Description: This paper uses a mortality surge model to estimate the total financial impact on the U.S. insurance industry of a flu pandemic. It does not attempt to determine the probability of such a pandemic.

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

Description: This discussion provides an overview of the SOA research process, reviews the new turnover tables and efforts to model probable outcomes of proposed legislation on the U.S. economy. From Record of Society of Actuaries, Vol. 22, No. 3.

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: The failure of a few large life insurers in the early 1990's led to public concern about the safety of annuities purchased by qualified retirement plans. As a result, the Department of Labor issued guidelines, known as the 'Safest Annuity Rule,' for selecting annuity providers. This study examines whether the Safest Annuity Rule is significantly changing the market for insured annuities issued to tax-qualified pension plans, particularly upon the termination of defined benefit plans. From Transactions of Society of Actuaries 1997-98 Reports.

Description: Full version of Risks and Rewards Newsletter, October 2003, Issue No. 43.

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.