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: 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: 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: 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: As the portion of inforce business valued under PBR grows, it becomes increasingly important to not only calculate reserves for point-in-time valuation but to also project reserves. This is especially critical for actuarial functions such as pricing, business strategy/forecasting, and asset adequacy testing. In this session, we will review PBR projection techniques based on work completed by the American Academy of Actuaries when developing the PBA Projection Practice Note. In addition, this session will examine specific challenges that can arise when actuaries use models to project reserves at future dates. Topics covered include mortality improvement, credibility, scenario generation, starting asset projections, and various other technical issues related to nested modeling requiring both inner and outer loop projections.

Description: While many know that machine learning is a big deal and even have a general idea of what it is, many do not know what machine learning can do for them. As an alternative to citing achievements or explaining algorithms, this article outlines the challenges that occur in statistics and the solutions that machine learning offers. Some of those challenges include correlated predictors, missing data, data interaction, and prediction intervals. Corresponding solutions include regularization technics, missing value imputation with KNN, tree based models, and cluster analysis for backtesting.

Description: This abstract describes a paper that investigates how to apply a stochastic mortality model in the presence of missing data, using 'multiple imputation'.

Description: Profile of an actuary in a non-traditional actuarial role: focusing on medical cost and analysis, both retrospective and prospective.

Description: This paper presents the fundamentals of creating and using projections. From Transactions of Society of Actuaries 1950, Vol. 2, No. 4.