Description: Expert discussion of three previous papers: Makeham-Type Mortality Models Mumpar-Victoria, An Extreme Value Analysis of Advanced Age Mortality Data Robertson, and Living to 100 and Beyond: An Extreme Value Study Han. From 2005 Living to 100 and Beyond Monograph, M-LI05-1.

Description: In session 10PD of the Washington Annual Meeting panelists discuss current pensioner mortality information as well as projected trends. From the Record of the Society of Actuaries, Vol. 23, No. 3.

Description: Experts' discussion of mortality laws and models. From 2005 Living to 100 and Beyond Monograph, M-LI05-1.

Description: Panelists at this session of the SOA 1998 Maui II Spring Meeting discuss details of the turnover assumption for the valuation of pension plans. A recently released SOA Turnover Study is discussed.

Description: Presented for discussion are two research reports: Public Employee Retirement Plans Research: Experience Studies, Valuation Reports and Unfunded Liabilities, and Pension Plan Termination in Ontario since 1988. From the Record of the Society of Actuaries, Vol. 21, No. 4a.

Description: Panelists at this session of the SOA 1998 Maui II Spring Meeting discuss the purpose and expectations for medical savings accounts [MSA] at the time the Health Insurance Portability and Accountability Act was enacted, and whether these expectations have been achieved.

Description: This paper demonstrates the calculation of the moments of the distribution of aggregate life insurance claims from seriatim inforce data, assuming that each record represents an independent Bernoulli trial with its own known probability of a claim, q. Continuous distributions matching the first three or four moments are identified.

Description: As a life reinsurer, understanding mortality risk is mission critical. Superior models of mortality risk lead to more competitive pricing in profitable market segments and more efficient use of capital. Surprisingly, modern statistical tools such as predictive modeling have not previously been used to model mortality data to gain this edge. In this paper, we present the use of a predictive modeling technique called projection pursuit regression PPR to model mortality data. We first describe the process of creating a PPR model using inter-company mortality data collected by the Individual Life Experience Committee of the Society of Actuaries, and present the resulting model. We then discuss the process of using this model as a starting point for creating a more detailed PPR model of internal company mortality data.

Description: Full version of Pension Section News, February 1999, Issue No. 39.

Description: Full version of Small Talk Newsletter, April 2000, Issue No. 15.