eleventh edition global risk, profitability, and growth...

Risk. Reinsurance. Human Resources.

Aon Benfield

Global Risk, Profitability, and Growth MetricsCompanion volume to Global Insurance Market Opportunities

Insurance Risk Study | Eleventh Edition

Rating agencies, regulators, and investors today are demanding that insurers provide detailed assessments of their risk tolerance and quantify the adequacy of their economic capital. To complete such assessments requires a credible baseline for underwriting volatility. The Global Insurance Market Opportunities report provides our clients with an objective and data-driven set of underwriting volatility benchmarks by line of business and country as well as correlations by line and country. These benchmarks are a valuable resource to CROs, actuaries, and other economic capital modeling professionals who seek reliable parameters for their models.

Modern portfolio theory for assets teaches that increasing the number of stocks in a portfolio will diversify and reduce the portfolio’s risk, but will not eliminate risk completely; the systemic

market risk remains. This is illustrated in the left chart below. In the same way, insurers can reduce underwriting volatility by increasing account volume, but they cannot reduce their volatility to zero. A certain level of systemic insurance risk will always remain, due to factors such as the underwriting cycle, macroeconomic trends, legal changes and weather (right chart below). This study calculates this systemic risk by line of business and country. The Naïve Model on the right chart shows the relationship between risk and volume using a Poisson assumption for claim count—a textbook actuarial approach. The study clearly shows that this assumption does not fit with empirical data for any line of business in any country. It will underestimate underwriting risk if used in an ERM model.

Po

rtfo

lio r

isk

Insurance portfolio riskAsset portfolio risk

Number of stocks Premium Volume

Insu

ran

ce r

iskPortfolio Risk

SystemicMarket Risk

SystemicInsurance

Risk

Naïve Model

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Global Premium, Capital, Profitability, and Opportunity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Geographic Opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Global Risk Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

US Risk Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Macroeconomic, Demographic, and Social Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Global Correlation Between Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Sources and Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Contacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Contents

About the Study

Aon Benfield 1

The 2016 edition of Global Insurance Market Opportunities reports on our current risk environment, in addition to

the ability and willingness of insurers and capital providers to address the risks we face today. As in previous editions,

we pay close attention to the critical role of data and analytics in bridging the gap between risk and capital to create

viable insurance market solutions. This year, however, we build on that story and pay greater attention to the forces of

innovation and disruption that now confront the industry.

The study, now in its 11th year, has evolved from its

beginnings as a quantification study for enterprise risk

management. We now take an expansive view of issues

related to global risk to encompass global growth,

emerging risks, operational challenges, and this year, how

our industry can best capture the opportunities from

innovation and defend against the threats of disruption.

Analytics remains at the core of everything we do. The

Global Insurance Market Opportunities study continues

to provide the insurance industry’s leading set of risk

parameters for modeling and benchmarking underwriting

risk and global profitability. While the main study focuses

on the opportunities, this companion volume explains the

numbers—including the critical metrics and parameters

that insurers can use to advance their decision making

in areas ranging from growth strategy to performance

benchmarking, risk tolerance, and capital management. All

parameters are produced using a consistent methodology

that we have employed since the first edition of the study.

This volume begins with a review of insurance industry

performance globally: premium and capital levels, areas of

growth, and profitability. Since the 8th edition, industry

combined ratios are calculated across the top 50 countries.

Beginning with the Country Opportunity Index on page 5,

we turn from numerical highlights to strategic considerations

that identify the countries showing an attractive mix

of growth and profitability with limited political risk.

Page 9 focuses on risk parameters that can be used to

model underwriting volatility and insurance capital.

Using the Study

Beyond risk modeling, we can provide our clients with

very granular, customized market intelligence to create

business plans that are realistic, fact-based, and achievable.

With a global fact base and broad access to local market

practitioners, we are equipped to provide insight across a

spectrum of lines, products, and geographies. Inpoint, the

consulting division of Aon, helps insurers and reinsurers

address these challenges, from sizing market opportunities

to identifying distribution channel dynamics, assessing

competitor behavior, and understanding what it takes to

compete and win. Our approach leverages Aon’s USD 350

million annual investment in analytics, data, and modeling

to help our clients grow profitably. Please enjoy the articles

in the accompanying Global Insurance Market Opportunities

study, available from thoughtleadership.aonbenfield.com.

All of our work at Aon is motivated by client questions. We

continue to be grateful to clients who have invited us to

share in the task of helping them analyze their most complex

business problems. Dynamic and interactive working groups

always lead to innovative, and often unexpected, solutions. If

you have questions or suggestions for items we could explore

in future editions, please contact us through your local Aon

Benfield broker or one of the contacts listed on the last page.

Introduction

2 Insurance Risk Study

Globally, property casualty business again produced an underwriting profit in 2015 with a combined ratio of 98.6 percent, a slight deterioration from last year’s 97.0 percent combined ratio. The Americas averaged a 97.9 percent combined ratio, while Europe averaged 96.3 percent and Asia Pacific was highest at 103.1 percent.

In 21 of the top 50 markets, combined ratios were below

95 percent, and 12 countries were below 90 percent,

compared to 27 and 6 countries last year. Furthermore,

12 countries showed five-year premium growth in excess of 10

percent, led by very strong growth in China. The overall global

combined ratio result, and the variation in results by country,

demonstrate there are many desirable areas for profitable

growth in the market today.

At year-end 2015, global insurance premium stands at an all-

time high of USD 5.1 trillion, an increase of 1.8 percent over the

prior year. Property-casualty premium increased 0.6 percent,

life and health premiums by 2.5 percent, while reinsurance

premiums decreased by 2.9 percent.

Global insurance premium and capital, USD trillions

Premium Capital

Property & Casualty 1.4 1.4

Life & Health 3.5 2.4

Reinsurance 0.2 0.6

Total 5.1 4.3

Global capital increased 3.2 percent year on year to USD 4.3

trillion. Property casualty insurance capital increased

3.3 percent. Reinsurance capital decreased slightly, as we

discuss at greater length in Aon Benfield’s Reinsurance

Market Outlook.

Property casualty penetration is 2.0 percent of GDP based

on 50 of the largest countries, up from 1.9 percent last

year. Motor insurance accounts for 47 percent of property-

casualty premium, while property accounts for 32 percent

and liability 21 percent. This mix of business is nearly

unchanged from last year.

Motor insurance is also the fastest growing line of business,

with 4.2 percent annual growth over the last five years, driven

by strong growth in China, Brazil, Argentina, Venezuela,

and Saudi Arabia. Property is growing at an annual rate of

3.5 percent, and liability at 2.7 percent.

Global Premium, Capital, Profitability, and Opportunity

Motor: 7.2% annual growth

520

540

560

580

600

620

640

660

680

2012 2013 2014 20152011

USD

Bill

ion

s

Property: 4.9% annual growth

390

400

410

420

430

440

450

460

470

2012 2013 2014 20152011

USD

Bill

ion

s

Liability: 6.6% annual growth

240

250

260

270

280

290

300

310

2012 2013 2014 20152011

USD

Bill

ion

s

Global premium for motor

Global premium for property

Global premium for liability

Aon Benfield 3

Premium by product line

Notes: All statistics are the latest available. “Motor” includes all motor insurance coverages. “Property” includes construction, engineering, marine, aviation, and transit insurance as well as property. “Liability” includes general liability, workers compensation, surety, bonds, credit, and miscellaneous coverages.

