Description: background history of the insurance industry and the role of actuaries within it, followed by the current environment and anticipated future environment.

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: Panelists discuss the characteristics of and impediments associated with effective management of the long term care insurance market, particularly as it related to pricing, marketing, and underwriting. From the Record of the Society of Actuaries, Vol. 24, No. 2.

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

Description: View the complete issue for the August 2014 Reinsurance News newsletter.

Description: Panelists discuss the role of the valuation actuary in health insurance. From the Record of the Society of Actuaries, Vol. 24, No. 2.

Description: This 2000 word essay won the Joint Management Risk Section 2016 Essay Prize, summarizing the present challenges, potential solutions and Actuarial opportunities.

Description: This paper takes the position that the U.K. actuarial profession has still not come to a single view on financial economics, and the major divisions that remain continue to hamstring its policy development. From Current Pension Actuarial Practice in Light of Financial Economics Symposium, M-RS04-1.