Description: This presentation, session number 83CS at the 1999 Spring Meeting of the Society of Actuaries, held June 16-18 in Seattle, is a preview of an actual Course 7. The presenters, two experienced researchers, lead the discussion and a demonstration of a case study from the modeling Course 7. Discussion from participants is included. From the Record of the Society of Actuaries, Vol. 25, No. 2.

Description: Exploration of sources of volatility in retiree health valuations, noting how volatility arises and might be mitigated, with discussion of valuation parameters more problematic for retiree health benefits than for pensions. Three significant influences on retiree health valuation volatility are covered-- changes in benefit level, fluctuations in cost level, and alterations in eligibility for, or duration of, benefit – and attention focused on the last two. Specific conclusions result in recommendations, which are supported by practical examples contrasting volatile measurement results with those likely from the recommended practices. Theoretical discussion includes health claim variation, health trend usage, financial economics, option pricing, discount rates, and deterministic vs. stochastic modeling.

Description: The April 2016 Issue of The Modeling Platform

Description: A summary of Modeling Section-sponsored sessions at the 2016 Life/Annuity Symposium, covering model risk management, model governance, and model efficiency.

Description: Third article in a series on how to use predictive analytics to improve the development of long-term care projection assumptions.

Description: Describes using the new multi-risk scenario generator to create sensitivity tests at moderately adverse probability levels, resulting in margins to use for PBR.

Description: Presented at June 2002 Spring Meeting. A noted expert with a degree from the graduate program in Studies of the Future at the University of Houston-Clear Lake discusses long-term forecasting and planning, the future of information technology and technology transfer, strategic planning and the development of future scenarios.

Description: We highlight a new approach leveraging predictive analytics to identify high risk and rising risk opioid users for more effective screening and follow-up care.