Insurance Risk Study - Aon Benfieldthoughtleadership.aonbenfield.com/Documents/... · The 2013 Insurance Risk Study quantifies the systemic risk by line for 49 countries worldwide

Insurance Risk StudyEighth Edition 2013

Empower Results®

Insurance Risk Study

Contents

3 Foreword

5 Global Risk Parameters

8 U.S. Reserve Adequacy and Risk

10 Global Correlation between Lines

11 Macroeconomic Correlation

12 Global Premium, Profitability & Opportunities

29 Afterword: Extending Insurance-Linked Securities

33 Sources and Notes

35 Contacts

3

Aon Benfield

Foreword

One exciting prospect is the extension of ILS to other, largely non-catastrophe driven, perils. Such an extension requires capital market and investor acceptance of the underlying risk modeling — which is exactly the question the Aon Benfield Insurance Risk Study has been focused on since its inception in 2006. The Study provides data-driven parameters to put the modeling of non-catastrophe risk onto the same basis as catastrophe risk.

In fact, we can model many non-catastrophe lines of business very accurately, especially in combination with the sophisticated predictive models used by primary insurers to segment and price their business. We are actively engaged on this exciting prospect and believe the results over the next five years will be just as transformative as the convergence we have already witnessed for catastrophe risk. The Afterword explores non-catastrophe securitization in more detail.

For the industry, the downside of constrained volatility and manageable trends is the pressure it puts on growth. To help clients strategize and execute profitable growth, the 2013 Study provides a greatly expanded analysis of global insurance capital, premium and profitability.

The Study reveals a total of USD3.5 trillion of capital dedicated to insurance globally, with USD1.2 trillion supporting property casualty, USD1.8 trillion supporting life & health and USD0.5 trillion supporting reinsurance, catastrophe bonds and government pools. Global capital increased 7.0 percent year-over-year.

Global premium is USD4.9 trillion, an increase of 3.6 percent over the prior year. Property casualty accounts for USD1.4 trillion premium, with USD1.0 trillion health and USD2.5 trillion life. Global insurance penetration is now 6.8 percent of global GDP, up from 6.7 percent last year.

Property casualty penetration is 2.0 percent of GDP, up from 1.9 percent last year (based on the top 50 countries). Fully 45 percent of property casualty premium is related to auto insurance, 32 percent is property premium and 23 percent is liability premium. Auto insurance is also the fastest growing segment globally, with premiums increasing 7.3 percent year-over-year, helped by substantial growth in China, followed by property at 5.9 percent, with liability lagging at only 0.6 percent.

2013 is a watershed year for the insurance industry. We have seen the often-anticipated convergence of capital markets and insurance markets become a reality for property catastrophe risk. An influx of pension fund, high-net worth individual, hedge fund and other capital has made it as cheap, or cheaper, to transfer catastrophe risk into the capital markets than through traditional reinsurance. The reduction in cost of capital for fully collateralized, unlevered debt-like insurance-linked securities (ILS) has been so significant in 2013 that it more than offset the differential to traditional equity vehicles using a higher leverage and a higher cost of capital. As we have reported in our July 1 Reinsurance Market Outlook, and again in our forward looking September publication, convergence has been driven by declines in the risk margin on ILS transactions of between 30 percent and 50 percent since January 1, 2013. Looking forward, the obvious question becomes: what is next?

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Catastrophe losses have been a driver of the growth in property premiums in many parts of the world. Impact Forecasting, Aon Benfield’s catastrophe model development center of excellence, estimates that during 2012 insured catastrophe losses totaled USD72 billion. In perspective, catastrophe losses represented 0.1 percent of GDP, translating into 5.3 percent of property casualty premium and a “global catastrophe load” of 16.6 percent of property premium. Over the last five years insured catastrophe losses have averaged 17.0 percent of property premium globally. As well as tracking global catastrophe events through its monthly catastrophe reports, Impact Forecasting also builds a licensable suite of global catastrophe models that are customizable to reflect client experience. The model suite encompasses more than 40 peril-geography models and includes fully stochastic Thailand and U.S. flood models.

In addition to reporting premium growth, penetration and loss ratio statistics, the new Study provides a much more granular analysis of insurance profitability. For the first time we are reporting combined ratios by country in order to identify potential growth opportunities more accurately. The detailed analysis pulls together a number of data sources and was cross-validated against individual company results. To the best of our knowledge, Aon Benfield is the first to publish these statistics.

We have also included six in-depth country studies to highlight our detailed screening approach to identify potential growth opportunities. The country studies combine demographic, economic, sociological, and political information with insurance data insights and, crucially, real-time feedback from Aon’s local broking teams. We have included studies on Canada, Colombia, Indonesia, Malaysia, Mexico, and Turkey. The analysis demonstrates the need for local on-the-ground knowledge, in addition to a review of market statistics, in order to make a truly informed decision about global expansion.

Starting from the information in the Study, Aon Benfield can provide its clients with very granular, customized market intelligence to create business plans that are realistic, actionable, fact-based, and achievable. Our approach, from sizing the market opportunity by identifying distribution channel dynamics, assessing competitor behavior and understanding what it takes to compete and win, leverages our USD130 million annual investment in analytics, data and modeling to help our clients grow profitably.

The Aon Benfield Insurance Risk Study continues to be the industry’s leading set of risk parameters for modeling and benchmarking underwriting risk and global profitability. It is part of a suite of capabilities that help position Aon Benfield as a true business partner for insurers on questions of risk management, growth and operational performance. The Study is a cornerstone of Aon Benfield Analytics’ integrated and comprehensive risk modeling and risk assessment capabilities. Our reinsurance optimization framework, explicitly linking reinsurance and capital, and quantifying the resulting volatility reduction, relies on the Study for a credible assessment of baseline risk factors. And extending from underwriting risk we provide ERM and economic capital modeling services through the ReMetrica® software platform, both using the Study to benchmark risk, quantify capital adequacy and allocate capital to risk drivers. In addition, the massive database underlying the Study is supported by more than 450 local professionals within Aon Benfield Analytics’ global team who are available to work with you to customize the basic parameters reported in the Study to answer your specific business questions.

All of our work within the Analytics team 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 back page.

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Aon Benfield

ThailandPeru

MexicoTaiwanGreece

PhilippinesSingaporeIndonesia

BrazilHong Kong

Dominican RepublicRomania

NicaraguaSlovakia

ColombiaPakistan

ArgentinaPanama

HondurasEcuador

U.S.Vietnam

South KoreaEl SalvadorVenezuela

UruguayHungary

ChinaIndia

PolandJapan

FranceMalaysia

TurkeyNetherlands

ChileBolivia

CanadaU.K.

SwitzerlandItaly

AustriaSpain

AustraliaGermany

South AfricaIsrael

Denmark

PhilippinesGreece

NicaraguaHong Kong

RomaniaPanamaEcuador

DenmarkIndonesia

SlovakiaVenezuelaHondurasSingapore

ChinaEl Salvador

PeruU.S.

South AfricaVietnamMalaysia

U.K.Argentina

CanadaPoland

Dominican RepublicColombia

PakistanBrazilChile

NetherlandsIndiaItaly

UruguayTurkeyBolivia

MexicoCzech Republic

GermanySpain

AustriaSwitzerland

AustraliaHungary

South KoreaTaiwanFranceJapanIsrael

Thailand14%

12%

15%16%16%17%17%18%20%21%22%23%25%25%26%27%27%

33%33%34%34%34%35%37%38%

43%43%

42%42%

45%46%47%

51%53%53%55%57%

61%62%

65%66%68%70%

77%84%

93%

134%

4%5%5%6%7%7%8%8%8%8%8%9%9%9%10%11%11%12%12%12%12%13%13%13%13%14%14%14%14%15%15%15%16%16%17%17%18%18%

22%

18%22%

23%22%

46%

25%37%

41%

50%64%

Americas Asia Pacific Europe, Middle East & Africa

96%

Motor Property

Global Risk Parameters

The 2013 Insurance Risk Study quantifies the systemic risk by line for 49 countries worldwide. Systemic risk, or volatility, in the Study is 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 page 7. 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.

Coefficient of Variation of Loss Ratio by Country

6


U.S. Underwriting CycleThe 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 other liability claims made increases by 52 percent and commercial auto liability by 38 percent. Personal lines are more formula rated and thus show a lower cycle effect, with private passenger auto volatility only increasing by 7 percent because of the cycle.

Impact of Underwriting Cycle on Coefficient of Variation

Line of Business Impact of Pricing Cycle

Other Liability - Claims-Made 52%

Reinsurance - Liability 51%

Other Liability - Occurrence 43%

Workers Compensation 41%

Commercial Auto Liability 38%

Medical PL - Claims-Made 35%

Special Liability 29%

Commercial Multi Peril 15%

Homeowners 15%

Private Passenger Auto 7%

U.S. Risk ParametersThe U.S. portion of the Insurance Risk Study uses data from 12 years of NAIC annual statements for 2,363 individual groups and companies. The database covers all 22 Schedule P lines of business and contains 1.85 million records of individual company observations from accident years 1992-2012.

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

14%

17%

24%

27%

30%

36%

36%

38%

39%

40%

43%

47%

47%

54%

67%

71%

72%

85%

93%

96%

100%

137%

13%

16%

17%

19%

31%

37%

31%

26%

30%

26%

32%

41%

35%

50%

44%

50%

56%

57%

62%

59%

50%

101%Financial Guaranty

Special Property

Products Liability – Claims-Made

Reinsurance – Financial

Reinsurance – Property

International

Fidelity and Surety

Reinsurance – Liability

Other

Homeowners

Products Liability – Occurrence

Medical PL – Claims-Made

Other Liability – Claims-Made

Special Liability

Other Liability – Occurrence

Commercial Multi Peril

Medical PL – Occurrence

Warranty

Workers’ Compensation

Commercial Auto

Auto Physical Damage

Private Passenger Auto

Financial Guaranty

Special Property

Products Liability – Claims-Made

Reinsurance – Financial

Reinsurance – Property

International

Fidelity and Surety

Reinsurance – Liability

Other

Homeowners

Products Liability – Occurrence

Medical PL – Claims-Made

Other Liability – Claims-Made

Special Liability

Other Liability – Occurrence

Commercial Multi Peril

Medical PL – Occurrence

Warranty

Workers’ Compensation

Commercial Auto

Auto Physical Damage

Private Passenger Auto

Coefficient of Variation of Gross Loss Ratio | 1992–2012

All Risk No Underwriting Cycle Risk

7

Aon Benfield

Coefficient of Variation of Loss Ratio for Each Line by Country

Reported CVs are of gross loss ratios, except for Argentina, Australia, Bolivia, Chile, Ecuador, India, Malaysia, Singapore, Thailand, Uruguay and Venezuela, which are of net loss ratios.Accident & Health is defined differently in each country; it may include pure accident A&H coverage, credit A&H, and individual or group A&H. In the U.S., A&H makes up about 80 percent of the “Other” line of business with the balance of the line being primarily credit insurance.

Property volatility statistics include catastrophe losses.

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Americas

Argentina 14% 47% 57% 29% 9% 274%

Bolivia 10% 23% 16%

Brazil 13% 65% 50% 72% 70% 49% 45% 72%

Canada 14% 22% 17% 35% 34% 40% 65% 104% 89%

Chile 12% 25% 49% 58% 23% 52%

Colombia 13% 53% 68% 25% 16% 76%

Dominican Republic 13% 61% 86% 72%

Ecuador 23% 43% 51% 92%

El Salvador 17% 38% 15% 97%

Honduras 18% 45% 10% 243%

Mexico 9% 93% 63% 44%

Nicaragua 46% 55% 58% 170%

Panama 25% 46% 18% 99%

Peru 16% 96% 65% 23% 23% 130%

Uruguay 11% 35%

U.S. 16% 14% 24% 43% 47% 36% 38% 54% 39% 27% 71%

Venezuela 18% 37% 20% 230%

Asia Pacific

Australia 8% 16% 23% 32% 54% 10% 30%

China 17% 16% 34% 51% 38% 26% 20% 16% 69%

Hong Kong 41% 62% 86% 22% 65% 78%

India 12% 34% 13% 30%

Indonesia 22% 29% 66% 132% 52% 65% 87% 123%

Japan 5% 33% 11% 10% 18% 7%

Malaysia 15% 27% 119% 30% 36% 89%

Pakistan 13% 51% 36%

Philippines 64% 70% 72% 74% 87% 163%

Singapore 18% 68% 41% 75% 40%

South Korea 7% 7% 42% 33% 52%

Taiwan 7% 7% 84% 50% 23% 73% 79%

Thailand 4% 134% 134% 17% 34%

Vietnam 15% 42% 38% 11% 30%

Europe, Middle East & Africa

Austria 8% 17% 13% 49% 21% 13% 20% 50%

Czech Republic 9%

Denmark 22% 12% 15% 15% 18% 18% 27% 25%

France 6% 27% 30% 28% 36% 23% 60%

Germany 9% 16% 17% 29% 26% 17% 19% 51%

Greece 50% 77% 83% 84%

Hungary 8% 34%

Israel 5% 14% 56%

Italy 12% 18% 25% 19% 43% 42% 64%

Netherlands 12% 25% 25% 51% 34% 33%

Poland 14% 33%

Romania 37% 57% 88%

Slovakia 22% 53%

South Africa 15% 15% 67% 35% 39%

Spain 8% 8% 17% 12% 21% 33% 13% 33% 46% 112%

Switzerland 8% 20% 22% 11% 50% 81%

Turkey 11% 8% 26% 26% 38% 12% 61% 80%

U.K. 14% 14% 19% 21% 22% 25% 32% 4%

8


U.S. Reserve Adequacy and Risk

U.S. Reserve Estimated Adequacy and Development Summary (USD billions)

LineEstimated Reserves

Booked Reserves

Remaining Redundancy

at YE 2012

Favorable or (Adverse) DevelopmentYears at

Run Rate2008 2009 2010 2011 2012 Average

Personal Lines 129.6 139.7 10.1 5.4 5.8 6.7 7.6 7.1 6.5 1.6

Commercial Lines 437.8 436.9 (0.9) (3.5) 12.8 3.9 5.1 2.8 4.2 N/A

Commercial Property 45.2 47.2 2.0 2.6 2.4 2.7 1.4 1.1 2.1 1.0

Commercial Liability 232.6 235.6 2.9 5.3 3.8 2.4 4.1 2.5 3.6 0.8

Workers’ Compensation 142.1 138.2 (3.9) 1.1 (0.5) (1.6) (0.0) (0.1) (0.2) N/A

Financial Guaranty 17.8 15.9 (1.9) (12.6) 7.0 0.4 (0.4) (0.6) (1.3) N/A

Total 567.4 576.6 9.2 1.8 18.5 10.5 12.7 9.9 10.7 0.9

Reserve releases in the U.S. are now in their seventh consecutive year, heightening concerns that insurers are cutting reserves too aggressively. We can form an independent opinion about the adequacy of statutory reserves using the high quality, uniform data at the legal entity available through the NAIC Schedule P in statutory accounts. These accounts provide U.S. regulators with a clear view into insurance companies and are part of a very effective system of solvency regulation based on consistent and transparent reporting.