U.S.44%

U.S.35%

Middle East & Africa

Rest of Europe

Rest of Euro Area U.K.Germany

France4%

Rest of APAC

South Korea

Japan

China13%

Rest of Americas

Canada

Motor: USD 666 billion

Property: USD 454 billion

Brazil

Middle East & Africa

Rest of Europe

Rest of Euro Area

U.K.

Germany

France4%

Rest of APAC

South KoreaJapan

China4%

Rest of AmericasCanada

Brazil

Liability: USD 302 billion

U.S.49%

Middle East& Africa

Rest of Europe Rest of Euro Area

U.K.

Germany

France3%

Rest of APAC

South KoreaJapan

China4%

Rest of AmericasCanada

Brazil

Five-year average annual growth rate

Property: 4.9% annual growth globally

Liability: 6.6% annual growth globally

Motor: 7.2% annual growth globally

-5%

0%

5%

10%

15%

20%

25%

30%

35%

Mid

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frica

Rest o

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-5%

0%

5%

10%

15%

20%

25%

30%

35%

Mid

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st & A

frica

Rest o

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Rest o

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aU.K

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Rest o

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-5%

0%

5%

10%

15%

20%

25%

30%

35%

Mid

dle Ea

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frica

Rest o

f Euro

pe

Rest o

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aU.K

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any

France

Rest o

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Japan

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Rest o

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Global P&C gross written premium and growth rates by product line




Top 50 P&C markets ranked by gross written premium by regionP&

C G

WP

(USD

M)

Prem

ium

/ G

DP

Rati

o

Annualized Premium Growth Cumulative Net Loss Ratio Cumulative Net Expense Ratio Cumulative Net Combined Ratio

1yr 3yr 5yr 1yr 3yr 5yr 1yr 3yr 5yr 1yr 3yr 5yr

Americas

US 578,231 3.2% 4.9% 4.7% 4.9% 70.9% 71.5% 73.2% 27.2% 27.3% 27.3% 98.1% 98.8% 100.4%

Canada 41,326 2.7% 3.4% 4.6% 6.4% 66.6% 67.0% 68.9% 29.7% 29.5% 29.1% 96.3% 96.5% 98.0%

Brazil 20,108 1.1% 4.6% 12.1% 12.1% 54.6% 53.0% 53.3% 34.5% 34.0% 34.0% 89.1% 87.0% 87.2%

Mexico 13,541 2.3% 42.7% 38.3% 36.1% 67.0% 70.9% 69.3% 38.4% 36.6% 37.1% 105.4% 107.5% 106.4%

Argentina 12,607 2.5% 79.9% 51.6% 41.8% 62.1% 60.8% 61.7% 34.2% 35.6% 34.8% 96.3% 96.4% 96.5%

Venezuela 10,321 0.9% 13.5% 7.7% 9.8% 57.3% 57.3% 59.7% 37.2% 34.8% 33.6% 94.5% 92.1% 93.2%

Colombia 3,786 1.3% 13.9% 9.5% 11.2% 60.2% 61.0% 60.7% 50.2% 48.9% 48.4% 110.4% 109.9% 109.1%

Chile 3,414 1.4% 10.8% 7.3% 10.5% 51.2% 51.8% 51.8% 40.8% 43.0% 42.6% 92.0% 94.8% 94.4%

Ecuador 1,812 1.8% 17.1% 14.9% 16.2% 54.4% 55.3% 54.3% 34.6% 35.2% 34.6% 89.0% 90.5% 88.9%

Subtotal 685,146 2 .8% 7 .2% 6 .6% 6 .6% 69 .7% 70 .1% 71 .7% 28 .2% 28 .3% 28 .2% 97 .9% 98 .4% 99 .9%

Europe, Middle East & Africa

Germany 74,442 1.9% 3.5% 3.6% 2.9% 72.0% 74.1% 74.5% 25.5% 25.0% 25.4% 97.5% 99.1% 99.9%

UK 66,292 2.3% -1.7% 0.3% 1.3% 61.8% 62.9% 64.9% 36.3% 35.4% 34.6% 98.1% 98.3% 99.5%

France 63,949 2.2% 1.3% 1.0% 0.8% 76.1% 75.3% 75.2% 23.4% 23.8% 24.2% 99.5% 99.2% 99.4%

Italy 36,117 1.7% -3.4% -4.1% -2.6% 69.3% 69.1% 71.6% 24.9% 24.5% 24.2% 94.2% 93.6% 95.7%

Spain 24,902 2.1% 2.8% -0.5% -0.9% 70.9% 71.3% 71.5% 20.6% 21.3% 21.1% 91.6% 92.6% 92.6%

Netherlands 14,927 1.7% -6.9% -3.2% -2.6% 87.5% 87.0% 86.6% 13.4% 12.6% 12.9% 100.9% 99.6% 99.5%

Switzerland 14,551 2.2% 0.2% -0.2% 1.2% 68.6% 66.9% 68.7% 27.0% 28.4% 27.7% 95.6% 95.3% 96.3%

Russia 12,330 0.9% 3.7% 8.4% 11.8% 64.7% 61.4% 62.9% 21.7% 27.9% 27.0% 86.4% 89.4% 89.9%

Belgium 11,700 2.2% 1.5% 2.4% 2.9% 67.9% 67.1% 68.8% 29.0% 28.5% 28.3% 96.9% 95.6% 97.1%

Austria 9,108 1.8% 5.3% 5.1% 4.3% 70.2% 70.7% 72.2% 15.1% 14.3% 15.1% 85.3% 85.0% 87.3%

Norway 8,666 2.5% 6.6% 8.0% 7.7% 57.6% 59.6% 60.5% 30.2% 28.9% 26.6% 87.8% 88.5% 87.1%

South Africa 8,432 2.3% 2.1% 1.8% 2.4% 69.3% 69.9% 70.3% 30.1% 27.9% 27.5% 99.5% 97.8% 97.8%

Turkey 8,143 1.4% 4.0% 3.5% 2.1% 71.7% 72.6% 73.1% 17.8% 18.4% 18.0% 89.5% 91.1% 91.1%

Denmark 7,869 1.1% 20.2% 15.2% 17.7% 75.6% 75.4% 75.9% 29.0% 26.8% 27.4% 104.6% 102.2% 103.3%

Sweden 7,807 2.6% -1.4% 3.2% 3.1% 73.3% 72.2% 74.9% 15.6% 17.0% 17.1% 89.0% 89.3% 92.0%

Poland 7,342 1.3% -1.6% 0.6% 4.2% 66.1% 63.5% 65.7% 29.5% 30.3% 30.8% 95.7% 93.9% 96.5%

Finland 4,684 2.0% 25.3% 12.0% 6.6% 81.0% 77.6% 79.9% 20.6% 20.4% 20.5% 101.6% 98.0% 100.4%

Israel 4,360 1.5% 10.3% 6.0% 4.3% 72.8% 73.3% 74.8% 28.8% 29.8% 30.7% 101.6% 103.1% 105.5%

Czech Republic 3,718 1.6% -0.5% -2.7% -2.7% 69.6% 73.1% 72.1% 23.0% 27.2% 25.1% 92.6% 100.3% 97.1%

