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Insurance Risk Study Eighth Edition 2013
Empower Results®
Insurance Risk Study
Contents 3 Foreword 5 Global Risk Parameters
12 Global Premium, Profitability & Opportunities
8 U.S. Reserve Adequacy and Risk
29 Afterword: Extending Insurance-Linked Securities
10 Global Correlation between Lines
33 Sources and Notes
11 Macroeconomic Correlation
35 Contacts
Aon Benfield
Foreword 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? 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.
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Insurance Risk Study
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.
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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.
Aon Benfield
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
Property
Motor Thailand Israel Japan France Taiwan South Korea Hungary Australia Switzerland Austria Spain Germany Czech Republic Mexico Bolivia Turkey Uruguay Italy India Netherlands Chile Brazil Pakistan Colombia Dominican Republic Poland Canada Argentina U.K. Malaysia Vietnam South Africa U.S. Peru El Salvador China Singapore Honduras Venezuela Slovakia Indonesia Denmark Ecuador Panama Romania Hong Kong Nicaragua Greece Philippines
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% 18% 22% 22% 22% 23% 25%
Americas
37% 41% 46% 50%
Denmark Israel South Africa Germany Australia Spain Austria Italy Switzerland U.K. Canada Bolivia Chile Netherlands Turkey Malaysia France Japan Poland India China Hungary Uruguay Venezuela El Salvador South Korea Vietnam U.S. Ecuador Honduras Panama Argentina Pakistan Colombia Slovakia Nicaragua Romania Dominican Republic Hong Kong Brazil Indonesia Singapore Philippines Greece Taiwan Mexico Peru 64% Thailand Asia Pacific
12% 14% 15% 16% 16% 17% 17% 18% 20% 21% 22% 23% 25% 25% 26% 27% 27% 33% 33% 34% 34% 34% 35% 37% 38% 42% 42% 43% 43% 45% 46% 47% 51% 53% 53% 55% 57% 61% 62% 65% 66% 68% 70% 77% 84% 93% 96%
134%
Europe, Middle East & Africa
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Insurance Risk Study
U.S. Risk Parameters The 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. Coefficient of Variation of Gross Loss Ratio | 1992–2012
All Risk Private Passenger Auto Auto Physical Damage Commercial Auto Workers’ Compensation Warranty
No Underwriting Cycle Risk 14%
Private Passenger Auto
17%
Auto Physical Damage
24% 27%
19%
Warranty
31%
31%
36%
Commercial Multi Peril
Medical PL – Occurrence
36%
Medical PL – Occurrence
Other Liability – Occurrence
38%
Other Liability – Occurrence
Special Liability
39%
Special Liability
Other Liability – Claims-Made
40%
Other Liability – Claims-Made Medical PL – Claims-Made
Products Liability – Occurrence
47%
Products Liability – Occurrence
Homeowners
47%
Homeowners
Other Reinsurance – Liability Fidelity and Surety International Reinsurance – Property Reinsurance – Financial Special Property Products Liability – Claims-Made
Other
54%
Reinsurance – Liability
67%
Fidelity and Surety
71% 85%
U.S. Underwriting Cycle The underwriting cycle acts simultaneously across many lines of business, driving correlation between the results of different lines and amplifying the effect of underwriting risk to primary insurers and reinsurers. Our analysis demonstrates that the cycle increases volatility substantially for all major commercial lines, as shown in the table. For example, the underwriting volatility of 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.
35% 41% 50% 44% 50% 57%
Special Property Products Liability – Claims-Made 137%
32%
56%
96% 100%
30% 26%
Reinsurance – Property Reinsurance – Financial
93%
37%
26%
International
72%
Financial Guaranty
6
17%
Workers’ Compensation
Commercial Multi Peril
43%
16%
Commercial Auto
30%
Medical PL – Claims-Made
13%
62% 59% 50%
Financial Guaranty
101%
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%
Aon Benfield
Fidelity & Surety
Credit
29%
16%
Workers’ Compensation
Marine, Aviation & Transit
57%
23%
General Liability
47%
10%
Property
14%
Bolivia
Motor Personal
Argentina
Motor
Accident & Health
Property Commercial
Property Personal
Motor Commercial
Coefficient of Variation of Loss Ratio for Each Line by Country
Americas 9%
274%
Brazil
13%
65%
50%
72%
70%
49%
45%
72%
Canada
14%
22%
17%
35%
34%
40%
65%
104%
Chile
12%
25%
49%
58%
23%
Colombia
13%
53%
25%
16%
76%
68%
89% 52%
Dominican Republic
13%
61%
86%
72%
Ecuador
23%
43%
51%
92%
El Salvador
17%
38%
15%
97%
Honduras
18%
45%
10%
243%
9%
93%
Nicaragua
Mexico
46%
55%
58%
Panama
25%
46%
18%
Peru
16%
96%
Uruguay
11%
U.S.
16%
Venezuela
18%
63%
65%
44% 170% 99%
23%
23%
54%
39%
130%
35% 14%
24%
43%
47%
36%
38%
37%
27%
71%
20%
230%
Asia Pacific Australia
8%
16%
23%
32%
54%
34%
51%
38%
26%
20%
16%
86%
22%
65%
13%
30%
66%
132%
52%
65%
5%
33%
11%
10%
18%
7%
Malaysia
15%
27%
119%
30%
36%
89%
Pakistan
13%
51%
Philippines
64%
70%
Singapore
18%
68%
China
17%
Hong Kong
41%
India
12%
Indonesia
22%
Japan
16%
62% 34% 29%
10%
30% 69% 78% 87%
123%
36% 72%
74%
87%
41%
75%
23%
73%
17%
34%
38%
11%
30%
21%
13%
20%
South Korea
7%
7%
42%
33%
Taiwan
7%
7%
84%
50%
Thailand
4%
134%
Vietnam
15%
42%
Austria
8%
17%
Czech Republic
9%
134%
163% 40%
52% 79%
Europe, Middle East & Africa
Denmark France Germany
13%
49%
22%
12%
15%
15%
18%
18%
27%
6%
27%
30%
28%
36%
23%
60%
17%
29%
26%
9%
16% 77%
Hungary
8%
34%
Israel
5%
14%
56%
Italy
12%
18%
25%
19%
43%
42%
Netherlands
12%
25%
25%
51%
34%
33%
67%
35%
39%
33%
13%
33%
46%
22%
11%
50%
81%
26%
38%
12%
61%
80%
25%
32%
4%
Poland
14%
33%
Romania
37%
57%
Slovakia
22%
53%
South Africa
15%
Spain
8%
Switzerland
8%
Turkey
11%
U.K.