Four years ago Aon Benfield started publicly tracking the reported reserve adequacy of U.S. companies. Each year we analyze the aggregated net loss development data by Schedule P line of business. Working at an aggregate level allows our actuaries to use different methods and to weight the results in different ways than is possible for company actuaries who are working with smaller and less stable data

sets. Unlike some other public studies, each of our reports has called for continued reserve releases by the industry — predictions that have been borne out by subsequent facts.

The table below summarizes the analysis of the year end 2012 data. The analysis indicates an overall redundancy of USD9.2 billion, or 1.6 percent of total booked reserves, compared to USD11.7 billion at year end 2011. However, a closer inspection of the results shows a fundamental shift in the view of reserve adequacy on the commercial lines sector.

The analysis reveals that commercial lines moved to an overall deficiency position of USD0.9 billion at year end 2012 compared to an estimated USD4.1 billion redundancy at year end 2011. Within the commercial lines sector, reserve adequacy deteriorated in commercial liability, workers’ compensation and financial guaranty, with only property lines experiencing an improvement in reserve adequacy.

Year-over-Year Change in Reserve AdequacyThe drivers of year-over-year change in our reserve estimates are illustrated in the waterfall charts on the next page.

In 2011, we estimated the property & casualty industry reserve redundancy was USD11.7 billion. During calendar year 2012 the industry released USD9.9 billion of reserves. Offsetting the impact of reserve releases were two factors: 2012 calendar year favorable loss emergence and redundantly booked reserves in the 2012 accident year. The development of case incurred losses in calendar year 2012 contributed to a decrease in ultimate loss estimates of USD3.3 billion while the 2012 accident year contributes an additional USD4.1 billion of reserve redundancy. The sum of these pieces drives our year end 2012 redundancy estimate of USD9.2 billion.

When we separate the year-over-year waterfall into personal and commercial lines a different picture emerges. For personal lines, a reduction in booked reserves during the 2012 calendar year is more than offset by favorable loss emergence on the prior years and redundancy in the 2012 accident year. However, for commercial lines, the calendar year 2012 reserve releases are not offset by favorable loss emergence or a conservative 2012 accident year. This results in a slight negative overall position for commercial lines.

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Aon Benfield

U.S. Reserves Looking ForwardWe estimate that companies will continue to release reserves through year end 2013, possibly extinguishing overall redundancy in the industry. In the first three months of 2013, companies have already released an additional USD5.6 billion of reserves, compared to USD4.2 billion in 2012. USD3.8 billion of this release is from personal lines, while commercial lines continued to decrease USD1.6 billion. The release in personal lines may be attributable to conservatism in booked results at year end 2012 related to Superstorm Sandy.

With a reduced equity in reserves going forward, mistakes in underwriting, rate monitoring and primary pricing will no longer be covered up by a reserve cushion. Compounding this issue are continued low investment returns.

As we have discussed in prior Insurance Risk Studies, understanding reserve risk is critical for effectively modeling company solvency. It is also a notoriously difficult problem: whereas all companies face broadly similar insurance risks, such as weather, legal, social, and medical trends, each company’s reserving practices are idiosyncratic. Moving forward, rate adequacy and rate monitoring — not on an aggregate premium basis but on a rate per exposure basis — will be critical to the operating results of companies. Aon Benfield Analytics has developed effective models of industry loss drivers for some U.S. lines and continues to work to expand its understanding of macro drivers across all classes of business. We can also assist clients with exposure adjusted rate monitoring in this challenging reserve and investment environment.

0

2

4

6

8

10

12

14

2011 Year End Reserve Redundancy/Deficiency

2012 Calendar Year Change in Booked Reserves

2012 Calendar Year Favorable/Adverse Loss Emergencies

2012 Accident Year Redundancy/Deficiency

2012 Year End ReserveRedundancy/Deficiency

+9.2+4.1

+3.3

(9.9)+11.7

Drivers of 2012 Reserve Redundancy or Deficiency (USD billions)

All Lines

0

2

4

6

8

10

12

2011 Year End Reserve Redundancy/Deficiency


2012 Calendar Year Favorable/Adverse Loss Emergencies

2012 Accident Year Redundancy/Deficiency

2012 Year End ReserveRedundancy/Deficiency

+10.1+5.6

+4.0

(7.1)+7.6

0

-2

2

4

6

8

10

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2011 Year End Reserve Redundancy or (Deficiency)


2012 Calendar Year Favorable or (Adverse)

Loss Emergencies

2012 Accident Year Redundancy or (Deficiency)

2012 Year End ReserveRedundancy or (Deficiency)

(0.9)(1.4)(0.8)

(2.8)+4.1

Personal Lines

Commercial Lines

10


Global Correlation between Lines

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 are 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 other countries readily available and can produce custom analyses of correlation for many insurance markets globally upon request.

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 90 percent confidence level.

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Accident & Health 40% 18% 15% 20% 19% 32% 55%

Agriculture 40% 42% 9% 38% 16% 6% 11%

Credit 18% 42% 24% 11% 15% 27% 21%

Engineering 15% 9% 24% 25% 13% 48% 27%

General Liability 20% 38% 11% 25% 25% 26% 31%

Marine, Aviation & Transit 19% 16% 15% 13% 25% 31% 9%

Motor 32% 6% 27% 48% 26% 31% 37%

Property 55% 11% 21% 27% 31% 9% 37%

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Accident & Health 25% 70% 36% -15% 20% 21%

Commercial Lines Liability 25% 43% 36% 17% 49% 37%

Commercial Motor 70% 43% 41% -11% 16% 67%

Commercial Property 36% 36% 41% -18% 70% 32%

Financial Loss -15% 17% -11% -18% 3% -30%

Household & Domestic 20% 49% 16% 70% 3% 17%

Private Motor 21% 37% 67% 32% -30% 17%

11

Aon Benfield

Macroeconomic Correlation

Correlation among macroeconomic factors is a very important consideration in risk modeling. The interaction of inflation and GDP growth with loss ratios and investment returns has a profound effect on insurer financial health and stability.

The following matrix shows correlation coefficients for various macroeconomic variables impacting an insurer’s balance sheet, based on U.S. statistics.

The Consumer Price Index and Producer Price Index are highly correlated, but they do not show particularly strong correlation with other factors. This may be because inflation has been relatively tame for the last 25 years.

GDP growth shows strong negative correlation with changes in unemployment. When GDP drops — or unemployment increases — credit spreads tend to increase, property values fall and the VIX increases.

Treasury yields and corporate bond spreads are inversely correlated; financial market fears may push investors to flee corporates for the safety of Treasuries, causing corporate yields to rise and Treasury yields to fall.

The VIX is sensitive to fear and directionally has the appropriate signs: positive correlation with spreads and unemployment, negative correlation with GDP and equity returns.

These coefficients represent only the beginning of an analysis of macroeconomic dependency. Lags may be appropriate among certain variables. For example, GDP and equity returns show the strongest correlation when equity returns lead GDP by two quarters, suggesting that equity prices adjust as soon as expectations for GDP change, consistent with the Efficient Market Hypothesis.

It is also important to consider values that shift over time. In successive eight-quarter periods, equity returns and property returns showed zero or negative correlations until the recent financial crisis when correlations turned strongly positive. Subsequent to the financial crisis this correlation has once again tempered. This fact alone suggests that a simplistic view of correlation among macroeconomic factors will significantly underestimate material balance sheet risks.

U.S. Macroeconomic Correlations

Infla

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(CPI

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Inflation (CPI-U) 78% -2% 0% 32% 23% -12% -24% -13% -21% 9%

Inflation (PPI) 78% 5% -6% 28% 6% -6% -18% -7% -21% 7%

GDP Growth -2% 5% -57% -1% 27% -62% -70% 5% -42% 49%

Unemployment Change 0% -6% -57% 12% 26% 47% 39% -4% 44% -36%

3-Month T-Bill Rate 32% 28% -1% 12% 98% -21% -55% -8% -17% 12%

1-3 Year Treasuries 23% 6% 27% 26% 98% -23% -55% 9% -18% 9%

AAA-AA 3-5 Year Spread -12% -6% -62% 47% -21% -23% 82% -43% 62% -63%

BBB 3-5 Year Spread -24% -18% -70% 39% -55% -55% 82% -34% 66% -52%

S&P 500 Returns -13% -7% 5% -4% -8% 9% -43% -34% -52% 15%

VIX -21% -21% -42% 44% -17% -18% 62% 66% -52% -33%

Property Returns 9% 7% 49% -36% 12% 9% -63% -52% 15% -33%

12


Global Premium, Profitability & Opportunities

Abundant post-convergence capital, providing a lower cost alternative to traditional equity risk financing, reinvigorates the growth imperative. After many years of catastrophe risk management (often implemented as exposure reductions) clients are now looking more aggressively for innovative growth opportunities to leverage the new capacity. Aon Benfield Analytics has worked through a mass of market data from many different sources to produce the consistent, country-level profitability statistics we introduce in this section to help guide growth decisions.

In addition to important market profitability information, our access to Aon Benfield brokers, product experts and placement data allows us to work effectively with clients to prioritize among market opportunities. Our strategic decision framework identifies accessible markets and high potential customer segments to formulate growth programs tailored to an insurer’s capabilities and risk appetite. Working with our broker network and our investment bank, Aon Benfield Securities, Inc., we can develop and help execute growth plans through organic growth, acquisition, reinsurance, and joint ventures, singly or in combination.

Insurance demand increases with economic growth and prosperity. As disposable income and wealth increase, customer demand for insurance also increases, and often at a faster rate. Property accumulations create demand for catastrophe protections and a more developed legal system

can lead to greater liability exposures. The graph below shows per capita spending on property casualty insurance increasing more quickly than income across countries. The growth implications are clear and well-known: focus on growing economies and they account for the industry interest in China and other Asian economies as well as Brazil. Growth, of both the economy and the population, combined with political stability are three of our key socio-economic filters.

Another driver of insurance growth is increasing insurance penetration, through an increase in the ratio of premium to GDP. The table on page 13 shows a ranking of the top 50 economies by property casualty premium spend. This group has an average insurance penetration of 2.0 percent. The top 5 countries have a penetration of 2.3 percent. If all 50 countries moved to at least 2.0 percent insurance penetration, then global premium would increase by 20.5 percent, to USD1.6 trillion, and the top 50 countries would be realigned as shown in the far right table. Achieving increased penetration by developing insurance products valuable to emerging economies represents a great growth opportunity for the industry.

The remainder of this section presents our detailed analysis of U.S. profitability by line; global premium, profitability and demographic statistics; and then explores growth opportunities for a selected group of countries.