Portugal 3,718 0.9% 4.6% -1.3% 0.7% 81.2% 74.6% 73.7% 21.6% 22.4% 21.1% 102.8% 97.0% 94.8%

Saudi Arabia 3,707 0.5% 20.5% 20.7% 17.0% 82.2% 85.1% 80.7% 13.7% 14.4% 16.2% 95.8% 99.4% 96.9%

U.A.E. 3,573 2.0% 5.6% 4.0% 1.7% 62.2% 62.6% 62.9% 32.6% 30.5% 29.9% 94.8% 93.2% 92.8%

Ireland 3,565 1.4% 3.8% -1.7% -2.9% 66.6% 72.0% 71.9% 30.4% 30.3% 29.8% 97.0% 102.3% 101.7%

Greece 2,682 1.1% -11.0% -4.9% -6.8% 55.6% 53.9% 55.7% 36.6% 39.1% 39.4% 92.2% 93.0% 95.1%

Romania 1,861 1.7% 4.0% 5.6% 6.2% 59.9% 58.9% 60.5% 34.3% 34.0% 34.0% 94.3% 92.9% 94.5%

Morocco 1,160 0.2% -1.7% 4.5% 3.8% 50.1% 50.2% 48.7% 30.9% 37.0% 36.2% 81.0% 87.1% 84.9%

Nigeria 1,067 1.7% -4.3% 4.4% 4.7% 67.8% 67.1% 66.3% 37.3% 37.3% 37.4% 105.1% 104.4% 103.7%

Luxembourg 916 0.5% -0.7% -23.7% -16.3% 72.8% 74.2% 73.5% 43.6% 54.2% 48.9% 116.4% 128.4% 122.5%

Bulgaria 914 1.6% -0.1% 0.4% -1.2% 55.3% 54.5% 54.8% 34.0% 33.8% 35.9% 89.3% 88.4% 90.7%

Subtotal 412,502 1 .8% 1 .7% 1 .8% 2 .0% 71 .1% 71 .3% 72 .2% 25 .2% 25 .4% 25 .1% 96 .3% 96 .7% 97 .3%

Asia Pacific

China 117,351 1.1% 15.8% 16.0% 20.2% 63.0% 63.0% 63.5% 32.8% 32.6% 32.4% 95.8% 95.6% 95.9%

Japan 78,972 1.7% 3.2% 4.3% 3.1% 75.7% 71.2% 71.5% 33.9% 33.3% 33.7% 109.7% 104.5% 105.2%

Australia 29,317 2.4% 2.6% 3.7% 6.6% 74.3% 66.7% 69.1% 27.6% 27.8% 27.5% 101.9% 94.4% 96.6%

S. Korea 16,945 1.2% 7.8% 3.7% 3.4% 80.5% 79.6% 78.8% 23.3% 23.6% 23.4% 103.8% 103.2% 102.2%

India 9,956 0.5% 6.9% 12.7% 16.6% 88.8% 84.3% 86.6% 28.9% 28.8% 29.6% 117.7% 113.0% 116.2%

Thailand 5,280 1.3% 0.9% 4.5% 9.7% 71.0% 69.4% 68.3% 36.3% 34.6% 35.2% 107.3% 104.1% 103.5%

Malaysia 3,897 1.3% 2.6% 5.0% 6.2% 62.4% 59.5% 61.4% 26.3% 27.6% 27.5% 88.7% 87.1% 88.9%

Taiwan 4,038 0.8% 4.5% 4.5% 5.2% 59.0% 57.4% 57.8% 37.1% 37.4% 37.6% 96.1% 94.8% 95.4%

New Zealand 3,539 2.1% 0.1% 6.0% 7.9% 98.5% 68.8% 83.3% 33.5% 34.9% 35.0% 132.0% 103.6% 118.2%

Indonesia 3,836 0.4% 19.9% 16.4% 14.6% 52.5% 53.0% 53.8% 32.8% 32.6% 32.9% 85.3% 85.6% 86.8%

Hong Kong 2,733 0.9% 3.0% 7.9% 6.4% 60.6% 60.8% 60.2% 33.1% 32.6% 33.0% 93.7% 93.4% 93.2%

Singapore 2,494 0.8% 1.3% 2.4% 3.8% 48.0% 51.1% 52.8% 36.6% 34.8% 34.3% 84.6% 85.9% 87.1%

Subtotal 278,358 1 .2% 9 .0% 9 .6% 11 .6% 72 .4% 69 .8% 70 .4% 30 .8% 30 .5% 30 .6% 103 .1% 100 .3% 101 .0%

Grand Total 1,376,006 2.0% 5.9% 5.7% 6.3% 70.9% 70.5% 71.6% 27.7% 27.6% 27.5% 98.6% 98.1% 99.1%

Aon Benfield 5

Aon Benfield created the Country Opportunity Index to identify countries with a desirable mix of profitability, growth potential, and a relatively stable political environment. The table below displays the 50 property casualty markets ranked by this Index and divided into quartiles.

Geographic Opportunities

Aon Benfield Country Opportunity Index

5yr Cumulative Net Combined Ratio

5yr Annualized Premium Growth

Real GDP 5yr Growth

Population 5yr Annualized Growth

Political Risk Assessment

Quartile 1

1 Malaysia** 88.9% 6.2% 7.2% 1.6% Medium Low2 Indonesia** 86.8% 14.6% 6.8% 1.4% Medium2 Singapore** 87.1% 3.8% 4.5% 1.5% Low4 Sweden 91.1% 2.1% 3.6% 1.1% Low5 Ecuador** 88.9% 16.2% 3.3% 1.6% Medium High5 Chile** 94.4% 10.5% 4.5% 1.1% Medium Low5 Mexico 93.2% 9.8% 4.0% 2.1% Medium5 South Africa* 87.1% 7.7% 3.0% 1.6% Medium5 Norway** 87.3% 4.3% 3.1% 1.1% Low5 Nigeria** 84.9% 3.8% 5.7% 2.8% High11 China 95.9% 20.2% 9.1% 0.5% Medium11 Saudi Arabia** 96.9% 17.0% 4.7% 2.4% Medium

Quartile 2

11 Brazil 87.2% 12.1% 0.8% 0.9% Medium11 Australia 96.6% 6.6% 4.1% 1.6% Low11 Hong Kong 93.2% 6.4% 3.8% 0.7% Low11 Morocco 94.5% 6.2% 5.3% 1.0% Medium11 U.A.E. 94.8% 0.7% 6.0% 3.0% Medium Low18 Russia 89.9% 11.8% 2.7% 0.5% Medium High18 Denmark 92.0% 3.1% 2.2% 0.4% Low20 India 116.2% 16.6% 8.1% 1.6% Medium20 Canada 98.0% 6.4% 3.3% 1.1% Low20 Luxembourg 103.7% 4.7% 4.5% 2.1% Low20 Switzerland 96.3% 1.2% 2.8% 1.2% Low24 Turkey 103.3% 17.7% 4.8% 1.1% Medium24 Colombia 109.1% 11.2% 5.2% 1.1% Medium