14%
17%
12%
21%
20% 14%
8%
26%
19%
21%
19% 84%
51%
64%
88%
15% 8%
17%
25%
50%
Greece
83%
50%
22%
112%
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. 7
Insurance Risk Study
U.S. Reserve Adequacy and Risk 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.
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.
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.
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
U.S. Reserve Estimated Adequacy and Development Summary (USD billions)
Line
Estimated Reserves
Booked Reserves
Remaining Redundancy at YE 2012
Favorable or (Adverse) Development 2008
2009
2010
2011
2012
Average
Years at Run Rate
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
17.8
15.9
(1.9)
(12.6)
7.0
0.4
(0.4)
(0.6)
(1.3)
N/A
567.4
576.6
9.2
1.8
18.5
10.5
12.7
9.9
10.7
0.9
Financial Guaranty Total
Year-over-Year Change in Reserve Adequacy The 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.
8
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.
Aon Benfield
Drivers of 2012 Reserve Redundancy or Deficiency (USD billions)
All Lines 14 12
+11.7
(9.9)
10
+4.1
+9.2
2012 Accident Year Redundancy/Deficiency
2012 Year End Reserve Redundancy/Deficiency
+5.6
+10.1
8 +3.3
6 4 2 0
2011 Year End Reserve
Personal Lines Redundancy/Deficiency
2012 Calendar Year Change in Booked Reserves
12 10 8
+7.6
2012 Calendar Year Favorable/Adverse Loss Emergencies
(7.1)
6
+4.0
4 2 0 2011 Year End Reserve
Redundancy/Deficiency Commercial Lines
2012 Calendar Year Change in Booked Reserves
12
2012 Calendar Year Favorable/Adverse Loss Emergencies
2012 Accident Year Redundancy/Deficiency
2012 Year End Reserve Redundancy/Deficiency
10 8 6
+4.1
(2.8)
4 (0.8)
2
(1.4)
0 -2
2011 Year End Reserve Redundancy or (Deficiency)
2012 Calendar Year Change in Booked Reserves
2012 Calendar Year Favorable or (Adverse) Loss Emergencies
2012 Accident Year Redundancy or (Deficiency)
(0.9)
2012 Year End Reserve Redundancy or (Deficiency)
U.S. Reserves Looking Forward We 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.
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Insurance Risk Study
Global Correlation between Lines 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.
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.
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.
Credit
Engineering
General Liability
Marine, Aviation & Transit
Motor
Property
Accident & Health
Agriculture
Accident & Health
China
40%
18%
15%
20%
19%
32%
55%
42%
9%
38%
16%
6%
11%
11%
15%
27%
21%
25%
13%
48%
27%
25%
26%
31%
Agriculture
40%
Credit
18%
42%
Engineering
15%
9%
24%
General Liability
20%
38%
11%
24%
25%
Marine, Aviation & Transit
19%
16%
15%
13%
25%
Motor
32%
6%
27%
48%
26%
31%
31%
Property
55%
11%
21%
27%
31%
9%
9% 37%
37%
25%
Commercial Motor
70%
43%
Commercial Property
36%
36%
41%
Private Motor
43%
Commercial Lines Liability
Household & Domestic
70%
Financial Loss
25%
Commercial Property
Commercial Motor
Accident & Health
Commercial Lines Liability
Accident & Health
U.K.
36%
-15%
20%
21%
36%
17%
49%
37%
41%
-11%
16%
67%
-18%
70%
32%
3%
-30%
Financial Loss
-15%
17%
-11%
-18%
Household & Domestic
20%
49%
16%
70%
3%
Private Motor
21%
37%
67%
32%
-30%
17% 17%
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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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.
GDP Growth
Unemployment Change
3-Month T-Bill Rate
1-3 Year Treasuries
AAA-AA 3-5 Year Spread
BBB 3-5 Year Spread
S&P 500 Returns
VIX
Property Returns
Inflation (CPI-U)
Inflation (PPI)
Inflation (CPI-U)
U.S. Macroeconomic Correlations
78%
-2%
0%
32%
23%
-12%
-24%
-13%
-21%
9%
5%
-6%
28%
6%
-6%
-18%
-7%
-21%
7%
-57%
-1%
27%
-62%
-70%
5%
-42%
49%
12%
26%
47%
39%
-4%
44%
-36%
98%
-21%
-55%
-8%
-17%
12%
-23%
-55%
9%
-18%
9%
82%
-43%
62%
-63%
-34%
66%
-52%
-52%
15%
Inflation (PPI)
78%
GDP Growth
-2%
5%
Unemployment Change
0%
-6%
-57%
3-Month T-Bill Rate
32%
28%
-1%
12%
1-3 Year Treasuries
23%
6%
27%
26%
98%
AAA-AA 3-5 Year Spread
-12%
-6%
-62%
47%
-21%
-23%
BBB 3-5 Year Spread
-24%
-18%
-70%
39%
-55%
-55%
82%
S&P 500 Returns
-13%
-7%
5%
-4%
-8%
9%
-43%
-34%
VIX
-21%
-21%
-42%
44%
-17%
-18%
62%
66%
-52%
9%
7%
49%
-36%
12%
9%
-63%
-52%
15%
Property Returns
-33% -33%
11
Insurance Risk Study
Global Premium, Profitability & Opportunities 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.
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.
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.
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.
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.
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
Premium per Capita vs Income per Capita for Top 50 P&C Markets Premium per Capita
log Premium per Capita (USD)
5,000
500
GDP per Capita
50
5 500
5,000
50,000
log GDP per Capita (USD) Individual Countries
12
y = 0.0008x1.2881 R = 89.8%
Top 50 Aggregate
500,000
Aon Benfield
Global P&C Gross Written Premium by Product LIne
GDP (USD billions)
Premium / GDP Ratio
GDP per Capita
Country
P&C GWP (USD billions)
U.S.