Premium per Capita vs Income per Capita for Top 50 P&C Markets

5

50

500

5,000

500 5,000 50,000 500,000

log

Pre

miu

m p

er C

apit

a (U

SD)

log GDP per Capita (USD)

Individual Countries Top 50 Aggregate

y = 0.0008x1.2881 R = 89.8%

Prem

ium

per

Cap

ita

GDP per Capita

13

Aon Benfield

Top 50 P&C Markets by Gross Written Premium

Country P&C

GW

P (U

SD b

illio

ns)

GD

P

(USD

bill

ions

)

Pop

ulat

ion

(mill

ions

)

Prem

ium

/

GD

P Ra

tio

GD

P p

er

Cap

ita

U.S. 503.7 15,684.8 314.2 3.2% 49,922

Japan 92.4 5,948.3 127.6 1.6% 46,613

China 84.5 8,230.1 1,354.0 1.0% 6,078

Germany 66.9 3,389.6 81.9 2.0% 41,379

U.K. 64.7 2,443.6 63.2 2.6% 38,637

France 63.5 2,600.3 63.4 2.4% 41,008

South Korea 53.3 1,155.9 50.0 4.6% 23,114

Canada 41.9 1,817.6 34.8 2.3% 52,190

Italy 38.3 2,007.6 60.8 1.9% 33,008

Australia 34.1 1,534.3 22.8 2.2% 67,396

Spain 28.8 1,347.7 46.2 2.1% 29,194

Brazil 24.4 2,257.7 198.4 1.1% 11,382

Russia 18.6 2,021.9 141.9 0.9% 14,247

Netherlands 14.5 770.6 16.8 1.9% 45,994

Switzerland 14.5 637.6 8.0 2.3% 79,683

Belgium 11.9 483.1 11.1 2.5% 43,545

Norway 10.6 500.9 5.0 2.1% 99,428

Argentina 10.4 476.2 41.0 2.2% 11,606

Mexico 9.3 1,177.1 114.9 0.8% 10,247

Austria 9.2 397.3 8.5 2.3% 46,930

India 8.4 1,824.7 1,223.2 0.5% 1,492

Sweden 8.4 526.6 9.5 1.6% 55,197

Denmark 8.3 313.8 5.6 2.6% 56,221

Turkey 7.8 792.8 74.9 1.0% 10,587

Poland 7.2 485.7 38.9 1.5% 12,488

South Africa 5.8 384.3 51.2 1.5% 7,507

Venezuela 5.3 382.4 29.5 1.4% 12,954

Thailand 4.9 365.6 64.4 1.3% 5,679

Finland 4.4 249.3 5.4 1.8% 45,949

Colombia 4.3 364.5 46.6 1.2% 7,823

Malaysia 4.3 303.4 29.5 1.4% 10,300

Ireland 3.9 209.7 4.6 1.9% 45,744

Israel 3.8 240.5 7.7 1.6% 31,247

Czech Republic 3.8 196.0 10.6 1.9% 18,577

Chile 3.7 268.2 17.4 1.4% 15,410

U.A.E. 3.7 359.2 5.5 1.0% 64,882

Portugal 3.6 212.0 10.5 1.7% 20,113

Taiwan 3.6 473.9 23.3 0.8% 20,325

New Zealand 3.4 170.2 4.4 2.0% 38,338

Indonesia 3.3 878.0 244.5 0.4% 3,592

Greece 3.3 248.4 11.3 1.3% 21,984

Hong Kong 2.5 262.9 7.2 0.9% 36,651

Saudi Arabia 2.4 727.3 29.0 0.3% 25,085

Singapore 2.4 276.4 5.4 0.9% 51,147

Romania 1.8 169.3 21.3 1.0% 7,931

Morocco 1.6 97.4 32.5 1.7% 2,994

Ecuador 1.3 80.9 15.2 1.6% 5,311

Nigeria 1.1 275.1 164.8 0.4% 1,670

Luxembourg 1.0 56.6 0.5 1.7% 106,910

Bulgaria 0.9 51.0 7.3 1.7% 7,036

Grand Total 1,315.2 66,128.8 4,966.2 2.0% 13,316

U.S.

Middle East & Africa

Rest of Europe

Rest of Euro AreaU.K.

Germany

France

Rest of APAC

South Korea

Japan

China

Rest of Americas

CanadaBrazil

U.S.


Rest of EuropeRest of Euro Area

U.K.

Germany

France

Rest of APAC

South KoreaJapan

ChinaRest of Americas

CanadaBrazil

U.S.


Rest of Europe Rest of Euro AreaU.K.

Germany

France

Rest of APAC

South Korea

Japan

ChinaRest of Americas

CanadaBrazil

Global P&C Gross Written Premium by Product LIne

Motor: USD614 billion

Property: USD433 billion

Liability: USD312 billion

Note: Ranks are based on total P&C Gross Written Premium

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.

Top 50 P&C Markets Assuming at Least Two Percent Penetration

Country P&C

GW

P (U

SD b

illio

ns)

U.S. 503.7

China* 163.7

Japan 118.3

Germany 67.4

U.K. 64.7

France 63.5

South Korea 53.3

Brazil* 44.9

Canada 41.9

Russia* 40.2

Italy 39.9

India* 36.3

Australia 34.1

Spain 28.8

Mexico* 23.4

Indonesia* 17.5

Turkey* 15.8

Netherlands 15.3

Saudi Arabia* 14.5

Switzerland 14.5

Belgium 11.9

Norway 10.6

Sweden 10.5

Argentina 10.4

Poland 9.7

Taiwan* 9.4

Austria 9.2

Denmark 8.3

South Africa 7.6

Venezuela 7.6

Thailand 7.3

Colombia 7.2

U.A.E.* 7.1

Malaysia 6.0

Singapore* 5.5

Nigeria* 5.5

Chile 5.3

Hong Kong* 5.2

Finland 5.0

Greece* 4.9

Israel 4.8

Portugal 4.2

Ireland 4.2

Czech Republic 3.9

New Zealand 3.4

Romania 3.4

Morocco 1.9

Ecuador 1.6

Luxembourg 1.1

Bulgaria 1.0

Total 1,585.2

* Ranking increased by insurance penetration

14


U.S. Profitability by Line of BusinessThe 2013 Insurance Risk Study contains a new detailed analysis of profitability for the 50 largest property & casualty country markets. In many areas of the world profitability data are both scarce and coarse. In the U.S., however, the NAIC statutory financial statements provide a wealth of detailed information summarizing profitability of property & casualty insurance by company, line of business and geography, so we begin our analysis there.

The table below summarizes current net premium volume and net accident year loss ratio, expense ratio and combined ratio over the last 10 years. The last five columns summarize individual company 10 year combined ratios at the 10th, 25th, 50th, 75th, and 90th percentiles. The percentiles are computed on a premium weighted basis.

Over the past 10 accident years the property & casualty industry achieved a 98 percent combined ratio. However, insurance companies between the 25th and 75th percentiles had combined ratios ranging from 92 percent to 103 percent, illustrating that there is ample opportunity for individual companies to outperform average results.

The magnitude of the opportunity to outperform varies by line of business. For example, top quartile auto physical damage writers achieved at least an 89 percent combined ratio, which is 5 points better than the industry average. However, in other liability top quartile writers outperformed the industry by at least 10 points. Clearly, when considering new underwriting opportunities, average profitability is only part of the story.

Net Premium Volume and Net Loss Ratio, Expense Ratio and Combined Ratio over Last 10 Years, U.S. Statutory Entities

Line of Business

2012 Net Earned Premium

USD millions

Net Accident Year Loss

Ratio 10yr

Net Expense Ratio 10yr

Net Combined Ratio 10yr

10yr Combined Ratio Percentiles

10% 25% 50% 75% 90%

Private Passenger Auto Liability 102,285 77% 25% 102% 95% 97% 103% 105% 106%

Auto Physical Damage 68,813 69% 25% 94% 82% 89% 95% 101% 102%

Homeowner & Farmowners 67,976 74% 30% 105% 95% 100% 105% 105% 113%

Workers' Compensation 37,750 74% 24% 98% 88% 93% 100% 106% 111%

Special Property 34,786 62% 28% 90% 76% 81% 89% 100% 108%

Medical Professional Liability 33,485 66% 26% 92% 80% 87% 92% 99% 104%

Commercial Multiple Peril 30,676 64% 34% 99% 88% 91% 100% 106% 108%

Commercial Auto Liability 16,761 68% 30% 97% 88% 93% 97% 100% 105%

Reinsurance 15,165 66% 26% 93% 79% 87% 87% 92% 101%

Other Liability 14,609 65% 28% 93% 83% 83% 95% 96% 102%

Other (Inc Credit, Accident & Health) 8,564 72% 35% 106% 90% 97% 97% 106% 109%

Fidelity & Surety 5,926 39% 46% 85% 67% 77% 85% 87% 96%

Special Liability 5,787 57% 32% 89% 74% 84% 88% 93% 109%

Financial Guaranty 5,636 146% 25% 171% 118% 132% 151% 152% 245%

Product Liability 2,406 63% 26% 89% 69% 80% 86% 98% 107%

Warranty 1,671 73% 25% 98% 80% 80% 98% 103% 109%

International 102 74% 36% 110% 66% 73% 94% 116% 116%

All Lines 452,396 71% 27% 98% 90% 92% 98% 103% 104%

15

Aon Benfield

Whether exploring growth organically or through mergers and acquisitions, an effective strategy depends on how companies underwrite. Many companies strive to be known for their underwriting and to produce top quartile or top decile results. The previous page showed that top quartile or decile companies outperform the average by a wide margin in any given year. But given the vagaries of insurance risk, is it possible to outperform year after year?

Our research indicates sustained out-performance is achievable, with nearly two-thirds of top quartile companies sustaining that top position after one year. Digging deeper, 57 percent of top decile underwriters across all lines are still leaders one year later — but on the flip-side, 56 percent of bottom decile underwriters remain on the bottom. By chance only 10 percent of companies would remain top tier after one year, so these are very significant results. More importantly, the results persist over time. After five years 37 percent of top decile performers are still top tier (and 33 percent stay bottom tier).

The persistence is somewhat lower by individual line of business, in part reflecting the fact that top tier performers shift their portfolios over time. For example, 37 percent of top performers for workers’ compensation and commercial auto, 36 percent for medical malpractice and 32 percent for homeowners stay as top tier performers, but only 25 percent for commercial multi-peril and 24 percent for private passenger auto do so.

The tables below show the proportion of companies by decile of underwriting performance moving into each decile after one year (left) and five years (right). A high decile rank corresponds to a high combined ratio. For example, 57 percent of top tier companies stayed top tier after one year, while 19 percent moved into the second to top tier (top row). On the other hand, 56 percent of bottom decile companies stayed bottom decile, 15 percent moved to second worst, and 6 percent moved to third (lower row).

Over five years, 37 percent of top tier companies stayed top tier after one year, while 15 percent moved into the second top tier (top row). On the other hand, 33 percent of bottom decile companies stayed bottom decile, 12 percent moved to second worst, and 7 percent to third (lower row).

These results show that underwriting excellence is possible and sustainable over the longer term. Excellence requires the best underwriting and pricing tools, used in a disciplined and effective manner.

The results on underwriting excellence are in contrast to the results on premium growth. There we see only 22 percent of high growth companies remaining high growth after one year. And after five years the results show very little deviation from random chance, with the fastest growing companies being spread almost evenly by growth decile five years later. Top performing companies know they must manage a dynamic portfolio, shifting growth and mix of business over time in order to achieve top tier underwriting performance.

Five Year Transition Matrix — All Lines Combined Ratio

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

10% 37% 15% 10% 6% 4% 5% 4% 3% 6% 11%

20% 10% 19% 15% 12% 9% 7% 6% 6% 8% 9%

30% 8% 12% 13% 12% 14% 10% 11% 6% 9% 6%

40% 5% 11% 12% 12% 13% 12% 10% 11% 8% 6%

50% 5% 7% 8% 12% 15% 15% 14% 11% 8% 5%

60% 3% 6% 9% 13% 13% 14% 14% 11% 11% 6%

70% 4% 5% 8% 10% 11% 11% 15% 16% 13% 6%

80% 5% 8% 10% 9% 9% 14% 10% 16% 13% 7%

90% 8% 9% 8% 8% 9% 9% 10% 13% 14% 12%

100% 15% 9% 7% 5% 3% 4% 6% 7% 12% 33%

One Year Transition Matrix — All Lines Combined Ratio

10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

10% 57% 19% 7% 3% 2% 2% 2% 2% 2% 6%

20% 17% 34% 19% 9% 6% 3% 3% 3% 3% 4%

30% 6% 16% 26% 21% 12% 6% 4% 3% 2% 2%

40% 5% 10% 18% 23% 18% 9% 5% 4% 5% 2%

50% 3% 5% 12% 20% 21% 16% 9% 5% 5% 3%

60% 2% 4% 6% 10% 17% 23% 17% 11% 6% 4%

70% 1% 3% 3% 5% 11% 20% 24% 19% 11% 4%

80% 1% 2% 3% 4% 5% 10% 22% 27% 20% 5%

90% 3% 3% 2% 4% 3% 7% 10% 20% 32% 15%

100% 5% 3% 3% 2% 3% 3% 4% 6% 15% 56%

Underwriting Outperformance in the Long Run

Decile at End of Period Decile at End of Period

Dec

ile a

t St

art

of P

erio

d

Dec

ile a

t St

art

of P

erio

d

Top Performers 10% 100% Worst Performers

16


Developing a Robust Growth StrategyThe market statistics Aon Benfield presents in the Study are the initial steps to develop a growth strategy. The diagram below shows the detailed screening process Aon Benfield employs to identify potential markets that can be explored for realistic growth opportunities.

First, we evaluate basic insurance economics: profitability, scale and growth. We consider a number of perspectives: country market scale and insurance penetration; country loss ratio, expense ratio and combined ratio over one, three and five year time periods, and five year loss ratio volatility (page 17); growth and loss ratio out- and underperformance by line and overall combined ratio performance (pages 18 and 19). We include scale as a measure to account for the need of today’s larger companies to leverage their management time and intellectual capital over an appropriately large growth opportunity.

The next step is to understand the country landscape more thoroughly. We review demographics: is the country’s population growing or shrinking? Does the country have a well developed legal system and a politically stable environment in which to foster a multi-year insurance investment? These statistics are shown on page 20. We include insurance regulation as a screen. What are the minimum capital requirements and how is it regulated? Can insurance be operated via a branch or is a full subsidiary required? What are the rating agencies’ views?

Then, we combine these fact-based questions with qualitative feedback from detailed broker surveys of Aon’s local teams. What are they seeing as the under-served opportunities in each country? What potential acquisition targets do they anticipate coming to market over the next 12 to 24 months? What is the appropriate strategy for management to signal to local business leaders their interest in growing, and how should those important introductions be made?