Quartile 3

24 New Zealand 118.2% 7.9% 4.3% 1.3% Low24 Taiwan 95.4% 5.2% 3.5% 0.3% Medium Low24 Israel 105.5% 4.3% 4.6% 1.9% Medium Low24 Poland 96.5% 4.2% 4.3% 0.0% Medium Low30 Venezuela 96.5% 41.8% -0.9% 1.6% Very High30 U.S. 100.4% 4.9% 3.6% 0.8% Low30 Germany 99.9% 2.9% 2.6% 0.6% Low30 Bulgaria 90.7% -1.2% 3.5% -0.6% Medium34 Finland 100.4% 6.6% 1.1% 0.4% Low34 Czech Republic 92.8% 1.7% 2.9% 0.1% Medium Low34 Spain 92.6% -0.9% 1.9% -0.2% Medium37 Argentina 106.4% 36.1% 2.3% 1.4% High

Quartile 4

37 South Korea 102.2% 3.4% 4.2% 0.4% Medium Low37 Belgium 97.1% 2.9% 2.2% 0.8% Medium Low37 Austria 97.8% 2.4% 2.1% 0.4% Low37 U.K. 99.5% 1.3% 3.5% 0.7% Medium Low37 Italy 95.7% -2.6% 0.7% 0.6% Medium43 Thailand 103.5% 9.7% 6.2% 0.4% Medium High43 France 99.4% 0.8% 2.1% 0.5% Medium Low43 Netherlands 99.5% -2.6% 2.1% 0.4% Low43 Ireland 101.7% -2.9% 5.7% 0.4% Medium47 Greece 95.1% -6.8% -0.9% -0.6% High48 Japan 105.2% 3.1% 2.2% -0.2% Medium Low48 Portugal 97.1% -2.7% 1.1% -0.3% Medium50 Romania 122.5% -16.3% 4.5% -1.5% Medium High

*Indicates top quartile performer in 2015. **Indicates top quartile performer in each year since 2013.Index methodology explained in Sources and Notes.

Nine of the 12 countries in

Quartile 1 were also in the

top quartile last year, and

eight have been in Quartile 1

for all four years of this Index.

Asian countries dominate the

top positions, but Quartile

1 also includes countries in

Latin America, Scandinavia,

Africa, and the Middle East.

Last year, Malaysia was

tied with Indonesia and

Singapore for the top

position—this year, the

country claims the number

one ranking. All three of

these countries have shown

low combined ratios,

healthy premium and

GDP growth, and a stable

political environment.

Sweden, Mexico, and China

entered the top quartile this

year—Sweden and Mexico on

improved growth metrics,

and China on improvements

in its combined ratio. Brazil,

Australia, and the United

Arab Emirates fell out of

the top quartile this year.

Note that the US, Japan, and

most of Western Europe

are in Quartiles 3 and 4.

This Index suggests that to

achieve strong insurance

growth, it is best for

insurers to look beyond the

developed economies.


Growth Markets and Out/Underperformers

To determine expansion opportunities we examined

premium growth and loss ratio performance by country

across motor, property, and liability lines of business as

well as premium growth and combined ratio performance

by country for all lines. The quadrant plots below

identify countries as either low growth or high growth,

and as either out performers or under performers.

To measure performance, the first three quadrant plots use loss

ratio for each line of business while the right-most plot shows

combined ratio for all lines of business. Each plot also provides

the gross written premium size, in USD millions, of each country.

For all quadrant plots, growth is determined based on five-

year annualized premium growth. Countries with values

greater than 7.5 percent are classified as high growth.

Loss ratio and combined ratio performance is determined

based on five-year cumulative loss ratio and five-year net

cumulative combined ratio, respectively. Each country’s

loss ratio performance is compared against its income level

peers, using a USD 30,000 GDP per capita split between

high income and low income countries; whereas, combined

ratio performance is compared against the global combined

ratio. Countries with five-year loss ratios lower than the

average of their income peers, or combined ratios below

the global combined ratio, are classified as outperformers.

Property

Loss ratio performance

Motor


Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

Australia 9,487Brazil 1,585China 10,916Colombia 910Ecuador 359India 1,781Indonesia 959Mexico 2,575New Zealand 412Poland 1,302Russia 1,386Saudi Arabia 288Turkey 457Venezuela 1,722

Bulgaria 34Canada 6,529Hong Kong 1,432Japan 14,160Malaysia 419Netherlands 4,250Nigeria 263Romania 70Singapore 807South Africa 991Switzerland 3,331Taiwan 430U.A.E. 1,222U.S. 147,128

Austria 1,657Belgium 3,384Czech Republic 995Denmark 873Finland 1,375France 10,216Germany 16,570Greece 360Ireland 848Israel 779Italy 5,447Luxembourg 160Morocco 463Norway 1,614Portugal 1,053S. Korea 1,856Spain 5,438Thailand 285U.K. 18,619

Argentina 5,599Chile 683Sweden 248

Brazil 6,078Canada 16,223Chile 1,689Colombia 1,211Ecuador 815India 2,249Luxembourg 372Mexico 2,968Russia 4,126Saudi Arabia 1,267South Africa 3,806Turkey 2,892Venezuela 1,765

Austria 3,300Belgium 3,654Bulgaria 214Greece 683Hong Kong 794Malaysia 1,404Morocco 314Nigeria 638Romania 186Singapore 754Switzerland 4,847Taiwan 1,146U.A.E. 1,111U.K. 24,244U.S. 200,646

Australia 9,347Czech Republic 967Denmark 4,088Finland 1,501France 27,331Germany 25,282Ireland 1,136Italy 7,323Japan 17,912Netherlands 5,460Norway 4,365Poland 1,815Portugal 998S. Korea 2,411Spain 8,761Sweden 4,502

Argentina 1,946China 16,601Indonesia 1,805Israel 1,181New Zealand 2,025Thailand 1,472

Brazil 12,446China 89,834Colombia 1,664Ecuador 638Hong Kong 507Indonesia 1,072Mexico 4,778South Africa 3,869Thailand 3,522Venezuela 9,120

Austria 3,475Denmark 2,846Greece 1,639Japan 46,901New Zealand 1,103Nigeria 259Norway 3,129Singapore 934Switzerland 6,374U.S. 230,457

Australia 10,483Belgium 4,662Bulgaria 666Canada 18,574Czech Republic 1,611Finland 2,156France 26,402Germany 32,590Ireland 1,582Israel 2,401Italy 23,348Luxembourg 535Malaysia 2,073Morocco 1,084Netherlands 5,218Poland 4,226Portugal 1,667Romania 659S. Korea 12,678Spain 10,702Sweden 3,392Taiwan 2,461U.A.E. 1,385U.K. 23,429

Argentina 5,997Chile 1,042India 5,927Russia 6,819Saudi Arabia 2,140Turkey 4,519

Brazil 20,108Chile 3,414China 117,351Ecuador 1,812Indonesia 3,836Mexico 10,321Russia 12,330Saudi Arabia 3,707South Africa 8,666Venezuela 12,607

Australia 29,317Austria 8,432Belgium 11,700Bulgaria 914Canada 41,326Czech Republic 3,573Denmark 7,807Greece 2,682Hong Kong 2,733Italy 36,117Malaysia 3,897Morocco 1,861Nigeria 1,160Norway 9,108Poland 7,342Portugal 3,718Singapore 2,494Spain 24,902Sweden 8,143Switzerland 14,551Taiwan 4,038U.A.E. 3,718

Finland 4,684France 63,949Germany 74,442Ireland 3,565Israel 4,360Japan 78,972Luxembourg 1,067Netherlands 14,927Romania 916S. Korea 16,945U.K. 66,292U.S. 578,231

Argentina 13,541Colombia 3,786India 9,956New Zealand 3,539Thailand 5,280Turkey 7,869

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers


















Aon Benfield 7

Twenty countries are high growth, loss ratio outperformers

in at least one line of business. Of these twenty countries,

five appear in each of the lines of business analyzed

as high growth out performers: Brazil, Colombia,

Ecuador, Mexico, and Venezuela. Intriguingly, all five

outperformers this year are Latin American candidates.

