McKinsey & Company
In Insurance, Digital is expected to double the profits in some lines even after accounting for anticipated disruption in the long-term
SOURCE: Digital and Auto Insurers Value at Stake Analysis, McKinsey, 2016
1 Assumes a 3-5 p.p. improvement in loss ratio, a 2-4 p.p. improvement in operating expenses, and a 6-8 p.p. improvement in direct sales conversions2 Assumes a 25% reduction in premiums as a result of telematics and sensors and a 50% risk transfer to commercial product liability3 Includes growth in investment income as well premiums. Investment income modeled as a flat percentage of premium in each year
100220-300
Growth, loss, and
expense ratio
improvements1
120-200
Today’s profits
20-60
2035 Profits3
15-55
Shift in
liability to
commercial lines2
160-210
Loss and
expense ratio
improvements2
60-100
Impact from
improved
vehicle safety
(incl. semi-
and fully
autonomous
vehicles)2
2025 Profits3
Future profits as a percentage of today’s profits, %
Short-term improvement Long-term decline
In the short-term, higher customer satisfaction,
driven by the improved service and faster
processing times that digitization delivers, is
itself a driver of profit. At the same time, by
digitizing their existing business, carriers
can remove significant cost across the value
chain. Automation can reduce the cost of a
claims journey by as much as 30 percent
In the longer term, however, earnings from
traditional business will fall face headwinds
as driving becomes less risky owing to the
use of sensors and telematics or because, in
the case of autonomous cars, liability is
transferred to manufacturers
20McKinsey & Company
Relation between gross public replacement rate and retirement assets
Shift from public to private – as Pillar I solutions fail to cover pension needs, Pillar II and III are growing in importance
SOURCE: OECD Pensions at a Glance 2011, Assuralia, Allianz Asset management; IMF; World bank
1 As of 2012 2 As of 2010
Current developments of regulationGovernment debt as % of GDP2
30
80
90
160
10
100
70
60
100 200
8070605040
110
90
Gross Pillar I replacement rate1
Percent
Pil
lar
II
an
d P
illa
r I
II r
eti
re
me
nt
as
se
ts%
of G
DP
1
AU
CL
UK
US
BE
FRIT
ES
DE
NL
GR
CH2
• Increase in normal pension age from 65 to 67 for workers born after 1964
• Pension increase of 2.41% in 2009
• Civil servants´ contribution gradually rise from 7.85 to 10.55% by 2020
• Pension age increases from 60-65 to 62-67 (min rate – full rate) by 2017
• Withdrawal from Fonds de réserve pLife insu-ranceles retraites began in 2011 instead of 2020
• Automatic adjustment of pension to inflation suspended in 2010
• Payroll taxes during 2011 and 2012
• One-off payment of USD 250 to all public pension recipients in 2009
• Increased participation in occupational pension funds expected:
• Government introduced new Automatic Enrollment for individual retirement savings
• Individuals no longer required to convert 75% of DC plan assets into annuity at retirement
• Public pension contribution rates increased for the self-employed in the NDC2
• Pension age increase for women from 60 to 66 (in the public sector from 61 to 65) to match that of men by 2018
21McKinsey & Company
McKinsey & Company | 22
Many companies are facing critical employee engagement concerns that affect the bottom line
Job satisfaction rates are decreasing…
%
1987
%
2000
48484848%2013
% satisfied
…leading to higher turnover rates…
…and turnover costs are killing us
Total cost of turnover as a percentage of annual employee cost
SOURCE: BLS, The Conference Board, The Hay Group
%
2010
%
2014
Annual quits rate, not seasonally adjusted
23McKinsey & Company
2017 – the world’s most admired companies
24McKinsey & Company
A perfect storm for insurance?
Our evershifting customers
Digital as an opportunity: really?
Distribution: the big shift
War for talent: is insurance winning?
Public vs. private: new social contract?