Finally, the outcome of this detailed screening process identifies potential markets as realistic growth opportunities. For illustrative purposes in this study, Aon Benfield selected six contender countries to demonstrate our approach. After factoring the quantitative statistics, it is crucial to consider the qualitative factors, for example, the existing footprint and management expertise. As a result, not all selected countries are top quartile performers. All are, however, active locations of expansion, as evidenced by the mergers and acquisitions activity we tabulate (page 25).

Profitability

Scale

Growth

Demographics

Political Stability

Regulation

Broker Surveys

Contender Geographies Deep dive on strategy, organic growth and M&A opportunities

17

Aon Benfield

Top 50 P&C Markets Ranked by Gross Written Premium by RegionP&

C G

WP

(U

SD m

illio

ns)

Prem

ium

/

GD

P Ra

tio

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

5yr C

omb

ined

Ra

tio

CV

Country

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

Americas

U.S. 503,657 3.2% 4.8% 2.9% 1.0% 78.4% 74.7% 73.4% 27.1% 27.1% 26.8% 105.5% 101.9% 100.2% 4.2%Canada 41,860 2.3% 13.3% 9.1% 4.7% 70.8% 72.1% 70.4% 28.3% 28.6% 28.4% 99.1% 100.7% 98.8% 3.9%Brazil 24,408 1.1% -3.9% 13.8% 11.1% 53.5% 55.1% 56.3% 36.4% 33.1% 28.8% 89.9% 88.2% 85.2% 4.8%Argentina 10,400 2.2% 18.5% 21.7% 20.0% 67.0% 66.6% 65.6% 42.9% 39.7% 40.2% 109.9% 106.3% 105.8% 2.4%Mexico 9,307 0.8% 2.2% 7.8% 4.2% 71.4% 68.7% 69.1% 33.7% 33.6% 33.8% 105.0% 102.3% 102.9% 2.4%Venezuela 5,292 1.4% -27.9% -2.5% 15.8% 62.1% 64.4% 65.3% 34.2% 32.0% 31.8% 96.3% 96.4% 97.1% 1.3%Colombia 4,318 1.2% 15.9% 19.2% 14.1% 59.6% 59.9% 60.7% 46.7% 47.2% 46.6% 106.3% 107.2% 107.3% 1.9%Chile 3,719 1.4% 7.1% 22.5% 15.7% 51.2% 52.4% 51.7% 40.8% 43.6% 44.2% 92.0% 96.0% 95.9% 3.3%Ecuador 1,328 1.6% 11.2% 15.7% 17.4% 51.6% 53.0% 53.5% 32.7% 33.4% 33.5% 84.3% 86.4% 87.1% 4.1%Subtotal 604,289 2.7 4.8% 4.1% 2.1% 76.2% 73.4% 72.3% 28.2% 28.0% 27.4% 104.4% 101.4% 99.8% 3.9%

Europe, Middle East & Africa

Germany 66,941 2.0% -0.4% 0.2% 1.1% 75.3% 75.1% 73.6% 25.8% 25.3% 25.1% 101.0% 100.4% 98.7% 2.7%U.K. 64,732 2.6% 4.3% -3.3% -1.4% 68.2% 67.4% 67.0% 33.6% 34.1% 34.2% 101.9% 101.5% 101.2% 1.2%France 63,472 2.4% 10.5% -0.5% 3.9% 73.2% 75.6% 74.2% 24.3% 24.8% 24.5% 97.5% 100.4% 98.6% 3.1%Italy 38,316 1.9% -10.2% -3.7% -2.7% 74.9% 76.8% 75.3% 25.0% 24.1% 23.9% 99.9% 100.9% 99.2% 3.1%Spain 28,812 2.1% -9.4% -5.2% -3.4% 71.0% 72.0% 71.3% 20.7% 21.0% 21.0% 91.7% 93.0% 92.3% 1.4%Russia 18,574 0.9% 18.1% 15.2% 9.7% 64.7% 67.4% 66.7% 21.9% 21.0% 20.3% 86.6% 88.4% 87.0% 3.3%Netherlands 14,517 1.9% 0.7% -2.5% 2.9% 88.1% 88.1% 87.6% 13.1% 13.1% 13.6% 101.2% 101.2% 101.2% 0.6%Switzerland 14,456 2.3% -1.8% 7.5% 7.3% 72.7% 70.8% 71.9% 26.0% 26.1% 26.1% 98.7% 96.8% 98.0% 2.2%Belgium 11,882 2.5% 4.1% 0.7% 3.7% 70.4% 72.8% 72.1% 28.1% 27.6% 27.9% 98.5% 100.4% 99.9% 1.4%Norway 10,553 2.1% 12.4% 8.9% 5.4% 74.9% 75.0% 75.2% 15.6% 16.1% 16.5% 90.5% 91.1% 91.7% 2.6%Austria 9,160 2.3% -5.1% 0.1% 1.1% 70.4% 71.3% 70.5% 30.8% 29.2% 28.8% 101.2% 100.4% 99.3% 1.7%Sweden 8,392 1.6% 12.4% 0.6% 2.8% 75.0% 73.5% 73.6% 17.6% 17.4% 17.6% 92.6% 90.9% 91.2% 1.6%Denmark 8,254 2.6% -5.6% 0.2% 1.4% 76.9% 78.2% 76.4% 16.5% 17.2% 17.2% 93.4% 95.4% 93.7% 3.7%Turkey 7,755 1.0% 7.9% 1.6% 7.3% 77.3% 77.2% 77.1% 27.9% 28.8% 26.5% 105.2% 106.0% 103.6% 3.4%Poland 7,157 1.5% -6.7% 5.8% 3.8% 66.3% 69.2% 64.2% 29.8% 31.1% 32.9% 96.1% 100.2% 97.1% 4.1%South Africa 5,813 1.5% -20.3% 1.4% 0.3% 60.9% 63.3% 64.0% 25.7% 25.2% 24.5% 86.6% 88.6% 88.5% 2.3%Finland 4,422 1.8% -2.7% 1.6% 2.2% 85.7% 80.8% 80.1% 20.7% 20.7% 20.3% 106.4% 101.6% 100.4% 3.7%Ireland 3,909 1.9% -2.9% -6.6% -3.4% 71.2% 72.2% 71.1% 26.7% 28.5% 27.6% 97.8% 100.7% 98.7% 5.8%Israel 3,816 1.6% 7.9% 2.4% 5.6% 76.3% 77.6% 78.2% 32.5% 31.7% 31.0% 108.8% 109.3% 109.3% 0.3%Czech Republic 3,770 1.9% -11.3% -2.5% 0.8% 62.5% 64.2% 62.7% 29.5% 28.6% 26.6% 91.9% 92.8% 89.3% 5.3%U.A.E. 3,699 1.0% 4.0% 2.7% 12.3% 76.7% 70.8% 70.2% 18.9% 17.9% 15.8% 95.5% 88.7% 85.9% 7.2%Portugal 3,597 1.7% -2.4% -5.6% -3.7% 69.6% 70.8% 69.3% 23.0% 22.7% 22.8% 92.6% 93.5% 92.1% 2.5%Greece 3,251 1.3% -2.2% -1.2% 5.7% 56.2% 61.7% 64.0% 38.1% 37.1% 38.7% 94.3% 98.7% 102.7% 6.7%Saudi Arabia 2,400 0.3% 14.1% 12.5% 11.6% 72.5% 71.0% 71.5% 21.1% 19.8% 19.0% 93.6% 90.8% 90.4% 2.3%Romania 1,768 1.0% -9.4% -8.8% -5.1% 73.7% 74.5% 76.4% 44.3% 37.9% 35.1% 118.0% 112.3% 111.4% 3.1%Morocco 1,637 1.7% 2.7% 8.1% 10.1% 63.1% 64.6% 66.8% 34.6% 33.9% 33.4% 97.7% 98.4% 100.2% 3.0%Nigeria 1,136 0.4% 8.5% 2.1% 12.3% 48.0% 47.8% 47.2% 30.9% 31.2% 31.8% 79.0% 79.0% 78.9% 1.4%Luxembourg 982 1.7% 7.3% 1.3% -11.1% 63.6% 64.8% 63.2% 37.2% 37.9% 36.3% 100.9% 102.7% 99.5% 5.2%Bulgaria 852 1.7% -9.6% -5.5% -0.3% 55.3% 54.8% 54.0% 34.0% 36.3% 35.7% 89.3% 91.1% 89.7% 3.0%Subtotal 414,024 1.9 0.9% -0.5% 1.3% 73.4% 74.1% 73.3% 24.7% 24.6% 24.6% 98.1% 98.7% 97.9% 1.2%

Asia Pacific

Japan 92,376 1.6% 13.5% 9.0% 6.3% 75.7% 70.0% 68.6% 33.9% 34.5% 34.5% 109.7% 104.5% 103.0% 3.9%China 84,453 1.0% 18.1% 26.1% 26.3% 55.2% 63.7% 65.8% 34.2% 35.0% 36.0% 89.4% 98.6% 101.7% 9.7%South Korea 53,268 4.6% 22.5% 17.8% 12.4% 78.3% 77.4% 77.2% 22.2% 22.8% 22.8% 100.5% 100.2% 100.1% 2.5%Australia 34,069 2.2% 12.3% 12.1% 10.5% 74.4% 72.4% 74.4% 27.5% 27.8% 28.9% 101.8% 100.2% 103.3% 5.3%India 8,421 0.5% 10.6% 16.2% 8.5% 88.8% 89.8% 88.0% 28.9% 31.5% 31.9% 117.7% 121.3% 120.0% 3.4%Thailand 4,927 1.3% 27.4% 20.7% 13.3% 74.2% 62.7% 60.5% 35.7% 36.9% 37.2% 110.0% 99.6% 97.6% 7.8%Malaysia 4,251 1.4% 7.9% 12.8% 9.6% 68.4% 65.4% 65.6% 27.2% 27.4% 28.1% 95.6% 92.8% 93.6% 5.1%Taiwan 3,597 0.8% 6.7% 9.1% 2.8% 58.5% 57.4% 55.7% 37.4% 39.4% 41.8% 95.9% 96.8% 97.5% 1.3%New Zealand 3,359 2.0% 16.2% 17.5% 10.3% 113.8% 96.9% 87.6% 32.9% 35.6% 36.2% 146.7% 132.4% 123.9% 15.2%Indonesia 3,288 0.4% 20.0% 13.7% 13.0% 53.8% 55.7% 54.7% 33.4% 33.3% 34.1% 87.2% 89.0% 88.7% 1.6%Hong Kong 2,467 0.9% 14.0% 7.1% 7.6% 65.5% 60.5% 60.0% 46.8% 40.8% 39.9% 112.3% 101.3% 99.9% 7.5%Singapore 2,367 0.9% 1.2% 9.4% 10.3% 56.3% 55.8% 55.9% 33.8% 33.5% 32.9% 90.1% 89.3% 88.9% 2.1%Subtotal 296,842 1.4% 16.2% 15.6% 12.4% 70.7% 70.4% 70.4% 31.0% 31.7% 32.1% 101.7% 102.0% 102.5% 1.6%

Global 1,315,156 2.0% 5.8% 4.6% 3.6% 73.7% 73.0% 72.4% 27.4% 27.3% 27.1% 101.1% 100.3% 99.5% 1.8%

18


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

Brazil 1,753Chile 774China 6,875Colombia 1,001Ecuador 243Greece 441Hong Kong 1,271India 1,626Indonesia 434Malaysia 455New Zealand 295Russia 2,120Singapore 714Switzerland 3,238Turkey 377U.A.E. 1,258Venezuela 633

Australia 7,560Austria 2,173Bulgaria 32Canada 6,557Czech Republic 918Denmark 1,043France 11,093Japan 17,343Luxembourg 201Mexico 1,506Netherlands 3,327Nigeria 294Poland 1,023Romania 204Saudi Arabia 184South Africa 668Spain 6,401Taiwan 362Thailand 291U.K. 15,633

Belgium 3,252Finland 1,264Germany 15,547Ireland 888Israel 635Italy 5,335Norway 1,676Portugal 1,079Sweden 210U.S. 125,554

Argentina 4,124Morocco 379South Korea 39,468

Argentina 1,682Brazil 8,015China 14,495Colombia 1,379Ecuador 547Indonesia 1,710Morocco 256Nigeria 548Russia 5,860Saudi Arabia 965Switzerland 4,928Turkey 2,527U.A.E. 1,320Venezuela 846

Belgium 3,374Bulgaria 203Canada 15,411Czech Republic 1,095Greece 754Hong Kong 747India 2,115Luxembourg 284Malaysia 1,537Mexico 3,044Netherlands 5,202Romania 396South Korea 2,597Singapore 662Taiwan 1,221U.K. 23,967U.S. 181,184

Austria 3,201Denmark 4,360Finland 1,283France 27,233Germany 24,010Ireland 1,361Israel 931Italy 6,996Japan 19,736Norway 4,798Poland 1,681Portugal 1,043South Africa 2,458Spain 9,613Sweden 4,247

Australia 10,016Chile 1,851New Zealand 1,987Thailand 1,293

Brazil 14,640China 63,083Colombia 1,938Ecuador 538Indonesia 1,144Nigeria 294Norway 3,284Thailand 3,343U.A.E. 1,121Venezuela 3,812

Austria 3,786Bulgaria 617Czech Republic 1,757Denmark 2,850Finland 1,875Hong Kong 449Japan 55,298New Zealand 1,098Switzerland 6,291Taiwan 2,014U.S. 196,918

Belgium 4,548Canada 19,891France 26,246Germany 28,267Greece 2,056Ireland 1,660Israel 2,249Italy 25,985Luxembourg 497Mexico 4,758Netherlands 5,989Poland 4,454Portugal 1,746Romania 1,168Russia 10,540South Africa 2,686South Korea 11,204Spain 12,798Sweden 3,329Turkey 3,903U.K. 25,132

Argentina 4,595Australia 12,954Chile 1,093India 4,679Malaysia 2,259Morocco 841Saudi Arabia 1,250Singapore 991

Brazil 24,408Chile 3,719Ecuador 1,328Indonesia 3,288Malaysia 4,251Nigeria 1,136Russia 18,574Saudi Arabia 2,400Singapore 2,367Thailand 4,927U.A.E. 3,699Venezuela 5,292

Austria 9,160Bulgaria 852Canada 41,860Czech Republic 3,770Denmark 8,254France 63,472Germany 66,941Ireland 3,909Italy 38,316Norway 10,553Poland 7,157Portugal 3,597South Africa 5,813Spain 28,812Sweden 8,392Switzerland 14,456Taiwan 3,597

Belgium 11,882Finland 4,422Greece 3,251Israel 3,816Japan 92,376Luxembourg 982Mexico 9,307Netherlands 14,517Romania 1,768Turkey 7,755U.K. 64,732U.S. 503,657

Argentina 10,400Australia 34,069China 84,453Colombia 4,318Hong Kong 2,467India 8,421Morocco 1,637New Zealand 3,359South Korea 53,268

Growth Markets and Out or Under Performers

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 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 summarize the results of that analysis and identify countries as either low growth or high growth and as loss ratio or combined ratio out performers or under performers.

