Description: The author applies actuarial skills to solve a perceived problem with respect to objectively determining an annual champion in college football.

Description: The article describes the nature of actuarial research conducted at the Goldenson Center at the University of Connecticut. One of the research projects to create a National Retirement Sustainability Index is analyzed in detail. It demonstrates how the work we do at the Goldenson Center is both an art and a science while satisfying the following research criteria we adhere to at the Goldenson Center:  >The problem has to come from industry  >The solution has to add value to what is currently done in practice  >The solution has to be implementable

Description: This article describes a simple but powerful tool for use by valuation actuaries and auditors when evaluating current assumptions for use in GAAP net premium reserve methods that require retrospective updating for actual experience and assumption changes. As a supplement, this tool can fill some holes left by existing tools. It produces results that can be compared to materiality thresholds at any level of aggregation, from a single reserve cohort up to the combination of all cohorts for all products subject to retrospective net premium reserve requirements. It can also serve as a benchmarking tool for estimated the possible effects of an assumption change or to help in explaining the effects of an actual assumption change.

Description: Applying Predictive Analytics for Insurance Assumptions Setting: high level principles.

Description: Methods and assumptions used in the valuation of savings by external care vendors

Description: This article provides a brief overview of the current state of machine learning (ML) and artificial intelligence (AI) as they apply to actuarial science, including discussion around the integration of actuarial judgment with ML and AI. It concludes with an example of explainable ML through a python tool known as SHAP (SHapley Additive exPlanations), which is able to explain the key drivers behind individual ML or AI predictions.

Description: The April/May 2013 edition of The Actuary magazine—the Society of Actuaries’ flagship publication.

Description: Interview of people knowledgeable about risk adjustment and the use of social determinants of health with that context for Medicaid.

Description: This article introduces IT DevOps to actuaries and how it is applicable to them to improve their modeling efforts and make them more efficient.