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: 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: A multi-author collection exploring how catastrophe modeling can be adapted to life and health insurance, particularly in response to the 2025 Los Angeles wildfires.

Description: Private LTC insurers are paving the way for value-based care through working to implement care management programs that improve the lives of their policyholders before and during a claim. However, measuring the effectiveness of these new programs is a challenging task. In this article, we will explore powerful tools that can enhance traditional effectiveness studies and address some of their existing weaknesses.

Description: Guidance and a model for actuaries to use when performing their professional services related to Medicaid (Title XIX) and Children’s Health Insurance Program (CHIP or Title XXI) managed care capitation rate setting.

Description: This report evaluates the long-term mortality consequences of the COVID-19 pandemic from a cohort-based perspective using historical mortality data.

Description: This report analyzes insurance product design, morbidity trends, and pricing models for individuals with pre-existing illnesses in China to improve coverage for substandard health populations.

Description: Credibility is a mechanism for estimating a quantity of interest by combining subject experience and relevant experience to improve the estimate.

Description: This project enhances the current understanding of cyber risks in the smart home ecosystem from the insurance industry's perspective. In particular, the quantitative framework and pricing strategies developed in this project can be immediately adopted/adapted by actuaries to price the cyber risks for smart homes, a fast-growing insurance market.

Description: CMS has required hospitals to publish their chargemaster rates, cash discounts and negotiated rates as of January 1, 2021. Our panel is comprised of a data strategist, an executive from a large hospital system and an actuary.