To measure performance, the first three quadrant plots use loss ratio for each line of business while the furthest right 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 USD30,000 GDP per capita split between high income and low income companies; 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 out performers.

19

Aon Benfield

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

















Twenty-three countries are high growth, loss ratio out performers in at least one line of business. Of those twenty-three countries, six appear in each of the lines of business analyzed as high growth out performers: Brazil, Colombia, Ecuador, Indonesia, U.A.E., and Venezuela. All but Ecuador were similarly distinguished last year.

When considering profitability in the furthest right plot, we find that Colombia under performs its peers with a five year cumulative net combined ratio of 107.3 percent due to a significantly higher than average expense ratio with

respect to both its income and regional peers (46.6 percent five year cumulative net expense ratio). Brazil, Indonesia and U.A.E., conversely, have maintained five year average combined ratios between 85 and 89 percent, which is significantly lower than their income and regional peers. (See the Top 50 P&C Markets table, page 17 for more details.) Using combined ratio in addition to loss history allows us to further analyze and target high growth opportunities.

20


Macroeconomic, Demographic and Social Indicators

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Argentina 743.1 7.2% 41.0 1.1% 18,113 5.4% 68.1% 44.9% 12.6 10.0% 7.2% 35.0% High Medium Medium high More difficultAustralia 970.8 4.3% 22.8 1.5% 42,641 5.9% 61.2% 27.2% 66.0 1.8% 5.2% 30.0% Low Negligible Medium low EasiestAustria 359.0 2.3% 8.5 0.4% 42,407 6.7% 66.1% 73.7% 2.1 2.6% 4.4% 25.0% Low Low Medium low EasiestBelgium 420.3 2.1% 11.1 0.9% 37,883 6.6% 65.5% 99.6% -1.9 2.6% 7.3% 34.0% Low Low Medium low EasiestBrazil 2,355.6 4.9% 198.4 0.9% 11,875 10.3% 69.0% 68.5% 76.1 5.4% 5.5% 34.0% Medium low Low Medium More difficultBulgaria 103.8 2.4% 7.3 -1.0% 14,312 11.1% 71.6% 18.5% 2.0 2.4% 12.4% 10.0% Medium low Low High EasierCanada 1,488.3 2.8% 34.8 1.2% 42,734 7.0% 69.9% 85.6% 45.4 1.5% 7.3% 26.0% Low Low Low EasiestChile 320.5 5.6% 17.4 1.0% 18,419 3.8% 60.3% 11.2% 30.3 3.0% 6.5% 20.0% Low Medium Medium low EasiestChina 12,405.7 11.1% 1,354.0 0.5% 9,162 17.1% 43.8% 22.8% 253.5 2.7% 4.1% 25.0% Medium Medium Medium EasierColombia 502.9 5.7% 46.6 1.2% 10,792 6.6% 71.9% 32.8% 15.8 3.2% 10.4% 25.0% Medium High Medium high EasiestCzech Republic 287.0 2.0% 10.6 0.5% 27,192 8.9% 63.9% 43.2% 10.6 3.3% 7.0% 19.0% Low Low Medium low EasierDenmark 210.1 0.8% 5.6 0.5% 37,654 6.9% 66.3% 50.1% 1.3 2.4% 7.6% 25.0% Low Negligible Low EasiestEcuador 153.2 6.4% 15.2 1.5% 10,056 6.0% 74.2% 18.6% 0.6 5.1% 5.3% 22.0% High High n/a More difficultFinland 197.5 1.1% 5.4 0.5% 36,394 7.3% 66.8% 53.3% 1.8 3.2% 7.7% 24.5% Low Negligible Medium low EasiestFrance 2,254.1 1.7% 63.4 0.5% 35,548 7.4% 73.9% 90.3% 65.3 2.0% 10.2% 33.3% Low Medium Medium low EasiestGermany 3,197.1 2.4% 81.9 -0.1% 39,028 5.9% 67.8% 82.0% 27.2 2.1% 5.5% 29.6% Low Low Medium low EasiestGreece 276.9 -2.8% 11.3 0.3% 24,505 9.9% 80.1% 158.5% 2.9 1.0% 24.2% 26.0% Medium High High EasierHong Kong 369.4 4.2% 7.2 0.7% 51,496 3.1% 59.3% 32.4% n/a 4.1% 3.3% 16.5% Low Low Low EasiestIndia 4,684.4 8.6% 1,223.2 1.4% 3,830 12.0% 59.7% 66.8% 32.2 9.3% 0.0% 34.0% Medium low High Medium high More difficultIndonesia 1,216.7 7.7% 244.5 1.4% 4,977 10.0% 67.1% 24.0% 19.9 4.3% 6.2% 25.0% Medium High Medium high More difficultIreland 192.2 0.4% 4.6 0.9% 41,924 4.8% 60.0% 117.1% 32.9 1.9% 14.7% 12.5% Low Low Medium low EasiestIsrael 248.7 5.3% 7.7 2.2% 32,314 9.5% 67.1% 74.6% 10.4 1.7% 6.9% 25.0% Medium low High Medium low EasiestItaly 1,832.9 0.2% 60.8 0.6% 30,136 7.3% 69.7% 127.0% 8.1 3.3% 10.6% 31.4% Low Low Medium EasierJapan 4,627.9 1.5% 127.6 -0.1% 36,266 7.7% 67.4% 237.9% 0.1 0.0% 4.4% 38.0% Low Negligible Medium low EasiestLuxembourg 42.2 1.6% 0.5 1.9% 79,820 4.0% 41.2% 21.1% 18.4 2.9% 6.0% 29.2% Low Negligible n/a EasierMalaysia 498.5 5.9% 29.5 1.6% 16,922 5.5% 49.9% 55.5% 12.0 1.7% 3.0% 25.0% Medium low Medium Medium low EasiestMexico 1,758.9 3.3% 114.9 1.4% 15,312 3.5% 76.3% 43.5% 12.7 4.1% 4.8% 30.0% Medium low Medium Medium EasierMorocco 171.2 6.1% 32.5 1.1% 5,265 5.4% 62.5% 59.6% 2.5 1.3% 8.8% 30.0% Medium Medium Medium high More difficultNetherlands 707.0 1.6% 16.8 0.5% 42,194 10.3% 62.3% 71.7% -8.3 2.8% 5.3% 25.0% Low Low Low EasiestNew Zealand 132.0 2.3% 4.4 0.9% 29,733 8.0% 70.6% 38.2% 4.3 1.1% 6.9% 28.0% Low Negligible Medium low EasiestNigeria 448.1 8.7% 164.8 2.7% 2,720 17.1% 61.0% 17.8% 8.8 12.2% n/a 30.0% High Severe High More difficultNorway 277.1 2.3% 5.0 1.3% 55,010 6.4% 55.9% 34.1% 7.3 0.7% 3.2% 28.0% Low Low Low EasiestPoland 800.9 5.1% 38.9 0.4% 20,592 6.7% 73.7% 55.2% 3.0 3.7% 10.3% 19.0% Medium low Low Medium EasierPortugal 246.5 0.5% 10.5 -0.1% 23,385 5.7% 77.7% 123.0% 13.8 2.8% 15.7% 25.0% Low Low Medium EasiestRomania 273.4 2.0% 21.3 -0.2% 12,808 7.4% 76.1% 37.0% 2.6 3.3% 7.0% 16.0% Medium low Low Medium high EasierRussia 2,513.3 3.5% 141.9 -0.1% 17,709 8.8% 65.6% 10.9% 51.4 5.1% 6.0% 20.0% Medium Medium Medium high More difficultSaudi Arabia 906.8 8.3% 29.0 3.1% 31,276 7.1% 33.8% 3.6% 12.2 2.9% n/a 20.0% Medium Medium Medium low EasiestSingapore 326.5 6.0% 5.4 2.2% 60,408 10.1% 31.7% 111.0% 56.7 4.6% 2.0% 17.0% Low Negligible Low EasiestSouth Africa 582.4 3.9% 51.2 1.1% 11,375 8.0% 68.9% 42.3% 5.9 5.7% 25.2% 28.0% Medium Medium Medium EasiestSouth Korea 1,613.9 4.6% 50.0 0.6% 32,272 6.3% 55.9% 33.7% 5.0 2.2% 3.3% 24.2% Medium low Medium Medium low EasiestSpain 1,410.6 0.8% 46.2 0.6% 30,558 8.2% 68.7% 84.1% 36.2 2.4% 25.0% 30.0% Low Medium Medium low EasiestSweden 393.0 2.7% 9.5 0.8% 41,190 7.0% 68.2% 38.0% 3.9 0.9% 7.9% 22.0% Low Low Low EasiestSwitzerland 363.4 2.9% 8.0 1.3% 45,416 4.3% 61.6% 49.1% 9.3 -0.7% 2.9% 18.0% Low Negligible Low EasiestTaiwan 903.5 4.6% 23.3 0.3% 38,749 9.7% 59.5% 40.9% n/a 1.9% 4.2% 17.0% Medium low Low Medium low EasiestThailand 651.9 4.5% 64.4 0.4% 10,126 7.6% 58.4% 44.3% 8.6 3.0% 0.5% 20.0% Medium high High Medium EasiestTurkey 1,123.4 4.8% 74.9 1.3% 15,001 6.8% 78.1% 36.4% 12.6 8.9% 9.2% 20.0% Medium High Medium high EasierU.A.E. 271.3 3.8% 5.5 4.3% 49,009 3.4% 58.6% 17.6% 7.7 0.7% 0.0% 55.0% Medium low Medium Low EasiestU.K. 2,336.3 1.2% 63.2 0.7% 36,941 7.9% 77.1% 90.3% 55.6 2.8% 8.0% 23.0% Low Low Low EasiestU.S. 15,684.8 2.3% 314.2 0.8% 49,922 7.5% 76.2% 106.5% 205.8 2.1% 8.1% 40.0% Low Low Low EasiestVenezuela 401.9 3.7% 29.5 1.6% 13,616 4.9% 62.3% 57.3% 2.2 21.1% 7.8% 34.0% Very high High High Most difficult

21

Aon Benfield

Using several data points from each of these analyses, Aon Benfield created a Country Opportunity Index, identifying countries that have a desirable mix of profitability, growth potential and a relatively stable political environment. Aon Benfield’s Country Opportunity Index is a ranking based on five statistics. Five year average combined ratio receives one-third of the weight, and the growth and stability statistics shown below equally contribute to the remaining two-thirds.

The table displays the top 50 property & casualty markets ranked by the Country Opportunity Index and divided into quartiles. The six starred countries, Indonesia, Malaysia, Canada, Colombia, Turkey, and Mexico are discussed in the following sections. These selected countries represent a sample from various geographies, and the more detailed analysis illustrates some components we would engage in during a collaborative deep dive, exploring particular lines of business as well as the optimal pathway into the market.