If we compare these countries on the basis of overall combined

ratio, four of the five are outperformers globally. The exception

is Colombia, which underperforms its peers with a five-year net

combined ratio of 109.1 percent, driven by an expense ratio

of nearly 50 percent. In addition to the four outperforming

countries mentioned above, six additional countries outperform

the global averages for both growth and profitability. China,

for instance, outperforms for both motor and liability insurance,

and its five-year combined ratio of 95.9 percent is better than

both the global average and the average among its Asia-Pacific

peers. See the Top 50 P&C Markets table for more details on

page 4. Using combined ratio in addition to loss history allows

us to further analyze and target high growth opportunities.

Liability


Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

















All Lines

Combined ratio performance

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers

Lowgrowth

Highgrowth

Out performers

Under performers



















The insurance business is always a tradeoff of assuming risk in exchange for potential—presumed—return. We now turn to the “risk” side of the risk and return equation. Measuring the volatility and correlation of risk has long been the hallmark of the study.

The 2016 edition of the Study quantifies the systemic risk

by line for 41 countries worldwide. By systemic risk, or

volatility, we mean the coefficient of variation of loss ratio

for a large book of business. Coefficient of variation (CV)

is a commonly used normalized measure of risk defined as

the standard deviation divided by the mean. Systemic risk

typically comes from non-diversifiable risk sources such

as changing market rate adequacy, unknown prospective

frequency and severity trends, weather-related losses,

legal reforms and court decisions, the level of economic

activity and other macroeconomic factors. It also includes

the risk to smaller and specialty lines of business caused by

a lack of credible data. For many lines of business systemic

risk is the major component of underwriting volatility.

The systemic risk factors for major lines by region appear

on the facing page. Detailed charts comparing motor and

property risk by country appear below. The factors measure

the volatility of gross loss ratios. If gross loss ratios are not

available the net loss ratio is used.

Global Risk Parameters

Coefficient of variation of gross loss ratio by country

ThailandMexico

ChilePhilippinesSingapore

PeruTaiwan

BrazilArgentinaIndonesia

Hong KongEcuador

VenezuelaNicaraguaColombiaHonduras

Dominican RepublicVietnam

South KoreaBolivia

PanamaPakistan

U.S.Turkey

El SalvadorMalaysia

JapanIndia

UruguayChina

SwitzerlandFrance

U.K.Canada

ItalyGermany

AustriaSouth AfricaNetherlands

DenmarkIsrael

PhilippinesHong Kong

NicaraguaIndonesiaSingapore

PanamaVenezuelaColombia

U.S.Honduras

South AfricaTurkey

PakistanIndia

VietnamCanada

DenmarkUruguay

Dominican RepublicU.K.Italy

ChinaMexico

PeruEcuador

ArgentinaIsraelBrazil

South KoreaBolivia

NetherlandsAustria

MalaysiaGermany

FranceSwitzerland

JapanEl Salvador

TaiwanChile

Thailand11%

9%

13%16%17%18%19%

21%21%21%

24%27%28%29%30%

34%37%

39%41%

43%43%43%44%

50%51%

45%46%

61%63%

67%68%68%

76%78%

83%85%

87%88%

98%107%108%

3%3%3%

5%6%7%8%8%9%9%9%9%9%10%10%11%11%11%11%12%13%13%13%13%14%14%14%14%

16%16%16%18%18%18%

20%20%22%

38%

26%27%

45%

Americas

Asia Pacific


Motor Property

8 countries were removed from the study this year due to a lack of new statutory data with which to update the analysis: Australia, Czech Republic, Greece, Hungary, Poland, Romania, Slovakia, and Spain.

Aon Benfield 9

Coefficient of variation of loss ratio for major lines by country

Mot

or

Mot

or—

Pe

rson

al

Mot

or—

C

omm

erci

al

Prop

erty

Prop

erty

—

Pers

onal

Prop

erty

—

Com

mer

cial

Gen

eral

Li

abili

ty

Acc

iden

t &

Hea

lth

Mar

ine,

A

viat

ion

&

Tra

nsit

Wor

kers

C

omp

ensa

tion

Cre

dit

Fid

elit

y

& S

uret

y

Americas

Argentina 11% 76% 84% 92% 196%

Bolivia 9% 43% 12% 44% 102%

Brazil 10% 78% 86% 93% 37% 96%

Canada 14% 21% 17% 33% 37% 39% 61% 69% 101%

Chile 3% 98% 69% 43% 69% 52%

Colombia 18% 51% 58% 40% 41% 70% 64%

Dominican Republic 13% 46% 49% 207%

Ecuador 11% 67% 100% 59% 69% 96%

El Salvador 5% 37% 16% 152%

Honduras 18% 50% 12% 106%

Mexico 11% 108% 60% 49%

Nicaragua 27% 61% 68% 172%

Panama 20% 43% 24% 150%

Peru 11% 85% 60% 19% 24% 135% 89% 104%

Uruguay 13% 28% 21% 302%

U.S. 18% 14% 23% 41% 44% 35% 38% 47% 37% 26% 63%

Venezuela 20% 63% 11% 151%

Asia Pacific

China 12% 27% 48% 26% 13% 18% 21% 39%

Hong Kong 38% 68% 81% 21% 63% 69%

India 14% 29% 8% 28%

Indonesia 26% 68% 125% 44% 79% 100% 128%

Japan 6% 30% 12% 9% 17% 11%

Malaysia 9% 34% 94% 38% 27% 104%

Pakistan 16% 43% 49%

Philippines 45% 88% 85% 96% 136%

Singapore 22% 87% 35% 52% 26%

South Korea 9% 44% 23% 60% 179%

Taiwan 3% 3% 83% 45% 16% 66% 79%

Thailand 3% 109% 121% 14% 27%

Vietnam 14% 45% 165% 50% 39% 42%


Austria 9% 17% 13% 48% 19% 11% 28% 41%

Denmark 14% 11% 13% 11% 18% 15% 24% 36%

France 8% 21% 27% 16% 30% 23% 37% 90%

Germany 8% 18% 19% 31% 25% 21% 17% 46%

Israel 10% 9% 20%

Italy 13% 19% 24% 19% 42% 21% 67%

Netherlands 9% 13% 28% 56% 30% 37%

South Africa 16% 16% 59% 47% 39%

Switzerland 7% 24% 16% 9% 46% 85%

Turkey 16% 16% 39% 39% 43% 16% 48% 58% 102%

U.K. 13% 13% 16% 21% 22% 25% 30% 15% 47%

Global Risk Parameters


For the US risk parameters of the Study, we use data from 20 years of NAIC annual statements for 2,799 individual groups and companies. Our database covers all 22 Schedule P lines of business and contains over 5 million records of individual company observations from accident years 1987-2015.

