1. Integrated Risk Management in Life Insurance Companies Dr. Etti G. Baranoff Virginia Commonwealth University Dr. Thomas W. Sager The University of Texas at Austin International Insurance Society Seminar Chicago July 19, 2006

2. Overview In this paper we use accounting data to map the spectrum of enterprise risks and enterprise risk management (ERM) tools of U.S. life insurers. To our knowledge, these are the first risk and tool maps to be based on statistical analysis of objective data, rather than on surveys of ex ante best practice desiderata and ex post practices. International Insurance Society Seminar Chicago July 19, 2006

3. Outline We use a two-step methodology to analyze risk space: –(1) cluster analysis of about 150 risk-related variables to group associated risks together; –(2) factor analysis to uncover hidden themes of each cluster. The same methodology is applied to ERM tool space variables. Then we lay the two maps side by side for comparison. International Insurance Society Seminar Chicago July 19, 2006

4. Expectations – Risk Space Theoretical conventional wisdom expects that risk space should be organized into the following risk categories: –Asset –Product –Operational –with significant cross-category overlap generated by financial risk (Capital structure) and the risk of asset/liability matching (ALM). International Insurance Society Seminar Chicago July 19, 2006

5. Figure 1. The Conventional View of Risk and ERM Tools Part A: Life Insurers’ Enterprise Risks Capital Structure (Financial risk) Asset/Liability Matching ASSET RISKPRODUCT RISKOPERATIONAL RISK  Default risk  Volatility risk (market risk)  Liquidity risk  Catastrophe risk  Incomplete contracts risk  Reserves risk  IT risk  Distribution risk  Regulatory risk  Legal risk  Globalization risk International Insurance Society Seminar Chicago July 19, 2006

6. The RISK categories correspond to the three major activities of life insurers: –Investing –Underwriting –Operations –major category-straddling activities of structuring capital and ALM. International Insurance Society Seminar Chicago July 19, 2006

7. Part B: Life Insurers’ Enterprise risk Management Tools Capital Structure (Financial risk) Management Tools Asset/Liability Matching Management Tools ASSET RISK Management Tools PRODUCT RISK Management Tools OPERATIONAL RISK Management Tools  Hedging/derivatives  Asset allocation management (Active vs. passive)  Reinsurance  Reserving  Securitization  Diversification  Control over agents and brokers  Organizational/corporate structure  Adherence to regulation  IT controls  Operational safety and loss controls Figure 1. The Conventional View of Risk and ERM Tools International Insurance Society Seminar Chicago July 19, 2006

8. Expectations – ERM Space The organization of tool space is expected to mirror the hypothetical organization of risk space, since insurers deploy the tools to mitigate the risks. ERM_Geneva Papers2006_Baranoff_Sager.docERM_Geneva Papers2006_Baranoff_Sager.doc International Insurance Society Seminar Chicago July 19, 2006

9. Figure 1. The Conventional View of Risk and ERM Tools International Insurance Society Seminar Chicago July 19, 2006

10. Overall Results/Contribution We find three risk clusters that represent asset, product, and operational risks. We also find five other risk clusters – some including aspects of financial and ALM risks. The structure of ERM space does not clearly match that of risk space. –Tool space seems to be thematically clustered more by tool than by the risk to be mitigated. –Within each space, we find complex relationships. –Some clusters are thematically relatively pure, whereas others are mixed, and there is a fair degree of overlap. International Insurance Society Seminar Chicago July 19, 2006

11. Emerging Risk Space Themes See Figure 4, Risk side: ERM_Geneva Papers2006_Baranoff_Sager.docERM_Geneva Papers2006_Baranoff_Sager.doc International Insurance Society Seminar Chicago July 19, 2006

12. Emerging ERM Space Themes See Figure 4, ERM side: ERM_Geneva Papers2006_Baranoff_Sager.docERM_Geneva Papers2006_Baranoff_Sager.doc International Insurance Society Seminar Chicago July 19, 2006[

14. High Level Results – Risk Space The empirical analysis finds three clusters that can be identified primarily with asset, product, and operational risks. In addition, five other clusters emerge, with distinct themes, including liquidity, financial, and reinsurance risk. International Insurance Society Seminar Chicago July 19, 2006

15. High Level Results – Risk (Cont.) A number of variables that might conventionally be thought of as product or operational risks are more closely aligned with other clusters. International Insurance Society Seminar Chicago July 19, 2006

16. High Level Results – Risk (Cont.) Some clusters, like cluster 6 (operational) are thematically relatively pure; but others, like cluster 1, involve a complex mix of themes. International Insurance Society Seminar Chicago July 19, 2006

17. High Level Results – ERM Space A conventional view of ERM tool space might expect risk mitigation tools to be organized into asset, product, and organizational clusters to mirror corresponding risk clusters. Summary – ERM (Cont.) But the only leg of the hypothetical triad for which we find a clear parallel is the operational leg (ERM cluster 8 with Risk cluster 6). International Insurance Society Seminar Chicago July 19, 2006

18. High Level Results – Risk and ERM Spaces Compared We tend to see ERM tools organized by type of tool to be used, rather than by type of risk to be mitigated. –The ERM tool space shares many of the structural characteristics of risk space – a similar number of clusters, some thematically pure clusters, some mixed, with some overlap. International Insurance Society Seminar Chicago July 19, 2006