Aon Benfield Country Opportunity Index

Rank Country 5yr Cumulative Net

Combined Ratio5yr Annualized

Premium GrowthGDP 5yr

Real GrowthPopulation 5yr

Annualized Growth Political Risk

Quartile 11 Singapore 88.9% 10.3% 6.0% 2.2% Low2 Indonesia* 88.7% 13.0% 7.7% 1.4% Medium2 Saudi Arabia 90.4% 11.6% 8.3% 3.1% Medium4 Nigeria 78.9% 12.3% 8.7% 2.7% High4 U.A.E. 85.9% 12.3% 3.8% 4.3% Medium low4 Ecuador 87.1% 17.4% 6.4% 1.5% High4 Chile 95.9% 15.7% 5.6% 1.0% Low8 Brazil 85.2% 11.1% 4.9% 0.9% Medium low8 Norway 91.7% 5.4% 2.3% 1.3% Low8 Malaysia* 93.6% 9.6% 5.9% 1.6% Medium low11 Sweden 91.2% 2.8% 2.7% 0.8% Low11 Venezuela 97.1% 15.8% 3.7% 1.6% Very high11 Switzerland 98.0% 7.3% 2.9% 1.3% Low

Quartile 214 Russia 87.0% 9.7% 3.5% -0.1% Medium14 South Africa 88.5% 0.3% 3.9% 1.1% Medium16 Czech Republic 89.3% 0.8% 2.0% 0.5% Low16 Hong Kong 99.9% 7.6% 4.2% 0.7% Low16 Morocco 100.2% 10.1% 6.1% 1.1% Medium16 Australia 103.3% 10.5% 4.3% 1.5% Low20 Denmark 93.7% 1.4% 0.8% 0.5% Low20 Thailand 97.6% 13.3% 4.5% 0.4% Medium high20 France 98.6% 3.9% 1.7% 0.5% Low20 Canada* 98.8% 4.7% 2.8% 1.2% Low20 Belgium 99.9% 3.7% 2.1% 0.9% Low20 South Korea 100.1% 12.4% 4.6% 0.6% Medium low

Quartile 320 Colombia* 107.3% 14.1% 5.7% 1.2% Medium20 India 120.0% 8.5% 8.6% 1.4% Medium low28 Bulgaria 89.7% -0.3% 2.4% -1.0% Medium low28 Spain 92.3% -3.4% 0.8% 0.6% Low28 Poland 97.1% 3.8% 5.1% 0.4% Medium low28 Taiwan 97.5% 2.8% 4.6% 0.3% Medium low28 Germany 98.7% 1.1% 2.4% -0.1% Low28 Luxembourg 99.5% -11.1% 1.6% 1.9% Low28 China 101.7% 26.3% 11.1% 0.5% Medium28 Argentina 105.8% 20.0% 7.2% 1.1% High28 Israel 109.3% 5.6% 5.3% 2.2% Medium low28 New Zealand 123.9% 10.3% 2.3% 0.9% Low

Quartile 438 Portugal 92.1% -3.7% 0.5% -0.1% Low38 Ireland 98.7% -3.4% 0.4% 0.9% Low38 U.S. 100.2% 1.0% 2.3% 0.8% Low38 Turkey* 103.6% 7.3% 4.8% 1.3% Medium42 Italy 99.2% -2.7% 0.2% 0.6% Low42 Austria 99.3% 1.1% 2.3% 0.4% Low42 Finland 100.4% 2.2% 1.1% 0.5% Low42 Netherlands 101.2% 2.9% 1.6% 0.5% Low42 Mexico* 102.9% 4.2% 3.3% 1.4% Medium low47 Japan 103.0% 6.3% 1.5% -0.1% Low48 U.K. 101.2% -1.4% 1.2% 0.7% Low49 Greece 102.7% 5.7% -2.8% 0.3% Medium50 Romania 111.4% -5.1% 2.0% -0.2% Medium low

Country Opportunity Index

*These countries represent potential contender geographies discussed in the following pages.

22


Developing a robust growth strategy begins with an analysis of basic insurance metrics like premium growth, profitability and volatility. The contender countries we selected range from very profitable to consistently unprofitable, as measured by a five year average combined ratio. Three countries, Canada, Indonesia and Malaysia, all have five year combined ratios below 100 percent, while the remaining three, Colombia, Mexico and Turkey, all are in excess of 100 percent. Two of the profitable countries, Indonesia and Malaysia, also rank highly for growth based on a five year annualized growth rate.

Colombia has experienced significant five year annualized premium growth, yet the five year cumulative combined ratio is over 107 percent. However, when looking at the

components, the loss ratio is low at 60.7 percent and stable with a low volatility of only 1.9 percent CV. The expense ratio is the highest of all 50 countries in the Study, at 19 points above the global expense ratio.

Companies could still consider Colombia; given the rate of growth and manageable losses, companies with a proven record of expense management may find ways to outperform the current competition. Indonesia hits all the marks: 13.0 percent five year growth with a 88.7 percent combined ratio and only 1.6 percent volatility. The question then becomes whether or not there is room for new entrants since the market seems to be a logical place to expand into, and so may already be saturated.

Contender Geography Demographics

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Canada 1,488.3 2.8% 34.8 1.2% 42,734 7.0% 69.9% 85.6% 45.4 1.5% 7.3% 26.0%

Colombia 502.9 5.7% 46.6 1.2% 10,792 6.6% 71.9% 32.8% 15.8 3.2% 10.4% 25.0%

Indonesia 1,216.7 7.7% 244.5 1.4% 4,977 10.0% 67.1% 24.0% 19.9 4.3% 6.2% 25.0%

Malaysia 498.5 5.9% 29.5 1.6% 16,922 5.5% 49.9% 55.5% 12.0 1.7% 3.0% 25.0%

Mexico 1,758.9 3.3% 114.9 1.4% 15,312 3.5% 76.3% 43.5% 12.7 4.1% 4.8% 30.0%

Turkey 1,123.4 4.8% 74.9 1.3% 15,001 6.8% 78.1% 36.4% 12.6 8.9% 9.2% 20.0%

Contender Geography Growth, Profitability and Volatility

Country5yr Annualized

Premium Growth5yr Cumulative Net Loss Ratio

5yr Cumulative Net Expense Ratio

5yr Cumulative Net Combined Ratio

5yr Combined Ratio CV

Canada 4.7% 70.4% 28.4% 98.8% 3.9%Colombia 14.1% 60.7% 46.6% 107.3% 1.9%Indonesia 13.0% 54.7% 34.1% 88.7% 1.6%Malaysia 9.6% 65.6% 28.1% 93.6% 5.1%Mexico 4.2% 69.1% 33.8% 102.9% 2.4%Turkey 7.3% 77.1% 26.5% 103.6% 3.4%

Profitability

The contender countries we selected have varying demographics. Some are experiencing rapid population growth, while others are shrinking. Some are experiencing consistent inflation, while others are steady. Below are demographic indicators that will help companies better understand the landscape of the country to determine if it is a good insurance growth opportunity.

Colombia’s GDP is growing steadily while unemployment remains high. Nonetheless, there has been a recent shift of the population towards the middle class, creating new insurance opportunities. Canada has slow population growth and low GDP growth, offset by very low inflation. We have seen companies interested in expanding there, as evidenced by recent mergers and acquisitions activity.

Demographics

Once companies have identified markets that have a good balance of growth and profitability, the next step is to understand whether or not the demographics support a stable insurance market.

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Aon Benfield

Regulatory, Sovereign and Stability PerspectivesEven when profitable underwriting opportunities exist, companies need to remain cognizant of the regulatory framework, including capital requirements and foreign ownership limitations, as well as the sovereign, political and terror risk environments, to determine whether or not the risk of expansion is worth the reward. The four global rating agencies publish their relative views on the sovereign risk of the countries, which provide third-party perspectives. Further, Aon publishes an analysis of political, terror and people risk, noting where weaknesses may exist. Together, these opinions provide a good overview of the relative risk across different countries.

The next step is to consider the regulatory environment and foreign ownership restrictions to help assess whether the company’s investment strategy and risk management frameworks align with the countries under consideration.

Canada

There are no barriers to entry for foreign companies into the market at a federal or provincial level, provided that the legal requirements are met, and there are no restrictions on foreign investment. Foreign subsidiaries and branches are held to the same regulatory standards as local companies. In order for a foreign company to establish a branch or Canadian subsidiary, it must register with OSFI, the Canadian regulator, appoint a chief agent for Canada and lodge deposits with the Ministry of Finance. Minimum capital required is USD5 million.

Since 2008, OSFI has been revisiting the Canadian regulatory oversight system. The objective is to focus on managing the risk inherent in a company through enterprise risk management and capital planning. The key changes introduced were: reinsurance risk management policies (guideline B3) in 2010 and corporate governance (guideline E19) in 2012, followed recently by own-risk and solvency assessment to be effective 2014, and the proposed revised Minimum Capital Framework to be effective in 2015. Additionally, in February 2013, OSFI issued their Earthquake Exposure Sound Practices guideline. Insurers are required to more effectively measure, monitor and limit their earthquake

exposure. All of these changes are designed to increase accountability of board of directors and senior management and to build a more robust enterprise risk management framework. Companies must implement a capital planning process to project and assess capital requirements, not only on a day-to-day basis, but under certain stress scenarios in accordance with the company’s risk matrix. Capital planning is both on a current and forward-looking basis.

Colombia

New direct foreign investment in local commercial enterprises and new subsidiaries of banks and insurance companies are permitted up to 100 percent ownership. Ownership was raised from 49 percent in 1991 and has generated a large increase in foreign capital. Neighbors such as Peru, Chile, Venezuela, and Argentina do not have regulations restricting foreign investment and have opened their markets to many foreign insurance companies.

Minimum capital is USD4.8 million for insurers and USD19.2 million for reinsurers, with additional line of business net worth requirements. Financial regulators continue to modernize their solvency standards for insurers to align with international standards. Since 2009, the Financial Superintendency of Colombia has been moving towards IFRS; albeit, this has been a prolonged process and is not compulsory. Recently, Colombia has opened its insurance market to non-admitted writers.

Contender Geography Credit Rating and Risk Perspectives

S&P Fitch Moody’s A.M. Best Aon Political, Terrorism and People Risk Assessment

Rating Outlook Rating Outlook Rating Outlook Rating Political Terrorism People

Canada AAA Stable AAA Stable Aaa Stable Tier 1 Low Low Low

Colombia BBB+ Stable BBB Positive Baa3 Positive Tier 4 High High Medium High

Indonesia BB+ Stable BBB- Stable Baa3 Stable Tier 4 Medium High Medium High

Mayalsia A Stable A Negative A3 Stable Tier 3 Medium Medium Medium Low

Mexico A- Positive A- Stable Baa1 Stable Tier 3 Medium Low Medium Medium

Turkey BBB Stable BBB- Stable Baa3 Stable Tier 4 Medium High Medium High

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Indonesia

Foreign ownership in joint ventures is capped at 80 percent; however, this can increase following ownership changes as long as the Indonesian partner’s share of capital is upheld. Indonesia’s foreign ownership limit is higher than that of several neighboring countries such as India (26 percent), Thailand (49 percent) and Malaysia (70 percent). Actual foreign ownership is still low due to the highly competitive nature of the market.

In 2014, minimum capital requirements for insurers and reinsurers will be USD11 million and USD22 million, respectively. Additionally, insurers and reinsurers must reserve 20 percent of capital in a guarantee fund. As a key economy in ASEAN, Association of Southeast Asian Nations, Indonesia is refining its regulations to strengthen insurance development in line with international standards. An enhanced capital requirement is already in place ahead of full implementation of the ASEAN Free Trade Agreement in 2015. A number of undercapitalized local insurers face significant challenges, and merger or acquisition is a good option available for them; otherwise, they will have to surrender their licenses. Convergence to IFRS is ongoing, noting the impact has been greater on local insurers as most of the international insurers are already compliant.

Malaysia

Foreign investment of up to 70 percent is permitted in insurance companies and Takaful operators. With proper approval on a selected basis 100 percent foreign equity for insurance companies will be considered. If a foreign company expects to begin negotiations for 5 percent or more of a Malaysian conventional insurer or Takaful operator, it must receive approvals from the Malaysian Minister of Finance, and from the Foreign Investment Committee if at least 15 percent or more voting rights or a valuation of USD3.3 million is being considered.

Minimum required capital for non-life insurers and reinsurers is USD33 million. For insurers operating in the federal territory of Labuan, an institutional financial center, the requirement is USD2.5 million. The new Financial Services Act of 2013 is expected to spark another round of consolidation as insurers will be prohibited from operating both life and general insurance simultaneously. Takaful operators are to be subject to the same conditions under the Islamic Financial Services Act. As result of the new act, various frameworks and guidelines have been amended or introduced recently aimed at further improving the industry.

Mexico

Investments by North American insurance companies in Mexico have become easier since Mexico entered into NAFTA, North American Free Trade Agreement, in 1994. The maximum permitted investment increased annually starting in 1994, eventually reaching 100 percent by 2000. European companies can take advantage of NAFTA legislation by operating through a U.S. subsidiary.

Since 1995, the capital requirements have been stated in investment units or UDIs (unidades de inversiones) in order to relieve the pressure from heavy interest rates during Mexico’s financial crisis. The units change daily, are published every two weeks, and are adjusted based on inflation. The units by line of business are housing credit (12.2M UDI), financial guarantee (33.2M UDI), and other non-life (5.1M - 8.5M UDI), and reinsurers must hold 1.5 times these amounts. The units by line of business after the conversion based on 2012 foreign exchange rates are: housing credit USD4.4 million, financial guarantee USD11.6 million, and other non-life USD1.8 million - 3.0 million. A new law on Insurance and Bonding Institutions was passed by the Chamber of Deputies in February 2013 and is expected to be implemented in 2014. The new insurance law is intended to introduce a risk-based capital approach into the sector and is expected to lead to greater capital resources and risk management, and to improve industry transparency and supervision.

Turkey

Foreign insurers may have 100 percent ownership of domestic companies. In 2012, more than 20 foreign companies representing 15 countries had at least 70 percent market share of the non-life insurance sector.

Required capital for a non-life insurer or reinsurer is USD2.8 million. Additional capital is required depending on the line of business being written, which increases the required capital for non-life insurers and reinsurers to a maximum of USD6.4 million and USD4.9 million, respectively. There have been major changes to insurance legislation in recent years, bringing the industry more in line with EU requirements and international insurance principles. All foreign companies (including those in the EU) have to be established as a joint stock company or co-operative in order to do business, and they have the same licensing capital requirements as domestic companies.

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Aon Benfield

Market Opportunities and Pathways to EntryUnderstanding the underlying growth and profitability metrics is a basic consideration when assessing whether or not to consider expansion. Knowing the current market concentration and mergers and acquisitions environment reveals if there are opportunities for new players, and if so, how to best enter the market. Most importantly though, not all insight can be gleaned from publicly available resources; it is vital to have a partner with local knowledge of the market and trends.

