Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.

Description: Regression to the mean is a phenomenon that arises when comparing sequential data points. It states that when an initial observation is extreme or an outlier, future observations will be closer to the average. Health care actuaries need to understand and be able to mitigate the effects of regression to the mean to avoid misapplying predictive models or misstating measurements of historical effects.

Description: The author discusses the use of genetic algorithms as they apply to actuaries, specifically the application of characteristics and their potential to solve life insurance asset and liability management problems. He also highlights various ways genetic algorithms can be used to solve a variety of actuarial problems.

Description: 2011 Enterprise Risk Management Symposium, Chicago. This paper highlights the impact that a change in conditional data would have on a variety of risk assessment models, with specific emphasis on investment forecasting.

Description: This session is from the 1976 Washington D.C. Meeting and discusses qualitative and quantitative models for forecasting. The session is a general teaching session and not for experts.

Description: In Medicaid rate development, actuaries have not historically shared models that developed the margin (i.e., underwriting gain) assumption. This is unfortunate, given the margin assumption is one of the most critical components of the rate development in ensuring financial solvency of the Medicaid managed care organizations (MCOs). In this session, we will discuss the primary components of the this assumption and will share working models that help actuaries quantify these components—including the cost of capital and risk (or contingency) margin. We expect a lively discussion as we “open the black box” and discuss these actuarial assumptions in the public for the first time.

Description: The author reviews the book, The Perfect Swarm: The Science of Complexity in Everyday Life, by Len Fisher. He provides his own interpretation of the power of the swarm and touts the book as a straightforward and informative introduction to various aspects of complexity science.

Description: The financing for Social Security is a pay-as-you-go system, rather than the full-reserve system utilized in private insurance, and the financing conditions of the trust funds have more uncertainty than does the reserve in private insurance. Traditionally, the financing conditions have been decided by a deterministic approach using economic and demographic assumptions that rely upon negotiation among experts at various government agencies. This paper proposes an econometric approach, called the 'co-integrated multivariate time series model,' for forecasting the financing conditions of the trust funds. This stochastic approach not only establishes the interrelationships but also clarifies the co-movements among the economic assumptions. Furthermore, it helps analyze the original assumptions rather than the differences of the nonstationary assumption variables adopted by researchers in the past that are more difficult to interpret. Use of this approach permits the assessment of the probability distribution of the future balance of trust funds instead of assessing estimates from the three alternative deterministic assumptions. This distribution will provide policy-makers with a better assessment of stability of the trust funds.

Description: A discussion of the process and results report “A Study of the Use of the Delphi Method, A Futures Research Technique for Forecasting Selected U.S. Economic Variables and Determining Rationales for Judgments.”

Description: This paper presents a method involving re-sampling 'with replacement but without random numbers', numerical convolutions for sums and quotients, and estimation of confidence intervals for trend in average size claim. In this paper, this method is applied to major medical claims.