503.7
15,684.8
314.2
3.2%
49,922
U.S.
503.7
Japan
92.4
5,948.3
127.6
1.6%
46,613
China*
163.7
China
84.5
8,230.1
1,354.0
1.0%
6,078
Japan
118.3
Germany
66.9
3,389.6
81.9
2.0%
41,379
Germany
67.4
U.K.
64.7
2,443.6
63.2
2.6%
38,637
U.K.
64.7
France
63.5
2,600.3
63.4
2.4%
41,008
France
63.5
South Korea
53.3
1,155.9
50.0
4.6%
23,114
South Korea
53.3
Canada
41.9
1,817.6
34.8
2.3%
52,190
Brazil*
44.9
Italy
38.3
2,007.6
60.8
1.9%
33,008
Canada
41.9
Australia
34.1
1,534.3
22.8
2.2%
67,396
Russia*
40.2
Spain
28.8
1,347.7
46.2
2.1%
29,194
Italy
39.9
Brazil
24.4
2,257.7
198.4
1.1%
11,382
India*
36.3
Russia
18.6
2,021.9
141.9
0.9%
14,247
Australia
34.1
Netherlands
14.5
770.6
16.8
1.9%
45,994
Spain
28.8
Switzerland
14.5
637.6
8.0
2.3%
79,683
Mexico*
23.4
Belgium
11.9
483.1
11.1
2.5%
43,545
Indonesia*
17.5
Norway
10.6
500.9
5.0
2.1%
99,428
Turkey*
15.8
Argentina
10.4
476.2
41.0
2.2%
11,606
Netherlands
15.3
9.3
1,177.1
114.9
0.8%
10,247
Saudi Arabia*
14.5
Switzerland
14.5
Canada Rest of Americas China
U.S.
Japan South Korea Rest of APAC
Middle East & Africa
France
Rest of Europe
Germany U.K. Rest of Euro Area
Property: USD433 billion Brazil Canada Rest of Americas China Japan South Korea Rest of APAC
U.S.
France Germany U.K. Middle East & Africa
Rest of Euro Area
Rest of Europe
Liability: USD312 billion Brazil Canada Rest of Americas China Japan U.S.
South Korea
Rest of APAC France Middle East & Africa Rest of Europe
Germany U.K. Rest of Euro Area
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.
Mexico
Population (millions)
Country
P&C GWP (USD billions)
Top 50 P&C Markets by Gross Written Premium
Motor: USD614 billion Brazil
Top 50 P&C Markets Assuming at Least Two Percent Penetration
Austria
9.2
397.3
8.5
2.3%
46,930
India
8.4
1,824.7
1,223.2
0.5%
1,492
Belgium
11.9
Sweden
8.4
526.6
9.5
1.6%
55,197
Norway
10.6
Denmark
8.3
313.8
5.6
2.6%
56,221
Sweden
10.5
Turkey
7.8
792.8
74.9
1.0%
10,587
Argentina
10.4
Poland
7.2
485.7
38.9
1.5%
12,488
Poland
9.7
South Africa
5.8
384.3
51.2
1.5%
7,507
Taiwan*
9.4
Venezuela
5.3
382.4
29.5
1.4%
12,954
Austria
9.2
Thailand
4.9
365.6
64.4
1.3%
5,679
Denmark
8.3
South Africa
7.6
Venezuela
7.6
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
Thailand
7.3
Ireland
3.9
209.7
4.6
1.9%
45,744
Colombia
7.2
Israel
3.8
240.5
7.7
1.6%
31,247
U.A.E.*
7.1
Czech Republic
3.8
196.0
10.6
1.9%
18,577
Malaysia
6.0
Chile
3.7
268.2
17.4
1.4%
15,410
Singapore*
5.5
U.A.E.
3.7
359.2
5.5
1.0%
64,882
Nigeria*
5.5
Portugal
3.6
212.0
10.5
1.7%
20,113
Chile
5.3
Taiwan
3.6
473.9
23.3
0.8%
20,325
Hong Kong*
5.2 5.0
New Zealand
3.4
170.2
4.4
2.0%
38,338
Finland
Indonesia
3.3
878.0
244.5
0.4%
3,592
Greece*
4.9
Greece
3.3
248.4
11.3
1.3%
21,984
Israel
4.8
Hong Kong
2.5
262.9
7.2
0.9%
36,651
Portugal
4.2
Saudi Arabia
2.4
727.3
29.0
0.3%
25,085
Ireland
4.2
Singapore
2.4
276.4
5.4
0.9%
51,147
Czech Republic
3.9
Romania
1.8
169.3
21.3
1.0%
7,931
New Zealand
3.4 3.4
Morocco
1.6
97.4
32.5
1.7%
2,994
Romania
Ecuador
1.3
80.9
15.2
1.6%
5,311
Morocco
1.9
Nigeria
1.1
275.1
164.8
0.4%
1,670
Ecuador
1.6
Luxembourg
1.0
56.6
0.5
1.7%
106,910
Bulgaria
0.9
51.0
7.3
1.7%
7,036
1,315.2
66,128.8
4,966.2
2.0%
13,316
Grand Total
Note: Ranks are based on total P&C Gross Written Premium
Luxembourg
1.1
Bulgaria
1.0
Total
1,585.2
* Ranking increased by insurance penetration
13
Insurance Risk Study
U.S. Profitability by Line of Business The 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 Private Passenger Auto Liability
2012 Net Earned Premium USD millions
Net Accident Year Loss Ratio 10yr
10yr Combined Ratio Percentiles Net Expense Net Combined Ratio Ratio 10yr 10yr
10%
25%
50%
75%
90%
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%
102
74%
36%
110%
66%
73%
94%
116%
116%
452,396
71%
27%
98%
90%
92%
98%
103%
104%
International All Lines
14
Aon Benfield
Underwriting Outperformance in the Long Run 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).
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).
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 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 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.