When identifying opportunities companies want to know how concentrated the market is and whether or not a new entrant can profitably write business or if it is concentrated in the hands of a small number of key players. Of the six countries examined, the percentage of business being underwritten by the top five companies ranges from 31.3 percent to 60.7 percent and the top ten companies represent 49.1 percent to 84.6 percent of all business underwritten. Canada has a relatively low concentration of companies in the market and Colombia, Malaysia, Mexico, and Turkey all have a high concentration.

Market Concentration

Country Top 5 Companies Top 10 Companies

Canada 31.3% 49.1%

Colombia 52.4% 84.6%

Indonesia 39.1% 54.4%

Malaysia 44.2% 70.2%

Mexico 60.7% 70.2%

Turkey 51.8% 80.8%

In many regions it is very difficult for a company to enter the market without a strong, existing platform. As such, many companies seek merger and acquisition opportunities, either acquiring a company or agency outright, or a partnership opportunity with a bank or existing agency. Below are the top five (where available) recent merger and acquisition deals in each country being examined.

Top Five Recent Merger and Acquisition Deals by Country

Date Acquirer Target Lines of Business Valuation

(USD millions)Date Acquirer Target Lines of Business

Valuation (USD millions)

Canada Malaysia

31-Dec-13 Multi-National Composite 1,103 21-Dec-12 Local Investment Management N/A

10-Jun-13 Multi-National Non-Life N/A 11-Oct-12 Multi-National Composite 1,729

24-Oct-12 Multi-National Life 146 12-Apr-12 Local Non-life 532

30-Sep-12 Multi-National Non-Life N/A 17-Oct-11 Regional Investment Management N/A

6-Jun-12 Multi-National Non-Life N/A 10-May-11 Multi-National Non-life 166

Colombia Mexico

17-Mar-08 Multi-National Consumer Finance N/A 4-Dec-12 Local Composite 31

15-Jun-07 Multi-NationalReal Estate for Public Agencies N/A 18-Oct-12 Multi-National Non-Life 865

12-Sep-12 Multi-National Composite 293

5-Mar-12 Local Composite (Reinsurance) N/A

16-Aug-11 Local Life 200

Indonesia Turkey

30-Apr-13 Regional Non-life 2 13-May-13 Local Life 104

13-Jun-12 Multi-National Non-life 130 27-Mar-13 Multi-National Non-Life 874

9-May-12 Multi-National Life 100 18-Feb-11 Regional Non-Life 220

2-May-11 Multi-National Life 819 13-Dec-10 Regional Non-Life 34

8-Nov-10 Multi-National Life 5 28-Sep-10 Regional Non-Life 20

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The mergers and acquisitions deal table on page 25 shows there is a relatively even mix of multi-national acquisitions and local companies seeking to expand their existing market presence. Most of these countries have seen a large number of deals in the past two years alone. Therefore, it is important to understand what targets remain available, whether or not they are selling for a premium, and whether or not the company will provide a platform upon which the acquirer can grow its footprint in the region.

Without local insight into the nuances of the insurance industry in each country, companies risk making a decision based on incomplete information. Research may suggest entering a market with limited opportunities, or vice versa. Aon Benfield has a significant local presence in all key insurance regions globally, allowing our clients to access local experts who can provide important insight not obvious in demographic trends or historical insurance results. Below is a summary of the market conditions in each of the countries being examined, as well as opportunities available, providing a very high level overview of the markets. The theme is that there are no themes; each market is different, and all present different risks and opportunities that must be understood and weighed.

Canada

Canada is a very competitive market, with more than 20 companies having capitalization in excess of CAN300 million. The auto market, representing 45 percent of non-life premium, is very regulated and controlled in most provinces except Ontario and Alberta. In Ontario auto is the dominant line but the regulator is rolling back rate increases, resulting in an approximate 15 percent decline in rates. Companies are trying to grow via acquisition but this is difficult given strong capital levels and few opportunities available in the market. Recent transactions have commanded a premium price.

Nonetheless there are still pockets of opportunity. British Colombia has significant earthquake exposure and current writers have curtailed their writings. At the same time there is significant population growth in the region and insured values are increasing. Pricing, deductibles and terms and conditions for the business are improving and insurers are applying more granular pricing of earthquake risks in British Colombia. There is also more demand for reinsurance due to regulatory capital requirements and the conservatism of local markets, which helps enforce market discipline.

These pressures also mean that reinsurance presents an opportunity. Many companies are seeking a more diversified reinsurer panel and there are opportunities in the mid to upper layers of reinsurance.

The most profitable companies are the larger and more specialized players. Companies with efficient IT systems to allow direct underwriting, paperless commercial lines underwriting and technical pricing and claims management, as well as efficient expense management capabilities, are leading the market.

Colombia

Colombia is experiencing consistent GDP growth, which is creating opportunities in all industries, including insurance. The insurance industry has seen positive growth trends, and market penetration remains low, indicating the potential for sustained future growth. The economy and population are expanding, with a significant shift to the middle class, resulting in a number of opportunities for insurers. Recent mergers and acquisitions activity has been limited and the market is highly concentrated. The top five companies include both multi-nationals and local companies. Remaining opportunities for companies to expand into Colombia through acquisition will involve small companies or other distribution possibilities.

The primary opportunity relates to “social security” insurance: health, workers’ compensation, pensions, annuities, and professional insurance (covering the gap between pensions and actual needs). These lines are growing twice as fast as the rest of the industry as more people are working and moving towards the middle class. As Colombia enters new free trade agreements, the infrastructure is improving rapidly, and the government is encouraging more private investment. As a result there is demand for surety and engineering insurance (which is becoming compulsory in some cases). Further, the growing middle class is becoming more aware of their legal rights, presenting opportunities for various types of liability insurance. Motor liability is currently not compulsory, but those who are buying it are increasing limits from USD200,000 to USD1-2 million. Finally, the oil and mining as well as the agriculture sectors are growing, resulting in opportunities for specialized writers offering pollution, environmental and crop insurance.

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Aon Benfield

Indonesia

The Takaful compliant industry shows great untapped potential, with improved and additional regulation being introduced progressively to establish it on a more comprehensive legal foundation.

Jakarta and Java are the primary regional growth opportunities in Indonesia. In addition, East Indonesia represents a promising area for insurance penetration due to its abundance of natural resources (forestry, plantation, and fishery) as well as infrastructure (railway, port and airport). The major growth lines are large construction, marine cargo and property, and life insurance. Insurance distribution is largely a mix of direct marketing and intermediary with the retail market dominated by Bancassurance (motor, home, personal accident, and credit life). Captive agents are present in the market but do not have a large share. Currently, many personal insurance products are sold in the major retailers and supermarkets such as Carrefour or Hypermart.

Market potential remains positive. Motor insurance is viewed as attractive but it is dominated by subsidiaries of financial and leasing companies. Motor, marine, cargo, and personal auto are considered to be the most profitable lines. Many of the leading insurance companies in Indonesia are exploring health insurance, especially companies that write motor insurance and already have a 24-hours service infrastructure. Companies have primarily grown in the region via organic growth from innovative products or distribution systems, though there have been a number of recent mergers and acquisitions.

Mexico

The insurance sector is expected to grow from 1 percent of GDP to 4 or 5 percent of GDP by 2030 driven by current economic growth rates and more compulsory lines of insurance. There is a significant presence of foreign investors in the insurance industry as foreign insurers can wholly own subsidiaries. There have been a number of recent acquisitions of large Mexican insurance companies by global insurance companies. The mergers and acquisitions market is strongly competitive and there are a limited number of companies remaining for sale. The best operations are expensive, not 100 percent for sale, and are sold at a premium. A significant portion of remainder of the market is owned by Mexican conglomerates. Independent companies are transitioning from a multiline to specialty to gain a competitive advantage.

Mexico is well regulated and is moving towards Solvency II, which was approved by congress in 2012 for a 2015 implementation. Mexico is progressing in Pillar 1, focused on compulsory catastrophe modeling, improvement in risk management and strong current solvency margins

It is expected that over 70 percent of future growth in insurance will come from life and pension insurance, health insurance, auto liability, and property. Pension and health insurance are currently managed by the government but there is a shift to insurance by private companies. It is difficult for new companies to enter the life market but there are greater opportunities for new players in health. Property is another opportunity as currently there is low take-up aside from homes with a mortgage, where insurance is required by the banks. The wealthy are more likely to insure their property and with a growing middle class, more people will be looking for property insurance. There are reinsurance opportunities too as most companies are looking for a more diversified pool of reinsurers. Reinsurers need strong global ratings presenting opportunities for the multi-nationals.

Malaysia

The Central Bank, which is under the Ministry of Finance, has placed a freeze one the issuance of new licenses. Also, new investors must be a public company. The only way to enter the regulated market is via an acquisition. There is, however, an alternative licensing approach to entering market, which is through the Labuan Financial Services Authority (LFSA). Malaysia wants to encourage investment in the market, so it has created an offshore licensing opportunity that is not governed by the Central Bank. Lloyd’s syndicates, brokers and reinsurers are entering the market under the LFSA. Currently there are only 26 direct insurance companies in Malaysia, and there has been significant consolidation, much in past 24 months. Companies need a strong agency base or Bancassurance model to operate effectively within Malaysia.

Motor and fire insurance are currently tariffed lines, with essentially fixed rates, though this has been changing recently for fire. The current rates have been profitable for companies operating in Malaysia. However, in 2016 the government plans to cease the tariff system, which will result in the liberalization of the market but also likely fierce competition. The legislation is not yet finalized leading to uncertainty across the market.

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Companies with strong technical expertise in underwriting liability have an advantage, particularly in specialty liability lines such as financial and D&O, which are presenting the best opportunities. Liability insurance has been generally profitable except for general liability. Companies with an existing competitive advantage in this niche can likely import that to Malaysia, with the appropriate platform, and achieve success.

Turkey

The Turkish non-life insurance market has outpaced European counterparts in growth, and promises strong potential with lower penetration compared to those markets. Growth has been more than 7 percent on average over the last five years and is expected to continue in line with strong macroeconomic indicators. Car sales, real estate and healthcare spending are expected to support this growth on top of significant current uninsured rates both in auto and compulsory earthquake insurance. The key problem facing the industry has been structurally low profitability, driven by fierce price competition, resulting in large but loss-making segments, such as the motor business. In 2012, sudden spikes in provisions for outstanding losses increased the pressure on industry’s bottom-line and highlighted the need for effective claims management.

Traditionally, agents have been the dominant non-life distribution channel as referrals and personal relationships are still important for insurance customers; however, Bancassurance is growing quickly across the country.

Growth and profitability opportunities vary significantly across different business lines. Motor (both physical damage and liability) constitute half of the market, yet they are unprofitable. Health, general damage and general liability lines out-perform industry profitability measures, and so present an opportunity. In terms of distribution opportunities, fire is largest business line in Bancassurance while motor lines are underrepresented; the main insurance production at banks is driven by cross-sells (i.e. most of production via banks is credit related). Finally, due to Turkey working towards alignment with EU standards, liability insurance, which was not previously purchased, presents another opportunity. People are becoming more aware of their rights, and so there is an increasing need for professional and medical liability insurance.

Companies have historically focused more on growth of premium than profitability, resulting in poor experience for recent market entrants. Companies with an advantage in underwriting and claims management skills are better placed to successfully execute on opportunities for profitable growth.

SummaryThis section presents a snapshot of Aon Benfield’s approach when partnering with clients seeking profitable growth opportunities. It is always important to start with the quantitative metrics to try and understand whether or not the insurance market is growing and profitable. However, those metrics do not always tell the complete story. Even though a certain insurance market may not be growing rapidly today, demographic statistics might indicate that growth is inevitable given population and GDP growth. Some markets are very open, while others remain difficult to enter given regulatory constraints. Aon Benfield’s approach is to analyze all available data to build a complete picture of all potential growth opportunities, and then to overlay local broker and market insights to help pinpoint specific, actionable strategies.

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Aon Benfield

Afterword: Extending Insurance-Linked Securities

Characteristics of Cat Risk SecuritizationsWhy have catastrophe risk ILS solutions been so successful? There are numerous reasons.

1. Natural Demand Property values and demographics have driven huge concentrations in the industry relative to even today’s very adequate capital levels, which in turn drives a natural demand for risk transfer products.

2. Loss Modeling The development of computer models for natural catastrophes, on-going since the late 1980’s, has created a generally accepted “currency” to value the loss potential a given risk portfolio. Modeling has been successful in part because natural catastrophe events are driven by laws of nature and are not social science phenomenon with changing, reflexive and reactive parameters and causes.

3. Loss Triggers Modeling, and the physical drivers of loss, also allows for a range of non-indemnity loss triggers and facilitates multi-year resets.

4. Rating Agency Capital Rating agency capital models assign a clearly defined capital charge specifically to cover catastrophe risk, unencumbered by complications of diversification benefits and other technicalities. The rating agency credit is often as much, or greater than, a company’s own economic capital model credit.

5. Credit Risk Purchasers of traditional covers are always concerned with the credit risk of the product they purchase, especially for top layers, as well as the historical volatility in pricing and availability. As a result, they are open to alternative solutions and find fully collateralized ILS structures very attractive.

6. Bond-like Default Profile The loss profile of high layer catastrophe programs mirrors bond default profiles very closely: there is a low probability of a loss, but given a loss a reasonably high probability of a total loss, producing a loss profile familiar to fixed income investors.

7. No Equity Tranche As a result of the loss profile, there is no need for an equity tranche in a cat bond. Equity tranches are a big complication in many (non-insurance) securitizations because they create a residual interest that generally remains on the balance sheet of the issuer.