The chart below shows the loss ratio volatility for each Schedule P line, with and without the effect of the underwriting cycle.

The underwriting cycle effect is removed by normalizing loss ratios by accident year prior to computing volatility. This adjustment

decomposes loss ratio volatility into its loss and premium components.

Coefficient of variation of gross loss ratio (1987-2015)

The underwriting cycle acts simultaneously across many

lines of business, driving correlation between the results of

different lines and amplifying the effect of underwriting risk

to primary insurers and reinsurers. Our analysis demonstrates

that the cycle increases volatility substantially for all major

commercial lines, as shown in the table. For example, the

underwriting volatility of reinsurance liability increases by

60 percent and commercial auto liability by 32 percent.

Personal lines are more formula-rated and thus show a

lower cycle effect, with private passenger auto volatility

only increasing by 11 percent because of the cycle.

See page 58 of the 2015 Global Insurance Market Opportunities Study for a detailed description of how the underwriting cycle input is calculated.

US underwriting cycle impact on volatility

US Risk Parameters

Line of Business Impact

Reinsurance—Liability 60%

Other Liability—Claims Made 46%

Other Liability—Occurrence 44%

Medical PL—Claims Made 41%

Workers Compensation 38%

Special Liability 33%

Commercial Auto 32%

Commercial Multi Peril 22%

Homeowners 22%

Private Passenger Auto 11%

Financial Guaranty

Products Liability - Claims-Made

Special Property

Reinsurance - Property

Reinsurance - Financial

Reinsurance - Liability

International

Fidelity and Surety

Other

Products Liability - Occurrence

Homeowners

Medical PL - Claims-Made

Other Liability - Claims-Made

Special Liability

Other Liability - Occurrence

Warranty

Medical PL - Occurrence

Commercial Multi Peril

Workers' Compensation

Commercial Auto

Auto Physical Damage

Private Passenger Auto 14%13%

17%16%

23%18%

26%19%

33%33%

35%29%

36%30%

37%26%

37%28%

39%27%

42%29%

44%36%

44% 47%

48%37%

63%45%

68%22%

70%44%80%39%

84%53%

85%54%

93%41%

159%90%

All RiskNo Underwriting Cycle Risk

Aon Benfield 11

Macroeconomic, Demographic, and Social Indicators

Country GD

P—PP

P,

USD

bill

ions

GD

P 5y

r re

al g

row

th

Pop

ulat

ion—

m

illio

ns

Pop

ulat

ion

5yr

annu

aliz

ed g

row

th

GD

P Pe

r Cap

ita—

PP

P, U

SD

Gov

ernm

ent

cons

ump

tion

as

%

of G

DP

Act

ual i

ndiv

idua

l co

nsum

pti

on a

s

% o

f GD

P

Gen

eral

g

over

nmen

t deb

t as

% o

f GD

P

New

fore

ign

dir

ect

inve

stm

ent —

U

SD b

illio

ns

Infla

tion

rat

e

Une

mp

loym

ent

rate

Cor

por

ate

tax

rate

Polit

ical

ris

k as

sess

men

t

Aon

terr

oris

m r

isk

asse

ssm

ent

Wor

ld B

ank

rela

tive

ea

se o

f doi

ng

bus

ines

s

Argentina 972 2.3% 43.6 1.4% 22,303 11.2% 74.4% n/a 11.7 23.9% 7.8% 35.0% High Medium More difficult

Australia 1,178 4.1% 24.4 1.6% 48,196 16.0% 57.5% 19.5% 36.9 1.6% 5.9% 30.0% Low Low Easiest

Austria 413 2.1% 8.6 0.4% 48,098 17.9% 56.5% 47.5% 5.7 1.1% 6.2% 25.0% Low Negligible Easiest

Belgium 505 2.2% 11.4 0.8% 44,144 22.7% 56.9% 65.2% -20.7 -15.9% 8.3% 34.0% Medium Low Low Easiest

Brazil 3,101 0.8% 206.1 0.9% 15,049 18.8% 59.8% 42.9% 75.1 9.9% 9.2% 34.0% Medium Medium More difficult

Bulgaria 141 3.5% 7.1 -0.6% 19,839 25.7% 60.9% 1.5% 1.8 0.2% 8.6% 10.0% Medium Low Easiest

Canada 1,672 3.3% 36.2 1.1% 46,199 17.2% 55.7% 27.5% 63.2 1.6% 7.3% 26.5% Low Low Easiest

Chile 433 4.5% 18.2 1.1% 23,803 16.5% 62.0% -1.1% 20.5 5.4% 6.8% 24.0% Medium Low Medium Easiest

China 20,853 9.1% 1381.5 0.5% 15,095 12.8% 37.4% n/a 249.9 2.0% 4.1% 25.0% Medium Medium Easier

Colombia 691 5.2% 48.8 1.1% 14,171 16.6% 64.9% 42.2% 12.1 9.0% 9.8% 25.0% Medium High Easier

Czech Republic 344 2.9% 10.6 0.1% 32,600 26.0% 50.5% n/a 2.5 1.4% 4.7% 19.0% Medium Low Negligible Easiest

Denmark 265 2.2% 5.7 0.4% 46,704 24.5% 47.2% 9.3% 1.7 -23.4% 6.0% 22.0% Low Low Easiest

Ecuador 177 3.3% 16.5 1.6% 10,698 12.8% 61.4% n/a 1.1 2.4% 5.7% 22.0% Medium High Medium More difficult

Finland 229 1.1% 5.5 0.4% 41,690 24.4% 58.4% -42.5% 18.7 -18.1% 9.3% 20.0% Low Negligible Easiest

France 2,703 2.1% 64.6 0.5% 41,868 22.8% 56.8% 90.5% 42.9 -13.2% 10.1% 33.3% Medium Low Medium Easiest

Germany 3,935 2.6% 82.8 0.6% 47,536 17.8% 54.9% 46.7% 46.2 -13.7% 4.6% 29.7% Low Low Easiest

Greece 287 -0.9% 10.8 -0.6% 26,610 22.5% 71.3% 72.1% -0.3 -0.8% 25.0% 29.0% High Medium Easier

Hong Kong 428 3.8% 7.4 0.7% 58,128 25.2% 58.0% n/a 180.8 2.3% 3.2% 16.5% Low Low Easier

India 8,643 8.1% 1309.7 1.6% 6,599 10.7% 60.8% n/a 44.2 -49.9% 0.0% 34.6% Medium High More difficult

Indonesia 3,011 6.8% 258.8 1.4% 11,633 10.8% 53.9% n/a 15.5 3.9% 5.9% 25.0% Medium High More difficult

Ireland 273 5.7% 4.7 0.4% 58,373 13.5% 37.2% 71.6% 125.7 -8.1% 8.3% 12.5% Medium Low Easiest

Israel 293 4.6% 8.5 1.9% 34,336 23.3% 58.9% 62.6% 11.5 -0.6% 5.3% 25.0% Medium Low High Easier

Italy 2,213 0.7% 61.2 0.6% 36,191 17.8% 59.8% 111.8% 2.7 -16.0% 11.4% 31.4% Medium Low Easiest

