Description: Article Book Review The Future Of Risk by Calvert in The Actuary, December 1979, Volume 13, Number 10

Description: The paper argues that Risks Evaluation at its core is a psychological process that can lead to the special type of chaos described in modern Chaos Theory. It will argue that quantification and scientific modeling does not exempt risk assessment from the potential for deep biases. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

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: This paper outlines a risk measurement framework in which risk measures are derived by qualifying cash-flow-based risk measures on the state of the firm's debt capacity. This risk framework overcomes some of the weaknesses of the popular 'at-risk' framework. From 2007 Enterprise Risk Management Symposium, M-AS07-1.

Description: Enterprise risk management ERM is for the measurement and the management of all significant risks of the business holistically irrespective of types and sources. The study offers significant advances in the current debate on the performance of enterprise risk management, in particular, minimizing the existing gap between the academic understanding and practitioners’ experience on the topic.

Description: Panelists report on the status of activities by national associations in regard to risk-based capital requirements for health insurers. From the Record of the Society of Actuaries, Vol. 24, No. 2.

Description: A discussion of the need to connect the interrelated requirements of reserve requirements, capital requirements, risk management, IASB requirements and so forth.

Description: This research report is on the incorporation of flood and other catastrophe model results into pricing and underwriting.