Description: The objective of this paper is to provide a practical guide with concrete case studies to help actuaries implement artificial intelligence and machine learning (AIML) to help accelerate the speed of analysis for life and annuity actuarial modeling. We do so by researching the existing literature regarding AIML and its applicability to stochastic modeling and exploring case studies.

Description: The SOA Research Institute along with the International Section, and the Social Insurance and Public Finance Section are pleased to make available a research report that compares international and domestic mandated paid family and medical leave programs. Special thanks to both Sections for their sponsorship of this effort.

Description: This report presents research into recent population mortality experience compiled by the Retirement Plans Experience Committee (RPEC) of the Society of Actuaries Research Institute as it pertains to development of mortality improvement assumptions for measuring obligations of retirement programs in the United States.

Description: This report presents research into recent population mortality experience compiled by the Retirement Plans Experience Committee of the Society of Actuaries Research Institute as it pertains to development of mortality improvement assumptions for measuring obligations of retirement programs in the United States.

Description: This document explores how climate change impacts retirement planning, investments, housing, and health across policy and economic dimensions through essays and funded research.

Description: The global doubling of information content has been estimated to occur at a rate of every 12 hours, and conceivably faster. This ‘infowhelm’ is a double-edged sword for insurers. While maximization of the global knowledge base can fuel innovation, it can occur only in the context of reasonable cost for a higher benefit. The insurance industry – underwriters and actuaries in particular – are challenged to constantly examine new innovations that promise to raise confidence and protective value for insurability, within legal limits. This report aims to be the first of several to alert the SOA of promising innovations for the profession.

Description: This report outlines a framework for interpretable machine learning algorithms for detecting fraud in health insurance. It discusses the challenges of using black-box machine learning models in the insurance industry and proposes various interpretable methods to enhance transparency and understanding.

Description: This report is a discussion of the significant challenges involved in attempting to research with robust analysis the impact of disparities in health care access, cost and quality of care on financial wellness across racial, ethnic, socioeconomic and other demographic groups in the U.S. for reasons other than or in addition to income, wealth or employment status.

Description: The SOA Research Institute Aging and Retirement Strategic Research Program and Retirement Section are pleased to make available a research report that examines megatrends and potential paradigm shifts, and how they may impact the future of retirement and retirement plans, as well as the macro forces that will shape those trends.

Description: Decentralized finance, or DeFi, is an emerging financial system powered by blockchain technology. This research report aims to introduce actuaries to DeFi and help them develop a solid understanding of DeFi. It will begin with addressing “what is DeFi?” by providing an introduction on blockchains and DeFi. It will then discuss in further detail the key characteristics, applications, opportunities, and risks of DeFi. After providing the foundation, this report will discuss the potential adoption of DeFi and its interaction with the current financial system (sometime referred to as traditional finance for contrast with DeFi), and the implications for practicing and aspiring actuaries. In addition, a glossary of terms used in DeFi and a brief history of the development of DeFi have been included in the appendix.