Japan 4,901 2.2% 126.5 -0.2% 38,731 20.9% 59.9% 129.6% 0.0 -0.4% 3.3% 32.3% Medium Low Low Easiest

Luxembourg 58 4.5% 0.6 2.1% 100,991 16.3% 44.0% n/a 24.6 -19.1% 6.4% 29.2% Low Negligible Easier

Malaysia 860 7.2% 31.5 1.6% 27,278 15.8% 54.6% n/a 11.0 2.5% 3.2% 24.0% Medium Low Low Easiest

Mexico 2,303 4.0% 128.6 2.1% 17,906 19.3% 63.6% 48.6% 30.3 2.4% 4.0% 30.0% Medium Medium Easiest

Morocco 282 5.3% 33.8 1.0% 8,350 19.3% 56.3% 63.8% 3.2 1.6% 9.7% 31.0% Medium Low Easier

Netherlands 856 2.1% 17.0 0.4% 50,339 22.5% 44.1% 35.4% 68.7 -13.8% 6.4% 25.0% Low Low Easiest

New Zealand 173 4.3% 4.7 1.3% 36,950 19.6% 59.9% 7.4% -0.7 1.0% 5.9% 28.0% Low Negligible Easiest

Nigeria 1,128 5.7% 183.6 2.8% 6,143 8.1% 71.3% 12.8% 3.1 9.8% n/a 30.0% High Severe Most difficult

Norway 363 3.1% 5.3 1.1% 69,031 14.1% 34.5% -285.6% -9.9 2.7% 4.6% 25.0% Low Low Easiest

Poland 1,052 4.3% 38.0 0.0% 27,670 23.3% 61.8% 26.1% 6.3 -0.3% 6.9% 19.0% Medium Low Low Easiest

Portugal 297 1.1% 10.4 -0.3% 28,480 20.5% 65.6% 120.9% -1.3 -13.9% 11.6% 21.0% Medium Low Easiest

Romania 435 4.5% 19.9 -1.5% 21,916 22.3% 59.4% n/a 3.9 -2.0% 6.4% 16.0% Medium High Low Easiest

Russia 3,685 2.7% 146.3 0.5% 25,186 22.3% 59.4% n/a 4.8 6.1% 6.5% 20.0% Medium High Medium Easier

Saudi Arabia 1,720 4.7% 32.0 2.4% 53,728 20.1% 33.5% -31.0% 8.1 4.0% n/a 20.0% Medium High Easier

Singapore 485 4.5% 5.6 1.5% 86,854 10.0% 34.0% n/a 65.3 -0.3% 2.0% 17.0% Low Negligible Easiest

South Africa 735 3.0% 55.8 1.6% 13,166 19.1% 61.9% 46.2% 1.6 6.6% 26.1% 28.0% Medium Low Easier

South Korea 1,916 4.2% 50.8 0.4% 37,699 9.6% 79.8% 35.3% 5.0 0.4% 3.5% 24.2% Medium Low Low Easier

Spain 1,674 1.9% 46.3 -0.2% 36,143 18.9% 56.9% 66.2% 22.1 -14.2% 19.7% 25.0% Medium Low Easiest

Sweden 496 3.6% 10.0 1.1% 49,425 23.2% 50.3% -15.6% 15.9 1.8% 6.8% 22.0% Low Negligible Easiest

Switzerland 493 2.8% 8.3 1.2% 59,150 7.6% 49.1% 23.8% 119.7 2.2% 3.5% 0.0% Low Negligible Easiest

Taiwan 1,126 3.5% 23.6 0.3% 47,812 14.4% 58.0% 36.4% n/a -0.3% 3.8% 17.0% Medium Low Low Most difficult

Thailand 1,152 6.2% 69.0 0.4% 16,706 18.5% 61.1% n/a 8.0 -0.9% 0.8% 20.0% Medium High High Easier

Turkey 1,665 4.8% 78.6 1.1% 21,198 21.0% 60.0% 21.9% 16.8 10.9% 10.8% 20.0% Medium High Easier

U.A.E. 670 6.0% 9.9 3.0% 67,946 27.0% 73.2% -273.6% 11.0 5.2% 0.0% 55.0% Medium Low Low Easiest

U.K. 2,757 3.5% 65.6 0.7% 42,041 19.4% 63.4% 80.6% 39.5 -21.3% 5.0% 20.0% Medium Low Low Easiest

U.S. 18,558 3.6% 324.3 0.8% 57,220 11.3% 71.7% 82.2% 409.9 0.8% 4.9% 40.0% Low Low Easiest

Venezuela 479 -0.9% 31.4 1.6% 15,252 19.1% 94.8% n/a 3.8 555.2% 17.4% 0.0% Very High High Most difficult


Correlation between lines of business is central to a realistic assessment of aggregate portfolio risk, and in fact becomes increasingly significant for larger companies where there is little idiosyncratic risk to mask correlation. Most modeling exercises are carried out at the product or business unit level and then aggregated to the company level. In many applications, the results are more sensitive to the correlation and dependency assumptions made when aggregating results than to all the detailed assumptions made at the business unit level.

The Study determines correlations between lines within each country. Correlation between lines is computed by examining the

results from larger companies that write pairs of lines in the same country.

Aon Benfield Analytics has correlation tables for most countries readily available and can produce custom analyses of correlation

for many insurance markets globally upon request. As examples, tables for the US, UK, Colombia, and China appear below.

US

Hom

eow

ners

Priv

ate

Pass

eng

er A

uto

Com

mer

cial

M

ulti

Peri

l

Com

mer

cial

A

uto

Wor

kers

C

omp

ensa

tion

Oth

er L

iab

ility

- O

ccur

renc

e

Med

ical

PL

- C

laim

s M

ade

Oth

er L

iab

ility

- C

laim

s-M

ade

Prod

ucts

Li

abili

ty -

Occ

urre

nce

Homeowners 4% 28% 11% -7% 4% 5% 0% 16%

Private Passenger Auto 4% 13% 23% 42% 21% 29% 22% 24%

Commercial Multi Peril 28% 13% 52% 29% 51% 53% 45% 39%

Commercial Auto 11% 23% 52% 54% 60% 68% 43% 65%

Workers Compensation -7% 42% 29% 54% 48% 56% 52% 52%

Other Liability—Occurrence 4% 21% 51% 60% 48% 74% 56% 59%

Medical PL—Claims Made 5% 29% 53% 68% 56% 74% 69% 69%

Other Liability—Claims-Made 0% 22% 45% 43% 52% 56% 69% 28%

Products Liability—Occurrence 16% 24% 39% 65% 52% 59% 69% 28%

UK

Acc

iden

t &

Hea

lth

Com

mer

cial

Li

nes

Liab

ility

Com

mer

cial

M

otor

Com

mer

cial

Pr

oper

ty

Fina

ncia

l Los

s

Hou

seho

ld &

D

omes

tic

Priv

ate

mot

or

Accident & Health 41% 11% -28% 69% 41% 21%

Commercial Lines Liability 41% 14% -27% 56% 33% 33%

Commercial Motor 11% 14% -1% -11% 65% 47%

Commercial Property -28% -27% -1% -9% -14% 14%

Financial Loss 69% 56% -11% -9% 35% 34%

Household & Domestic 41% 33% 65% -14% 35% 26%

Private motor 21% 33% 47% 14% 34% 26%

Global Correlation Between Lines

Aon Benfield 13

Colombia

Acc

iden

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Cro

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Fid

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L

iab

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Mar

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Spec

ial

Liab

ility

Spec

ial

Prop

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Sure

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Accident & Health 22% 1% 22% 40% 4% 30% 18% 13% 25%

