Description: This abstract describes a paper that demonstrates the calculation of parameters for a Gamma-Exponential Mix distribution with moments matching the first three moments of the expected claims by amount for an arbitrary portfolio of life insurance policies.

Description: Chairperson's column for the October 2020 issue of Taxing Times with thoughts on the effects of COVID-19 on the Taxation Section.

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: 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: Papers: Multi-Population Longevity Models: A Spatial Random Field Approach– Nhan Huynh, Mike Ludkovski, Ph.D. - University of California at Santa Barbara, Howard Zail - Elucider, LLC. The Application of Affine Processes in Cohort Mortality Risk Models – Zhiping Huang, Michael Sherris, FSA, FIAA, FIA, Andres M. Villegas Ramirez, Ph.D., Jonathan Ziveyi, Ph.D. - UNSW Australia

Description: The Society of Actuaries' Committee on Life Insurance Research, Product Development Section and Reinsurance Section are pleased to make the following report available. Authored by Allen Klein and Karen Rudolph of Milliman, this paper presents the results of research that identifies laboratory tests that are not widely used in the life insurance industry but could have potential benefits for use in the life insurance underwriting process. In addition, the authors have provided an Excel workbook illustrating the calculation for determining mortality savings.

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: 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.