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Town Hall Session/ RCM-2 CAS 2006 Ratemaking Seminar, March 13, 2006 Louise Francis, FCAS, MAAA Francis Analytics and Actuarial Data Mining [email protected] www.data-mines.com How Many Risk Load Actuaries Can Dance on the Head of a Shamrock? Remarks • Risk adjusted discount rates/internal rate of return approaches still relevant • Alternative beta calculations • Alternative denominator for cost of equity • Some older approaches such as risk loads based on percentiles still make sense in some contexts • The market seems to allow for superior strategy returns • Should we think of Risk Load as a topic within ERM? • Should we charge a “bad data” risk load? Financial & Actuarial Perspective Converge? • Risk Load= Systematic + Frictional Cost Simpler Methods are Sometimes Better • To some managements, our methods of computing risk loads seems very complex • Loads based on percentiles still used often for self-insurance pools and captives Augmentations of Beta • Base on correlation with insurance liabilities • SUMBETA – (Ibbotson, Risk Premium Project) • Take lag effects into account • For insurance companies generally results in larger betas Cost of Capital Denominator • What is an appropriate denominator • Usually GAAP surplus • Smith says this is the wrong denominator • Economic Value of Company = Market value of assets - Discounted value of liabilities + franchise value – insolvency put • Measure change in this value Return for Having an Edge: Geometric Maximization Edge f Odds f Amount of capital to allocate to bet “Bad Data” Risk Load • Moral Hazard problem • Customers supplying bad data may be poorer risks due to poorer management • Information has a cost • More uncertainty is associated with pricing based on sparse or inadequate data