8. Uncorrelated Returns The loss profile of cat bonds is manifestly uncorrelated with other asset classes, at least a priori. Investors saw the attractiveness of the ILS asset class during the financial crisis (collateral trust problems notwithstanding, but these problems have now been solved).

9. Quick Emergence Major property catastrophe risk events are headline news; the fact of a loss or potential loss emerges very quickly, indeed instantaneously for earthquakes.

10. Quick Loss Settlement Losses from property catastrophe events generally reach their final settlement valuation in a matter of months. There are few issues with late reported claims or slow loss development.

For several years after the introduction of ILS in the mid-1990s there was an expectation — especially on the banking side — that ILS capital would displace traditional insurance equity capital. We have been a continuous believer in the strengths of ILS capital, for both clients and investors, and have been active in the market since its inception through our investment banking arm Aon Benfield Securities, Inc. Aon Benfield Securities as the leading player in the market has led a number of ground-breaking transactions, including the first contingent capital transaction, the only investment grade bond, and the first indemnity cover for complex commercial property. We are gratified to see ILS delivering a record amount of accretive capital to our clients during 2013. Now, as investors are embracing catastrophe risk ILS like never before, it is time to reconsider the securitization of non-catastrophe risk. The Afterword will review the reasons for the success of ILS in the cat risk market and use the data in the Study to model out how ILS structures could apply to non-cat lines of business. We will see that while there are hurdles to overcome none is insurmountable.

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The market has been receptive to non-property cat securitizations, and the reasons for the success of these types of transaction is informative as we consider broader and broader risks. Over the past 10 years we have seen transactions covering:

• Life insurance excess mortality risk

• Aggregate stop loss for health insurance

• High layer aggregate excess specialty liability cover

• Longevity swaps

• Personal automobile aggregate stop loss

How do these transactions score against the natural advantages of catastrophe risk transactions? The table below lays out a view for each typical transaction type. A check mark indicates that any issues associated with each characteristic have a single natural solution or a range of possible solutions acceptable in the market. All transactions also solved for an appropriate loss trigger, and the typical type of trigger is noted for each transaction. The remaining comments highlight modeling, data, structural or other issues that the particular type of transaction had to overcome.

There are several lessons from the table.

First, for all of the transactions except the longevity swap, despite beginning with a range of underlying loss distributions, the transaction converted the distribution into a low frequency, high severity cover akin to a property cat cover, generally via an aggregate stop loss reinsurance arrangement. Using this structure presents investors with the bond-like return distribution they are used to seeing and avoids (retains) the equity tranche that would otherwise be introduced. (For example, securitizing a ground up quota share would generally require an equity tranche.) Pricing and modeling the aggregate distribution used by the health, specialty liability and personal auto type transactions, all rely on risk parameters similar to those published in the Study. These transactions show market acceptance for modeling using statistical and more standard actuarial techniques, as opposed to catastrophe risk models.

Second, most of the transactions still involve a reasonably short emergence and payout tail. The specialty liability transaction involved a risk type with headline-losses, shortening emergence. Settlement was handled contractually through an agreed procedure for actuarial claims evaluation and through an extended term. Covering multiple accident years also naturally provided an extended reporting period for claims during the earlier years.

Securitization Characteristics

Characteristics Traditional Cat Life xs Mortality Health Agg. Stop Specialty Liability Longevity Swap Personal Auto Agg. Stop

Natural Demand ü ü Unclear ü ü Unclear

Loss Modeling ü ü ü Poor ü ü

Loss Triggers ü Index Indemnity Indemnity Index Indemnity

Rating Agency Capital ü Average Average Average Average Average

Bond-like Default Profile ü ü ü ü ü ü

No Equity Tranche ü ü ü ü ü ü

Uncorrelated Returns ü Unclear ü ü Unclear Unclear

Quick Emergence ü ü ü ü Slow Moderate

Quick Loss Settlement ü ü ü Slow Mark Moderate

Existing Non-Traditional Securitizations

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The personal auto securitization included a number of devices to speed reporting and settlement including a multi-year term, a cap on the size of individual claims (important in European countries with unlimited motor liability cover), the use of audits of open and closed claims, actuarial evaluations, and a period of up to two years for final settlement.

The longevity swaps are a different type of transaction. Structured as a swap of actual experience for an index, their long-term credit risk is handled through a mark to market procedure, similar to other financial swaps, which collateralizes the running benefit (or cost) of the transaction and thus limits the potential credit risk up to a point in time. It still has the potential for a future uncollectible recovery if the counter-party defaults after a period of time. A similar swap structure could be deployed to smooth development on smaller liability books of business, swapping actual emergence with that on a larger, more predictable book.

One area where all of the alternative transactions appear challenged is capital credit from a rating agency perspective. Again, this is because of shortcomings or weaknesses in the rating agency models. The fact of a transaction in each case shows that internal economic capital models were likely assigning greater capital credit to the transaction than the rating agency models and so provided a motivation for management to complete it. For example, even though personal auto is actually a capital provider in many cases, it does still have the potential for extreme losses — from a single large claim in Europe, or from unexpected inflation, for example — and removing the capital charge for this tail will lower the net charge, or increase the net benefit, measured from an economic perspective.

Outlook for Other RisksBased on our analysis what are the prospects for securitizing other classes of property casualty business? Likely solutions will revolve around an aggregate stop loss structure on a well understood book of business, extending the auto and health transactions. Contender classes from an actuarial modeling perspective include:

• Workers’ compensation, with a cap on individual loss sizes

• Commercial auto, as a natural extension of personal auto

• Medical malpractice, where most of the risk is frequency risk associated with tort reform, and where the Study provides a good historical benchmark

• Lower risk general liability

• Data rich specialty liability lines such as D&O or aviation

The Study systemic risk parameters for commercial auto and workers’ compensation are the lowest of the commercial lines, at 24 and 27 percent respectively and only 17 and 19 without the underwriting cycle impact. Medical malpractice currently shows a risk level of 36 percent. General liability, as a large class, has a higher risk level of 36 percent. In part this estimate is inflated owing to the disparate lines grouped together under general liability. The classes identified above show some of the potential subclasses that could be suitable for ILS transactions.

Workers’ compensation risk in the aggregate layers reviewed here is not commonly bought but would be attractive at the right pricing, and would have excellent rating agency capital characteristics for monoline writers, especially as part of a long-term reinsurance strategy. Payout patterns for workers compensation are very long, but typically stable for smaller claims, and could be handled contractually through actuarial and claims review and pre-agreed development factors. These transactions would effectively have an “indemnex” trigger: indemnity on claim counts but index or quasi-index on severity. Aon Benfield has deployed this approach successfully in the past in its BobCat product.

Aviation is a very data rich line and is typically reinsured; with appropriate pricing between the ILS and primary market, deals would be very attractive. An index approach could be used to solve the long payout lags for liability claims.

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The attraction for commercial auto is providing aggregate and occurrence protection in a single cover, with no inner limit. The very good exposure base (units or miles driven), increasing sophistication of primary pricing, relatively low systemic volatility (only 24 percent), and greater demand for higher primary limits make commercial auto an excellent ILS contender.

Medical malpractice is also a significantly reinsured line of business, especially by monoline writers who would obtain maximal rating agency capital credit from an aggregate transaction. It is another very data rich line of business with good overall risk characteristics.

In the light of the expiring U.S. government coverage, one line that unfortunately does not fit the requirements for securitized risk is terrorism. The key failure is modeling, where the underlying loss process is more driven by social and non-constant factors than would likely be acceptable to investors. Post 9/11 experience also showed losses were highly adversely correlated with asset market returns.

It is clear from our analysis that the outlook for ILS structures outside their traditional bounds of catastrophe risk is very bright. As an industry we are better equipped to model the underlying exposures than ever before, thanks in part to analyses like this study. We understand the true economic benefit of aggregate transactions. And we have a number of alternative approaches available to shorten emergence and loss settlement lags. Aon Benfield continues to believe that over the next five years we will see a number of landmark transactions brought successfully to market to further expand the reach of alternative capital, lower the cost of production for our clients, and to provide them with a consistent competitive advantage in the market. We look forward to working with our clients on these transactions.

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Sources and Notes

Port

folio

Ris

k

Insurance Portfolio RiskAsset Portfolio Risk

Number of Stocks Volume

Insu

ranc

e Ri

sk

Portfolio Risk

SystemicMarket Risk

SystemicInsurance

Risk

Naïve Model

Cover

Image: Wagendrift Dam wall, Estcourt, KwaZulu-Natal Province, South AfricaPhotographer/Artist: Cuan Hansen

Foreword

Sources:

A.M. Best, Axco Insurance Information Services, Impact Forecasting 2012 Annual Global Climate and Catastrophe Report, SNL Financial

Global Risk Parameters and U.S. 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), Dirección General de Seguros (Spain), DNB (Netherlands), Ernst & Young Annual Statements (Israel), Finma (Switzerland), FMA (Austria), FSA (U.K.), HKOCI (Hong Kong), http://www.bapepam.go.id/perasuransian/index.htm (Indonesia), ICA (Australia), 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), Romanian Insurance Association, Slovak Insurance Association, SNL Financial (U.S.), 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 Insurance Association of Pakistan, The Statistics of Japanese Non-Life Insurance Business, Turkish Insurance and Reinsurance Companies Association, Yearbooks Of China’s Insurance, and annual financial statements

Notes:

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 behavior is illustrated in the left hand 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, see right chart. The Study calculates this systemic risk by line of business and country. The Naïve Model on the right hand plot 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.

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U.S. Reserve Adequacy and Risk

Sources:

SNL Financial

Notes:

See the Aon Benfield Analytics U.S. P&C Industry Statutory Reserve Study for additional analysis at: http://thoughtleadership.aonbenfield.com/Documents/20130612_ab_analytics_industry_reserves_study_2012.pdf

Global Correlation between Lines

Sources:

FSA (U.K.), Yearbooks Of China’s Insurance

Macroeconomic Correlation

Sources:

Bloomberg, Case-Schiller U.S. National Home Price Index, U.S. Bureau of Economic Analysis, U.S. Bureau of Labor & Statistics

Global Premium, Profitability & Opportunities

Sources:

A.M. Best, Aon Hewitt People Risk Index 2013, Aon Political Risk Map 2013, Aon Terrorism & Political Violence Map 2013, Axco Insurance Information Services, Bloomberg, Ernst & Young, Fitch Ratings, IMF World Economic Outlook Database April 2013 Edition, KPMG, Moody’s, Penn World Table Version 7.1, SNL Financial, Standard & Poor’s, World Bank Doing Business 2013, World Bank World Development Indicators July 2013

Notes:

Page 13 Table — P&C GWP from Axco converted to USD by Axco, GDP from IMF converted to USD using consistent Axco exchange rates.

Pages 14 & 15 — Results based on universe of U.S. statutory top level companies and single companies. Combined ratio calculated by combining accident year loss ratios from Schedule P with IEE expense ratios on a net basis.

Page 14 Table — Combined ratio percentiles are weighted by 10 year average premium volume.

Page 15 Transition Matrices — Transitions calculated using most recent 10 years of data. Individual company combined ratios below 10 percent or greater than 600 percent were excluded from the calculation.

Page 17 Table — Premium and growth are calculated using Axco data. 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).

Page 20 Table — GDP (PPP) is GDP in local currency adjusted using purchasing power parity (PPP) exchange rate into the U.S. 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.

Page 21 Table — Opportunity Index Calculation: For each combined ratio, growth and political risk statistic, countries were ranked and broken into quartiles. A score of 1 to 4 was then assigned to each metric based on quartile. Opportunity Index Score = one-third multipled by combined ratio score plus two-thirds multiplied by average of premium, GDP and population growth and political risk scores.

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Aon Benfield

For more information on the Insurance Risk Study or our analytic capabilities, please contact your local Aon Benfield broker or:

Stephen MildenhallGlobal Chief Executive Officer of Analytics for Aon+65 9233 [email protected]

Greg HeerdeHead of Analytics, Americas+1 312 381 [email protected]

Kelly SuperczynskiHead of Strategic Consulting +1 312 381 [email protected]

John MooreHead of Analytics, International+44 (0) 20 7522 [email protected]

George AttardHead of Analytics, Asia Pacific+65 6239 [email protected]

Marc BeckersHead of Analytics, EMEA+ 44 (0) 20 7086 [email protected]

Contacts

© 2013 Aon Benfield. This document is intended for general information purposes only and should not be construed as advice or opinions on any specific facts or circumstances. The comments in this summary are based upon Aon Benfield’s preliminary analysis of publicly available information. The content of this document is made available on an “as is” basis, without warranty of any kind. Aon Benfield disclaims any legal liability to any person or organization for loss or damage caused by or resulting from any reliance placed on that content. Aon Benfield reserves all rights to the content of this document.

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About Aon BenfieldAon Benfield, a division of Aon plc (NYSE: AON), is the world’s leading reinsurance intermediary and full-service capital advisor. We empower our clients to better understand, manage and transfer risk through innovative solutions and personalized access to all forms of global reinsurance capital across treaty, facultative and capital markets. As a trusted advocate, we deliver local reach to the world’s markets, an unparalleled investment in innovative analytics, including catastrophe management, actuarial and rating agency advisory. Through our professionals’ expertise and experience, we advise clients in making optimal capital choices that will empower results and improve operational effectiveness for their business. With more than 80 offices in 50 countries, our worldwide client base has access to the broadest portfolio of integrated capital solutions and services. To learn how Aon Benfield helps empower results, please visit aonbenfield.com.

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