tomorrow’s insurance - nat re · macro-trends: we are the engine of growth in global insurance...

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


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%


50

12

57

31

2009

Brazil

8McKinsey & Company

Marco trends – in mature markets, shrinking middle class

United States

Lowest

earning 40%

Middle 40%


Highest

earning 20%

2020E1

11

37

52

2011

12

37

51

ESTIMATES

Germany


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


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%


2020E1

19

2011

Lowest

earning 40%

Lowest

earning 40%

2020E12009

20

3839

41Highest

earning 20%

19

Middle 40%


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


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


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.


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


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


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


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


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

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


2017 – the world’s most admired companies


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?

tomorrow’s insurance - nat re · macro-trends: we are the engine of growth in global insurance...

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