Insurance Risk Study - Aon

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Insurance Risk Study Evaluating Solvency II Factors Solvency II is scheduled to take effect no later than January 1, 2013. The fifth quantitative impact study (QIS 5) is in progress with a deadline of October 2010 for individual insurers and mid-November 2010 for groups. QIS 5 is likely the key test for most insurers across Europe. The Standard Formula factors were designed to be appropriate for the entire market — meaning a typical company of average size — so larger insurers with greater diversification will find the formula generates conservative capital requirements. Moreover, in QIS 5, the formula reflects added concerns that emerged from the 2008 financial crisis. Insurers now have heightened incentives to develop full or partial internal models as an alternative to the Solvency II Standard Formula. At this stage, the most important aspect of preparing for Solvency II is correct parameterization, driven by access to data. Insurers may face serious challenges to their IT systems. They will need some reference point as they undertake the various Solvency II tests: evaluating the statistical quality of the data, calibrating and validating the models they are using. The non-life Solvency Capital Requirement (SCR) is predominantly driven by premium risk, reserve risk and catastrophe risk. Since many companies with catastrophe exposure purchase excess of loss reinsurance, premium and reserve risk will be the key drivers of capital. Solvency II vs. Insurance Risk Study There are four key differences between the Solvency II factors and those in the Insurance Risk Study. Key Differences 6 Solvency II Insurance Risk Study Standard deviations of gross loss ratios Based on loss ratios at end of first year Coefficients of variation of gross loss ratios Based on ultimate loss ratios Excludes catastrophe risk Includes catastrophe risk Average-sized company, parameter and process risk Large company, parameter risk only Standard Deviations vs. Coefficients of Variation In Solvency II, the premium risk factors are calculated as standard deviations of historical loss ratios. Within the Standard Formula, these standard deviations are applied on the total volume of premium rather than to the premium net of loadings for costs, commissions and profit. Whether this overestimates the risk, and thus the capital requirement, depends on the company and the line of business. Certainly the Regulator has made some conservative assumptions: expenses are assumed to have the same volatility as the losses, and no profit is assumed over the cycle. If insurers disagree with these assumptions they must apply for a partial internal model. One-Year Emergence vs. View of Ultimate The Standard Formula premium risk factors and the corresponding Insurance Risk Study factors appear below. For ease of comparison, we have restated our factors as standard deviations rather than coefficients of variation. Non-Life Premium Risk, Gross of Reinsurance QIS 5 CEIOPS Risk Study Line StDev StDev # Obs StDev # Obs Motor — TPL 10.0% 11.5% 209 12.0% 4,631 Motor — Other 7.0% 8.5% 107 n/a n/a Marine, Aviation & Transit 17.0% 23.0% 37 29.6% 2,623 Fire 10.0% 15.0% 138 17.4% 4,751 General Liability 15.0% 17.5% 101 19.9% 3,443 Credit 21.5% 28.0% 58 27.6% 570 The factors proposed by CEIOPS and those used in the QIS 5 exercise can be made comparable with the factors in this Study through appropriate adjustments. If we use Motor TPL as an example, the CV in this Study corresponds to a standard deviation of 12.0 percent. The Study standard deviation is calculated from an ultimate perspective. We can use the same dataset that was used in our analysis to recalculate it from a one-year perspective, producing a standard deviation of 8.7 percent. Finally, the Study parameter reflects the non-diversifiable premium risk for a large insurance company whereas the QIS 5 parameters used in the Standard Formula represent an averagesized insurance company. As expected the QIS 5 parameter, 10.0 percent, is higher than systemic-only parameter of 8.7 percent for motor TPL.
Solvency II Correlation Coefficients Not surprisingly, correlation will be an important determinant of capital requirements. Solvency II Correlation Coefficients Motor - TPL Motor - Other Marine, Aviation & Transit These coefficients are more conservative than we would derive from calculating linear correlation since they must consider nonlinear tail correlation. The factors applied were derived mainly from an analysis of German market data for the years 1998 through 2002. As an example, for the correlation between motor TPL and general liability, the average correlation was 28 percent using the data of 89 firms and 1,269 observations. The final coefficient selected was 50 percent, as seen above. In this case, we find that the Solvency II correlations are significantly higher than many of the observed correlations for European insurers. The correlation matrix for Germany appears below, and corresponds to the larger matrix on page 13 of this Study. Insurance Risk Study — Germany Fire General Liability Motor — TPL 50% 50% 25% 50% 25% Motor — Other 50% 25% 25% 25% 25% Marine, Aviation & Transit Credit 50% 25% 25% 25% 25% Fire 25% 25% 25% 25% 25% General Liability 50% 25% 25% 25% 50% Credit 25% 25% 25% 25% 50% Motor Marine, Aviation & Transit Property General Liability Motor 20% 7% 6% 26% Marine, Aviation & Transit 20% 22% 10% 45% Property 7% 22% 0% 31% General Liability 6% 10% 0% -3% Credit 26% 45% 31% -3% Credit Aon Benfield S2Metrica: ReMetrica Modeling for Proposed Solvency II Developing an internal model can be a significant investment of time and resources. To assist our clients, Aon Benfield has developed S2MetricaSM , a standalone tool built on ReMetrica ® technology. S2Metrica builds a simplified internal model from QIS 5 inputs, supplemented with details about large losses, cat losses, reinsurance, and the asset portfolio. It also has a built-in economic scenario generator. Standard output reports include: > Profit and loss accounts for different return periods > Year-end balance sheets > Comparisons between Standard Formula capital requirements and those generated by the S2Metrica internal model Using S2Metrica, clients can quickly construct a competent baseline model, freeing them to focus on critical tasks such as parameterization and appropriate customization. ReMetrica is Aon Benfield’s innovative financial modeling tool and the engine of S2Metrica. Insurers increasingly turn to financial modeling to help them achieve their corporate objectives. Each insurer has its own distinct objectives, risks, corporate structure, and reinsurance strategy. Using the ReMetrica software platform, insurers can build adaptable and flexible models that capture their risks better than the Solvency II Standard Formula and fully recognize their risk mitigation strategies. In particular, ReMetrica allows insurers to: > Create ”off-the-shelf” internal models that cover both assets and liabilities > Use customizable templates to monitor internal metrics and Solvency II requirements such as Fair Value and SCR > Model highly customized reinsurance structures > Integrate partial models, such as non-life and health lines, in a full internal model covering all aspects of the balance sheet The combination of the Insurance Risk Study with ReMetrica allows our clients to parameterize their models in an optimal way and to make informed decisions about risk transfer through reinsurance or the capital markets. 7
Page 1 and 2: Insurance Risk Study Fifth Edition
Page 3 and 4: Foreword Since the first internal A
Page 5: Underwriting Volatility for Major L
Page 9 and 10: Industry Reserve Adequacy: How Long
Page 11 and 12: Year-Over-Year Change in Gross Loss
Page 13 and 14: Germany Japan U.K. U.S. Accident &
Page 15 and 16: Americas - Liability Europe - Liabi
Page 17 and 18: Size and Correlation Insurers of di
Page 19 and 20: Managing Inflation Risk Risk manage
Page 21 and 22: Global Market Review With rates con
Page 23 and 24: Global Premium, Loss Ratio and Vola
Page 25 and 26: Afterword: The Greatest Risk In las
Page 27 and 28: For more information on the Insuran

Insurance Risk Study - Aon

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