One Year Transition Matrix — All Lines Combined Ratio
Five Year Transition Matrix — All Lines Combined Ratio
Decile at End of Period 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%
10%
Decile at Start of Period
Decile at Start of Period
10%
Decile at End of Period 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%
1%
2%
3%
4%
5%
10%
22%
27%
20%
5%
80%
5%
8%
10%
9%
9%
14%
10%
16%
13%
7%
90%
3%
3%
2%
4%
3%
7%
10%
20%
32%
15%
90%
8%
9%
8%
8%
9%
9%
10%
13%
14%
12%
100%
5%
3%
3%
2%
3%
3%
4%
6%
15%
56%
100%
15%
9%
7%
5%
3%
4%
6%
7%
12%
33%
Top Performers 10%
100%
Worst Performers
15
Insurance Risk Study
Developing a Robust Growth Strategy The 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.
Profitability
Demographics
Contender Geographies
Deep dive on strategy, organic growth and M&A opportunities
Political Stability
Scale Regulation
Growth
Broker Surveys
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?
16
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).
Aon Benfield
Cumulative Net Expense Ratio Cumulative Net Combined Ratio
Premium / GDP Ratio
Cumulative Net Loss Ratio
P&C GWP (USD millions)
Country
Annualized Premium Growth
5yr Combined Ratio CV
Top 50 P&C Markets Ranked by Gross Written Premium by Region
503,657 41,860 24,408 10,400 9,307 5,292 4,318 3,719 1,328 604,289
3.2% 2.3% 1.1% 2.2% 0.8% 1.4% 1.2% 1.4% 1.6% 2.7
4.8% 13.3% -3.9% 18.5% 2.2% -27.9% 15.9% 7.1% 11.2% 4.8%
2.9% 9.1% 13.8% 21.7% 7.8% -2.5% 19.2% 22.5% 15.7% 4.1%
1.0% 4.7% 11.1% 20.0% 4.2% 15.8% 14.1% 15.7% 17.4% 2.1%
78.4% 70.8% 53.5% 67.0% 71.4% 62.1% 59.6% 51.2% 51.6% 76.2%
74.7% 72.1% 55.1% 66.6% 68.7% 64.4% 59.9% 52.4% 53.0% 73.4%
73.4% 70.4% 56.3% 65.6% 69.1% 65.3% 60.7% 51.7% 53.5% 72.3%
27.1% 28.3% 36.4% 42.9% 33.7% 34.2% 46.7% 40.8% 32.7% 28.2%
27.1% 28.6% 33.1% 39.7% 33.6% 32.0% 47.2% 43.6% 33.4% 28.0%
26.8% 105.5% 28.4% 99.1% 28.8% 89.9% 40.2% 109.9% 33.8% 105.0% 31.8% 96.3% 46.6% 106.3% 44.2% 92.0% 33.5% 84.3% 27.4% 104.4%
101.9% 100.7% 88.2% 106.3% 102.3% 96.4% 107.2% 96.0% 86.4% 101.4%
100.2% 98.8% 85.2% 105.8% 102.9% 97.1% 107.3% 95.9% 87.1% 99.8%
4.2% 3.9% 4.8% 2.4% 2.4% 1.3% 1.9% 3.3% 4.1% 3.9%
66,941 64,732 63,472 38,316 28,812 18,574 14,517 14,456 11,882 10,553 9,160 8,392 8,254 7,755 7,157 5,813 4,422 3,909 3,816 3,770 3,699 3,597 3,251 2,400 1,768 1,637 1,136 982 852 414,024
2.0% 2.6% 2.4% 1.9% 2.1% 0.9% 1.9% 2.3% 2.5% 2.1% 2.3% 1.6% 2.6% 1.0% 1.5% 1.5% 1.8% 1.9% 1.6% 1.9% 1.0% 1.7% 1.3% 0.3% 1.0% 1.7% 0.4% 1.7% 1.7% 1.9
-0.4% 4.3% 10.5% -10.2% -9.4% 18.1% 0.7% -1.8% 4.1% 12.4% -5.1% 12.4% -5.6% 7.9% -6.7% -20.3% -2.7% -2.9% 7.9% -11.3% 4.0% -2.4% -2.2% 14.1% -9.4% 2.7% 8.5% 7.3% -9.6% 0.9%
0.2% -3.3% -0.5% -3.7% -5.2% 15.2% -2.5% 7.5% 0.7% 8.9% 0.1% 0.6% 0.2% 1.6% 5.8% 1.4% 1.6% -6.6% 2.4% -2.5% 2.7% -5.6% -1.2% 12.5% -8.8% 8.1% 2.1% 1.3% -5.5% -0.5%
1.1% -1.4% 3.9% -2.7% -3.4% 9.7% 2.9% 7.3% 3.7% 5.4% 1.1% 2.8% 1.4% 7.3% 3.8% 0.3% 2.2% -3.4% 5.6% 0.8% 12.3% -3.7% 5.7% 11.6% -5.1% 10.1% 12.3% -11.1% -0.3% 1.3%
75.3% 68.2% 73.2% 74.9% 71.0% 64.7% 88.1% 72.7% 70.4% 74.9% 70.4% 75.0% 76.9% 77.3% 66.3% 60.9% 85.7% 71.2% 76.3% 62.5% 76.7% 69.6% 56.2% 72.5% 73.7% 63.1% 48.0% 63.6% 55.3% 73.4%
75.1% 67.4% 75.6% 76.8% 72.0% 67.4% 88.1% 70.8% 72.8% 75.0% 71.3% 73.5% 78.2% 77.2% 69.2% 63.3% 80.8% 72.2% 77.6% 64.2% 70.8% 70.8% 61.7% 71.0% 74.5% 64.6% 47.8% 64.8% 54.8% 74.1%
73.6% 67.0% 74.2% 75.3% 71.3% 66.7% 87.6% 71.9% 72.1% 75.2% 70.5% 73.6% 76.4% 77.1% 64.2% 64.0% 80.1% 71.1% 78.2% 62.7% 70.2% 69.3% 64.0% 71.5% 76.4% 66.8% 47.2% 63.2% 54.0% 73.3%
