Description: People naturally observe risk in the form of the range of experienced gains and losses which is usually represented in statistical terms by standard deviation. In most cases, there are not enough observed values to reliably discern the true amount of losses that are possible in extreme situations. Statistical techniques that have long been applied to insurance company risks are being used to extrapolate from observed risk to extreme tails of the distribution of gains and losses. These processes are essentially an extrapolation from the “known” risk of volatility near the mean to “unknown” risk of extreme losses. “Fat tails” is a term often applied to risks where the likely losses in rare situations significantly exceeds the predictions of a Gaussian (“thin tailed”) distribution. This paper will look at the relationship between the observed risk and the extreme risk in statistical insurance r isk models and discuss how we might create a discussion among model users about the appropriateness of that relationship for specific types of risks.

Description: People naturally observe risk in the form of the range of experienced gains and losses which is usually represented in statistical terms by standard deviation. In most cases, there are not enough observed values to reliably discern the true amount of losses that are possible in extreme situations. Statistical techniques that have long been applied to insurance company risks are being used to extrapolate from observed risk to extreme tails of the distribution of gains and losses. These processes are essentially an extrapolation from the “known” risk of volatility near the mean to “unknown” risk of extreme losses. “Fat tails” is a term often applied to risks where the likely losses in rare situations significantly exceeds the predictions of a Gaussian (“thin tailed”) distribution. This paper will look at the relationship between the observed risk and the extreme risk in statistical insurance r isk models and discuss how we might create a discussion among model users about the appropriateness of that relationship for specific types of risks.

Description: Statistics were invented to describe heterogeneity and are now applied to tackle alea. It may not be appropriate. Let's clarify their field of relevance.

Description: New Zealand is about to launch its first variable annuity with guaranteed lifetime withdrawal benefits. The product design is mindful of the lessons from the financial crisis in the United States, Europe and Japan.

Description: Actuaries are accustomed to considering how much conservatism is appropriate in their estimates, whether made for pricing or for mea- surement of liabilities. In the proposals for a new standard on accounting for insurance contracts, this conservatism is referred to by the International Accounting Standards Board IASB and the Financial Accounting Standard Board FASB of the United States as the risk adjustment.

Description: This article presents recent perspectives on the understanding and measurement of pandemic risk.

Description: Explains the method used to calculate Liquidity Cost Score and Price Impact Score. Describes the rationale for and applications of these methods.

Description: The author constructed the efficient frontier of new business sales by modeling the embedded value and economic capital against a universe of possible growth rates of the three lines of business in a typical three-year planning horizon. The ERM function can use the efficient frontier of new business to provide a more rigorous analysis of the impact of growth rates on the firm’s overall capital efficiency and value creation, hence forming a feedback loop with the businesses in the planning process to optimize the growth strategy.

Description: The author constructed the efficient frontier of new business sales by modeling the embedded value and economic capital against a universe of possible growth rates of the three lines of business in a typical three-year planning horizon. The ERM function can use the efficient frontier of new business to provide a more rigorous analysis of the impact of growth rates on the firm’s overall capital efficiency and value creation, hence forming a feedback loop with the businesses in the planning process to optimize the growth strategy.

Description: Panel discussion focused on the Effective Use of Capital. Topics included: 1. Definition of capital 2. Appropriate level of capital and surplus in a life insurance company 3. Alternatives for deploying capital 4. Returns a life company should demand on invested capital 5. How much a company should charge for lending its capital in reinsurance transactions