Crop & Animal 22% 3% 14% 30% 2% 42% 12% 11% 1%

Fidelity & Surety 1% 3% 40% 11% -5% 29% 10% 21% 18%

General Liability 22% 14% 40% 43% -7% 36% 17% 18% 16%

Marine, Aviation & Transit 40% 30% 11% 43% 8% 54% 35% 26% 45%

Motor 4% 2% -5% -7% 8% 8% 8% 17% 12%

Property 30% 42% 29% 36% 54% 8% 31% 24% 43%

Special Liability 18% 12% 10% 17% 35% 8% 31% 13% 38%

Special Property 13% 11% 21% 18% 26% 17% 24% 13% 14%

Surety 25% 1% 18% 16% 45% 12% 43% 38% 14%

China

Acc

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Hea

lth

Ag

ricu

lture

Cre

dit

Engi

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ing

Fina

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l G

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Gen

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Li

abili

ty

Mar

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A

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&

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sit

Mot

or

Oth

er

Prop

erty

Spec

ial R

isks

Accident & Health 39% 15% 9% 34% 11% 18% 26% 25% 20% -6%

Agriculture 39% 42% 12% 12% 32% 9% 9% 15% 27% -36%

Credit 15% 42% 6% 1% 7% 5% 14% 11% 14% -19%

Engineering 9% 12% 6% 16% 20% 13% 39% 34% 13% -9%

Financial Guaranty 34% 12% 1% 16% 20% -2% -3% 38% 22% 12%

General Liability 11% 32% 7% 20% 20% 22% 16% 26% 13% -13%

Marine, Aviation & Transit 18% 9% 5% 13% -2% 22% 26% 23% 3% -7%

Motor 26% 9% 14% 39% -3% 16% 26% 39% 23% -14%

Other 25% 15% 11% 34% 38% 26% 23% 39% 36% -49%

Property 20% 27% 14% 13% 22% 13% 3% 23% 36% 12%

Special Risks -6% -36% -19% -9% 12% -13% -7% -14% -49% 12%

Correlation is a measure of association between two random quantities. It varies between -1 and +1, with +1 indicating a perfect increasing linear relationship and -1 a perfect decreasing relationship. The closer the coefficient is to either +1 or -1 the stronger the linear association between the two variables. A value of 0 indicates no linear relationship whatsoever.

All correlations in the Study are estimated using the Pearson sample correlation coefficient.

In each table the correlations shown in bold are statistically different from zero at the 95 percent confidence interval.



Sources and Notes

Global Premium, Capital, Profitability & Opportunity Sources: A.M. Best, Axco Insurance Information Services, IMF World Economic Outlook Database April 2015 Edition, SNL Financial, Standard & Poor’s, World Bank

Notes: Premium amounts stated in USD are converted to USD by Axco. Growth rates are calculated in original currency and exclude currency exchange fluctuation.

Country Opportunity Index Calculation: For each combined ratio, growth and political risk statistic, countries were ranked and segmented into quartiles. A score of 1 to 4 was assigned to each metric based on quartile. Opportunity Index Score = one-third multiplied by combined ratio score plus two-thirds multiplied by average of premium, GDP and population growth and political scores. Ties were broken by premium growth.

Growth Markets and Out/Underperformers—Premium and growth calculated using Axco data. Loss ratios for motor, property and liability lines also calculated using Axco. “All lines” loss, expense, and combined ratios are calculated using A.M. Best’s Statement File–Global and are based on the net results of the largest 25 writers for a given country (where available).

Global Risk Parameters and US Risk Parameters Sources: ANIA (Italy), Association of Vietnam Insurers, BaFin (Germany), Banco Central del Uruguay, Bank Negara Malaysia, CADOAR (Dominican Republic), Cámara de Aseguradores de Venezuela, Comisión Nacional de Bancos y Seguros de Honduras, Comisión Nacional de Seguros y Fianzas (Mexico), Danish FSA (Denmark), DNB (Netherlands), Ernst & Young Annual Statements (Israel), Finma (Switzerland), FMA (Austria), FSA (UK), HKOCI (Hong Kong), http://www.bapepam.go.id/perasuransian/index.htm (Indonesia), Insurance Commission (Philippines), IRDA Handbook on Indian Insurance Statistics, Korea Financial Supervisory Service, Monetary Authority of Singapore, MSA Research Inc. (Canada), Quest Data Report (South Africa), SNL Financial (US), Superintendencia de Banca y Seguros (Peru), Superintendencia de Bancos y Otras Instituciones Financieras de Nicaragua, Superintendencia de Bancos y Seguros (Ecuador), Superintendencia de Pensiones de El Salvador, Superintendencia de Pensiones, Valores y Seguros (Bolivia), Superintendencia de Seguros de la Nación (Argentina), Superintendencia de Seguros Privados (Brazil), Superintendencia de Seguros y Reaseguros de Panama, Superintendencia de Valores y Seguros de Chile, Superintendencia Financiera de Colombia, Taiwan Insurance Institution, The Statistics of Japanese Non-Life Insurance Business, Undersecretariat of Treasury (Turkey), China Insurance Yearbooks, and annual financial statements

Macroeconomic, Demographic, and Social Indicators

Sources:

Aon Political Risk Map 2015, Aon Terrorism & Political Violence Map 2015, Axco Insurance Information Services, Bloomberg, IMF World Economic Outlook Database April 2015 Edition, KPMG, Penn World Table Version 8.1, World Bank

Notes: Table—GDP (PPP) is GDP in local currency adjusted using purchasing power parity (PPP) exchange rate into US dollars. The PPP exchange rate is the rate at which the currency of one country would need to be converted in order to purchase the same amount of goods and services in another country.


Sources:

FSA (UK), SNL Financial (US), Superintendencia Financiera de Colombia, and China Insurance Yearbook

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About Aon Benfield

© Aon Benfield Inc. 2016.All rights reserved. This document is intended for general information purposes only and should not be construed as advice or opinions on any specific facts or circumstances. This analysis is based upon information from sources we consider to be reliable, however Aon Benfield Inc. does not warrant the accuracy of the data or calculations herein. The content of this document is made available on an “as is” basis, without warranty of any kind. Aon Benfield Inc. disclaims any legal liability to any person or organization for loss or damage caused by or resulting from any reliance placed on that content. Members of Aon Benfield Analytics will be pleased to consult on any specific situations and to provide further information regarding the matters.

ContactsFor more information on the Global Insurance Market Opportunities study or our analytic capabilities, please contact your local Aon Benfield broker or:

Paul MangGlobal Chief Executive Officer of AnalyticsAon Benfield+65 6812 [email protected] Tracy HatlestadGlobal Chief Operating Officer of Analytics Aon Benfield+65 6512 [email protected] Greg HeerdeHead of Analytics & Inpoint, AmericasAon Benfield+1 312 381 [email protected]

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