25.8% 33.6% 24.3% 25.0% 20.7% 21.9% 13.1% 26.0% 28.1% 15.6% 30.8% 17.6% 16.5% 27.9% 29.8% 25.7% 20.7% 26.7% 32.5% 29.5% 18.9% 23.0% 38.1% 21.1% 44.3% 34.6% 30.9% 37.2% 34.0% 24.7%
25.3% 34.1% 24.8% 24.1% 21.0% 21.0% 13.1% 26.1% 27.6% 16.1% 29.2% 17.4% 17.2% 28.8% 31.1% 25.2% 20.7% 28.5% 31.7% 28.6% 17.9% 22.7% 37.1% 19.8% 37.9% 33.9% 31.2% 37.9% 36.3% 24.6%
25.1% 34.2% 24.5% 23.9% 21.0% 20.3% 13.6% 26.1% 27.9% 16.5% 28.8% 17.6% 17.2% 26.5% 32.9% 24.5% 20.3% 27.6% 31.0% 26.6% 15.8% 22.8% 38.7% 19.0% 35.1% 33.4% 31.8% 36.3% 35.7% 24.6%
101.0% 101.9% 97.5% 99.9% 91.7% 86.6% 101.2% 98.7% 98.5% 90.5% 101.2% 92.6% 93.4% 105.2% 96.1% 86.6% 106.4% 97.8% 108.8% 91.9% 95.5% 92.6% 94.3% 93.6% 118.0% 97.7% 79.0% 100.9% 89.3% 98.1%
100.4% 101.5% 100.4% 100.9% 93.0% 88.4% 101.2% 96.8% 100.4% 91.1% 100.4% 90.9% 95.4% 106.0% 100.2% 88.6% 101.6% 100.7% 109.3% 92.8% 88.7% 93.5% 98.7% 90.8% 112.3% 98.4% 79.0% 102.7% 91.1% 98.7%
98.7% 101.2% 98.6% 99.2% 92.3% 87.0% 101.2% 98.0% 99.9% 91.7% 99.3% 91.2% 93.7% 103.6% 97.1% 88.5% 100.4% 98.7% 109.3% 89.3% 85.9% 92.1% 102.7% 90.4% 111.4% 100.2% 78.9% 99.5% 89.7% 97.9%
2.7% 1.2% 3.1% 3.1% 1.4% 3.3% 0.6% 2.2% 1.4% 2.6% 1.7% 1.6% 3.7% 3.4% 4.1% 2.3% 3.7% 5.8% 0.3% 5.3% 7.2% 2.5% 6.7% 2.3% 3.1% 3.0% 1.4% 5.2% 3.0% 1.2%
92,376 84,453 53,268 34,069 8,421 4,927 4,251 3,597 3,359 3,288 2,467 2,367 296,842
1.6% 1.0% 4.6% 2.2% 0.5% 1.3% 1.4% 0.8% 2.0% 0.4% 0.9% 0.9% 1.4%
13.5% 18.1% 22.5% 12.3% 10.6% 27.4% 7.9% 6.7% 16.2% 20.0% 14.0% 1.2% 16.2%
9.0% 26.1% 17.8% 12.1% 16.2% 20.7% 12.8% 9.1% 17.5% 13.7% 7.1% 9.4% 15.6%
6.3% 26.3% 12.4% 10.5% 8.5% 13.3% 9.6% 2.8% 10.3% 13.0% 7.6% 10.3% 12.4%
75.7% 55.2% 78.3% 74.4% 88.8% 74.2% 68.4% 58.5% 113.8% 53.8% 65.5% 56.3% 70.7%
70.0% 63.7% 77.4% 72.4% 89.8% 62.7% 65.4% 57.4% 96.9% 55.7% 60.5% 55.8% 70.4%
68.6% 65.8% 77.2% 74.4% 88.0% 60.5% 65.6% 55.7% 87.6% 54.7% 60.0% 55.9% 70.4%
33.9% 34.2% 22.2% 27.5% 28.9% 35.7% 27.2% 37.4% 32.9% 33.4% 46.8% 33.8% 31.0%
34.5% 35.0% 22.8% 27.8% 31.5% 36.9% 27.4% 39.4% 35.6% 33.3% 40.8% 33.5% 31.7%
34.5% 36.0% 22.8% 28.9% 31.9% 37.2% 28.1% 41.8% 36.2% 34.1% 39.9% 32.9% 32.1%
109.7% 89.4% 100.5% 101.8% 117.7% 110.0% 95.6% 95.9% 146.7% 87.2% 112.3% 90.1% 101.7%
104.5% 98.6% 100.2% 100.2% 121.3% 99.6% 92.8% 96.8% 132.4% 89.0% 101.3% 89.3% 102.0%
103.0% 101.7% 100.1% 103.3% 120.0% 97.6% 93.6% 97.5% 123.9% 88.7% 99.9% 88.9% 102.5%
3.9% 9.7% 2.5% 5.3% 3.4% 7.8% 5.1% 1.3% 15.2% 1.6% 7.5% 2.1% 1.6%
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%
1yr
3yr
5yr
1yr
3yr
5yr
1yr
3yr
5yr
1yr
3yr
5yr
Americas U.S. Canada Brazil Argentina Mexico Venezuela Colombia Chile Ecuador Subtotal
Europe, Middle East & Africa Germany U.K. France Italy Spain Russia Netherlands Switzerland Belgium Norway Austria Sweden Denmark Turkey Poland South Africa Finland Ireland Israel Czech Republic U.A.E. Portugal Greece Saudi Arabia Romania Morocco Nigeria Luxembourg Bulgaria Subtotal Asia Pacific Japan China South Korea Australia India Thailand Malaysia Taiwan New Zealand Indonesia Hong Kong Singapore Subtotal Global
17
Insurance Risk Study
Growth Markets and Out or 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.
Motor
Property
Loss Ratio Performance
Loss Ratio Performance Out Performers Out Performers
Out Performers Out Performers
Low Growth
Australia Austria Bulgaria Canada Czech Republic Denmark France Japan Luxembourg Mexico Netherlands Nigeria Poland Romania Saudi Arabia South Africa Spain Taiwan Thailand U.K.
7,560 2,173 32 6,557 918 1,043 11,093 17,343 Austria 201 1,506 Bulgaria Czech 3,327 Republic 294 Denmark 1,023 Finland 204 Hong Kong 184 Japan 668 New Zealand 6,401 Switzerland 362 Taiwan 291 U.S. 15,633
Belgium Finland Germany Ireland Israel Italy Norway Portugal Sweden U.S.
Belgium 3,252 Canada1,264 France 15,547 Germany888 Greece 635 Ireland5,335 Israel 1,676 Italy 1,079 210 Luxembourg 125,554 Mexico Netherlands Poland Portugal Romania Russia South Africa South Korea Spain Sweden Turkey U.K.
Low Growth
Brazil Chile China Colombia Ecuador Greece 3,786Kong Hong 617 India 1,757 Indonesia 2,850 Malaysia 1,875Zealand New 449 Russia 55,298 Singapore 1,098 Switzerland 6,291 Turkey 2,014 U.A.E. 196,918 Venezuela
1,753 774 6,875 1,001 243 441 1,271 Brazil 1,626 China 434 Colombia455 Ecuador 295 Indonesia 2,120 Nigeria 714 Norway3,238 Thailand377 U.A.E. 1,258 Venezuela 633
4,548 Argentina 19,891 Morocco 26,246 South Korea 28,267 2,056 1,660 2,249 25,985 497 4,758 5,989 4,454 1,746 1,168 10,540 2,686 11,204 12,798 3,329 3,903 25,132
Argentina 4,124 Australia379 Chile 39,468 India Malaysia Morocco Saudi Arabia Singapore
Under Performers Under Performers
18
14,640 63,083 1,938 538 1,144 294 3,284 3,343 1,121 3,812
High Growth 4,595 12,954 1,093 4,679 2,259 841 1,250 991
High Growth
Low Growth
Belgium Bulgaria Canada Czech Republic Greece Hong Kong India Luxembourg Malaysia Mexico Netherlands Romania South Korea Singapore Taiwan U.K. U.S.
Austria3,374 Bulgaria 203 Canada 15,411 Czech Republic 1,095 Denmark754 France 747 Germany 2,115 Ireland 284 Italy 1,537 Norway3,044 Poland5,202 Portugal396 South Africa 2,597 Spain 662 Sweden1,221 Switzerland 23,967 Taiwan 181,184
Austria Denmark Finland France Germany Ireland Israel Italy Japan Norway Poland Portugal South Africa Spain Sweden
Belgium 3,201 Finland4,360 Greece1,283 Israel 27,233 Japan24,010 Luxembourg 1,361 Mexico 931 Netherlands 6,996 Romania 19,736 Turkey4,798 U.K. 1,681 U.S. 1,043 2,458 9,613 4,247
Low Growth
9,160 852 41,860 3,770 Argentina 8,254 Brazil 63,472 China 66,941 Colombia 3,909 Ecuador 38,316 Indonesia 10,553 Morocco 7,157 Nigeria 3,597 Russia 5,813Arabia Saudi 28,812 Switzerland 8,392 Turkey 14,456 U.A.E. 3,597 Venezuela 11,882 Australia 4,422 Chile 3,251Zealand New 3,816 Thailand 92,376 982 9,307 14,517 1,768 7,755 64,732 503,657
1,682 8,015 Brazil14,495 Chile 1,379 Ecuador547 Indonesia 1,710 Malaysia256 Nigeria 548 Russia5,860 Saudi Arabia 965 Singapore 4,928 Thailand 2,527 U.A.E.1,320 Venezuela 846 Argentina 10,016 Australia 1,851 China 1,987 Colombia 1,293 Hong Kong India Morocco New Zealand South Korea
Under Performers Under Performers
24,408 3,719 1,328 3,288 4,251 1,136 18,574 2,400 2,367 4,927 3,699 5,292
High Growth
10,400 34,069 84,453 4,318 2,467 8,421 1,637 3,359 53,268
High Growth
Aon Benfield
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.
Liability
All Lines
Loss Ratio Performance
Combined Ratio Performance Out Performers Out Performers
Out Performers Out Performers
Low Growth
Australia Austria Bulgaria Canada Czech Republic Denmark France Japan Luxembourg Austria 3,786 Mexico Bulgaria 617 Netherlands Czech Republic Nigeria 1,757 Denmark 2,850 Poland Finland 1,875 Romania Hong Kong 449 Saudi Arabia Japan 55,298 South Africa New Zealand Spain 1,098 Switzerland Taiwan6,291 Taiwan 2,014 Thailand U.S. U.K.196,918
Low Growth
Belgium Canada France Germany Greece Ireland Israel Italy Luxembourg Mexico Netherlands Poland Portugal Romania Russia South Africa South Korea Spain Sweden Turkey U.K.
4,548 Belgium Finland 19,891 Germany 26,246 Ireland 28,267 Israel 2,056 Italy 1,660 Norway 2,249 Portugal 25,985 Sweden497 U.S. 4,758 5,989 4,454 1,746 1,168 10,540 2,686 11,204 12,798 3,329 3,903 25,132
7,560 2,173 32 6,557 918 1,043 11,093 17,343 201 1,506 Brazil 3,327 China 294 Colombia 1,023 Ecuador 204 Indonesia 184 Nigeria 668 Norway 6,401 Thailand 362 U.A.E. 291 Venezuela 15,633 Argentina 3,252 1,264 Australia 15,547 Chile 888 India 635 Malaysia 5,335 Morocco 1,676Arabia Saudi 1,079 Singapore 210 125,554
Brazil Chile China Colombia Ecuador Greece Hong Kong India14,640 63,083 Indonesia 1,938 Malaysia 538 New Zealand Russia1,144 294 Singapore 3,284 Switzerland Turkey3,343 U.A.E.1,121 3,812 Venezuela 4,595 Argentina 12,954 Morocco South1,093 Korea 4,679 2,259 841 1,250 991
Under Performers Under Performers
1,753 774 6,875 1,001 243 441 1,271 1,626 434 455 295 2,120 714 3,238 377 1,258 633
High Growth
4,124 379 39,468
High Growth
Low Growth
Austria Bulgaria Canada Czech Republic Denmark France Germany Ireland Italy Norway Poland Portugal South Africa Spain Sweden Switzerland Taiwan
9,160 Belgium Bulgaria852 41,860 Canada Czech3,770 Republic Greece8,254 63,472 Hong Kong India66,941 3,909 Luxembourg 38,316 Malaysia 10,553 Mexico 7,157 Netherlands 3,597 Romania South5,813 Korea 28,812 Singapore 8,392 Taiwan U.K.14,456 U.S. 3,597
Belgium Finland Greece Israel Japan Luxembourg Mexico Netherlands Romania Turkey U.K. U.S.
11,882 Austria 4,422 Denmark 3,251 Finland France3,816 92,376 Germany Ireland 982 Israel 9,307 Italy14,517 Japan1,768 7,755 Norway 64,732 Poland 503,657 Portugal South Africa Spain Sweden
Low Growth
3,374 203 15,411 1,095 754 Brazil 747 Chile 2,115 Ecuador 284 Indonesia 1,537 Malaysia 3,044 Nigeria 5,202 Russia 396 Saudi 2,597Arabia Singapore 662 Thailand 1,221 U.A.E. 23,967 Venezuela 181,184 Argentina 3,201 Australia 4,360 China 1,283 Colombia 27,233 Hong Kong 24,010 India 1,361 Morocco 931 New Zealand 6,996 South Korea 19,736 4,798 1,681 1,043 2,458 9,613 4,247
Argentina Brazil China24,408 3,719 Colombia 1,328 Ecuador 3,288 Indonesia 4,251 Morocco Nigeria1,136 18,574 Russia Saudi 2,400 Arabia 2,367 Switzerland 4,927 Turkey U.A.E.3,699 5,292 Venezuela 10,400 Australia Chile34,069 New 84,453 Zealand 4,318 Thailand 2,467 8,421 1,637 3,359 53,268
1,682 8,015 14,495 1,379 547 1,710 256 548 5,860 965 4,928 2,527 1,320 846
High Growth
10,016 1,851 1,987 1,293
Under Performers Under Performers
19
High Growth
Insurance Risk Study
Aon Political Risk Assessment
Aon Terrorism Risk Assessment
Aon Hewitt People Risk Assessment
World Bank Relative Ease of Doing Business
10.0%
7.2%
35.0%
High
Medium
Medium high
More difficult
66.0
1.8%
5.2%
30.0%
Low
Negligible
Medium low
Easiest
Austria
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
Easiest
Belgium Brazil Bulgaria Canada
Unemployment Rate
12.6
27.2%
Inflation Rate
44.9%
61.2%
Net Foreign Direct Investment — USD billions
68.1%
5.9%
General Government Debt as % of GDP
5.4%
42,641
Actual Individual Consumption as % of GDP
18,113
1.5%
Government Consumption as % of GDP
1.1%
22.8
GDP Per Capita — PPP, USD
41.0
4.3%
Population 5yr Annualized Growth
7.2%
970.8
Population — millions
743.1
Australia
GDP 5yr Real Growth
Argentina
Country
GDP — PPP, USD billions
Corporate Tax Rate
Macroeconomic, Demographic and Social Indicators
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
Easiest
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 difficult
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
Easier
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
Easiest Easiest
Chile
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
China
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
Easier
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%
Medium
High
Medium high
Easiest
Czech 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
Easier
Denmark
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
Easiest
Ecuador
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 difficult
Finland
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
Easiest
France
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
Easiest
Germany
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
Easiest
Greece
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
Easier
Hong 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
Easiest
India
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 difficult
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%
Medium
High
Medium high
More difficult
Ireland
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
Easiest
Israel
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
Easiest
Italy
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
Easier
Japan
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
Easiest
Luxembourg Malaysia Mexico Morocco
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
Easier
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
Easiest
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
Easier
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 difficult
Netherlands
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
Easiest
New 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
Easiest
Nigeria
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 difficult
Norway
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
Easiest
Poland
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
Easier
Portugal
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
Easiest
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
Easier
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 difficult
Romania Russia Saudi 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
Easiest
Singapore
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
Easiest
South 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
Easiest
South 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
Easiest
Spain
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
Easiest
Sweden
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
Easiest
Switzerland
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
Easiest
Taiwan
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
Easiest Easiest
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
Turkey
Thailand
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
Easier
U.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
Easiest Easiest
U.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
U.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
Easiest
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
Venezuela
20
Aon Benfield
Country Opportunity Index 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 Quartile 1 1 2 2 4 4 4 4 8 8 8 11 11 11 Quartile 2 14 14 16 16 16 16 20 20 20 20 20 20 Quartile 3 20 20 28 28 28 28 28 28 28 28 28 28 Quartile 4 38 38 38 38 42 42 42 42 42 47 48 49 50
Country Singapore Indonesia* Saudi Arabia Nigeria U.A.E. Ecuador Chile Brazil Norway Malaysia* Sweden Venezuela Switzerland
5yr Cumulative Net Combined Ratio
5yr Annualized Premium Growth
GDP 5yr Real Growth
Population 5yr Annualized Growth
Political Risk
88.9% 88.7% 90.4% 78.9% 85.9% 87.1% 95.9% 85.2% 91.7% 93.6% 91.2% 97.1% 98.0%
10.3% 13.0% 11.6% 12.3% 12.3% 17.4% 15.7% 11.1% 5.4% 9.6% 2.8% 15.8% 7.3%
6.0% 7.7% 8.3% 8.7% 3.8% 6.4% 5.6% 4.9% 2.3% 5.9% 2.7% 3.7% 2.9%
2.2% 1.4% 3.1% 2.7% 4.3% 1.5% 1.0% 0.9% 1.3% 1.6% 0.8% 1.6% 1.3%
Low Medium Medium High Medium low High Low Medium low Low Medium low Low Very high Low
Russia South Africa Czech Republic Hong Kong Morocco Australia Denmark Thailand France Canada* Belgium South Korea
87.0% 88.5% 89.3% 99.9% 100.2% 103.3% 93.7% 97.6% 98.6% 98.8% 99.9% 100.1%
9.7% 0.3% 0.8% 7.6% 10.1% 10.5% 1.4% 13.3% 3.9% 4.7% 3.7% 12.4%
3.5% 3.9% 2.0% 4.2% 6.1% 4.3% 0.8% 4.5% 1.7% 2.8% 2.1% 4.6%
-0.1% 1.1% 0.5% 0.7% 1.1% 1.5% 0.5% 0.4% 0.5% 1.2% 0.9% 0.6%
Medium Medium Low Low Medium Low Low Medium high Low Low Low Medium low
Colombia* India Bulgaria Spain Poland Taiwan Germany Luxembourg China Argentina Israel New Zealand
107.3% 120.0% 89.7% 92.3% 97.1% 97.5% 98.7% 99.5% 101.7% 105.8% 109.3% 123.9%
14.1% 8.5% -0.3% -3.4% 3.8% 2.8% 1.1% -11.1% 26.3% 20.0% 5.6% 10.3%
5.7% 8.6% 2.4% 0.8% 5.1% 4.6% 2.4% 1.6% 11.1% 7.2% 5.3% 2.3%
1.2% 1.4% -1.0% 0.6% 0.4% 0.3% -0.1% 1.9% 0.5% 1.1% 2.2% 0.9%
Medium Medium low Medium low Low Medium low Medium low Low Low Medium High Medium low Low
Portugal Ireland U.S. Turkey* Italy Austria Finland Netherlands Mexico* Japan U.K. Greece Romania
92.1% 98.7% 100.2% 103.6% 99.2% 99.3% 100.4% 101.2% 102.9% 103.0% 101.2% 102.7% 111.4%
-3.7% -3.4% 1.0% 7.3% -2.7% 1.1% 2.2% 2.9% 4.2% 6.3% -1.4% 5.7% -5.1%
0.5% 0.4% 2.3% 4.8% 0.2% 2.3% 1.1% 1.6% 3.3% 1.5% 1.2% -2.8% 2.0%
-0.1% 0.9% 0.8% 1.3% 0.6% 0.4% 0.5% 0.5% 1.4% -0.1% 0.7% 0.3% -0.2%
Low Low Low Medium Low Low Low Low Medium low Low Low Medium Medium low
*These countries represent potential contender geographies discussed in the following pages.
21
Insurance Risk Study
Profitability 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 Growth, Profitability and Volatility Country
5yr Annualized Premium Growth
Canada
5yr Cumulative Net Loss Ratio
5yr Cumulative Net Expense Ratio
5yr Cumulative Net Combined Ratio
5yr Combined Ratio CV
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%
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.
Demographics 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.
42,734
7.0%
69.9%
85.6%
45.4
1.5%
7.3%
26.0%
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%
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%
Malaysia
22
Corporate Tax Rate
1.2%
46.6
Unemployment Rate
GDP Per Capita — PPP, USD
34.8
5.7%
Inflation Rate
Population 5yr Annualized Growth
Net Foreign Direct Investment — USD billions
Population— millions
2.8%
502.9
Canada
Consumption as % of GDP
GDP 5yr Real Growth
1,488.3
Colombia
Country
Government Spending as % of GDP
GDP—PPP, USD billions
General Government Debt as % of GDP
Contender Geography Demographics
Aon Benfield
Regulatory, Sovereign and Stability Perspectives Even 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. 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
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.
23
Insurance Risk Study
Indonesia
Mexico
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.
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.
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.
24
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.
Aon Benfield
Market Opportunities and Pathways to Entry Understanding 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)
31-Dec-13
Multi-National
Composite
10-Jun-13
Multi-National
24-Oct-12
Multi-National
30-Sep-12 6-Jun-12
Target Lines of Business
Valuation (USD millions)
1,103
21-Dec-12
Local
Investment Management
Non-Life
N/A
11-Oct-12
Multi-National
Composite
Life
146
12-Apr-12
Local
Non-life
532
Multi-National
Non-Life
N/A
17-Oct-11
Regional
Investment Management
N/A
Multi-National
Non-Life
N/A
10-May-11
Multi-National
Non-life
166
N/A 1,729
Mexico
Colombia
15-Jun-07
Acquirer
Malaysia
Canada
17-Mar-08
Date
Multi-National
Consumer Finance
N/A
4-Dec-12
Local
Composite
Multi-National
Real Estate for Public Agencies
N/A
18-Oct-12
Multi-National
Non-Life
12-Sep-12
Multi-National
Composite
293
5-Mar-12
Local
Composite (Reinsurance)
N/A
16-Aug-11
Local
Life
200
Indonesia
31
865
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
25
Insurance Risk Study
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.
26
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.
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.
27
Insurance Risk Study
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.
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.
Turkey
This 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.
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.
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Summary
Aon Benfield
Afterword: Extending Insurance-Linked Securities 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 groundbreaking 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 noncatastrophe 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.
Characteristics of Cat Risk Securitizations Why 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. Q uick 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. 29
Insurance Risk Study
Existing Non-Traditional Securitizations 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
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Aon Benfield
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 Risks Based 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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Aon Benfield
Sources and Notes Cover Image: Wagendrift Dam wall, Estcourt, KwaZulu-Natal Province, South Africa Photographer/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.
Asset Portfolio Risk
Insurance Portfolio Risk
Portfolio Risk
Insurance Risk
Portfolio Risk
Systemic Insurance Risk
Systemic Market Risk
Naïve Model
Number of Stocks
Volume
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Insurance Risk Study
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
Contacts For more information on the Insurance Risk Study or our analytic capabilities, please contact your local Aon Benfield broker or:
Stephen Mildenhall Global Chief Executive Officer of Analytics for Aon +65 9233 0670
[email protected] Greg Heerde Head of Analytics, Americas +1 312 381 5364
[email protected] Kelly Superczynski Head of Strategic Consulting +1 312 381 5351
[email protected]
John Moore Head of Analytics, International +44 (0) 20 7522 3973
[email protected] George Attard Head of Analytics, Asia Pacific +65 6239 8739
[email protected] Marc Beckers Head of Analytics, EMEA + 44 (0) 20 7086 0394
[email protected]
About Aon Benfield Aon 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.
© 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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