Description: The Individual Life Experience Committee is holding a competition encouraging actuaries and other interested parties to predict 2017 industry mortality based on a data set containg 2009 - 2016 data. The competition is not only about predicting mortality, but also about explaining and presenting the results.

Description: This report covers the latest emerging trends in U.S. population mortality. The SOA relied upon data furnished by the Centers for Disease Control and Prevention (CDC). Observations are based on the CDC’s recent release of 2021 mortality experience, along with prior mortality experience data from 1999 through 2020.

Description: LIMRA, Reinsurance Group of America (RGA), the Society of Actuaries (SOA) Research Institute, and TAI have collaborated on an ongoing effort to analyze the impact of COVID-19 on the individual life insurance industry’s mortality experience and share the emerging results with the insurance industry and the public. This report documents a high-level analysis of the claims that have been reported.

Description: The Mortality Improvement Life Working Group released a recommendation for a set of improvement factors that vary by gender and attained age to be used in conjunction with the 2008 Valuation Basic table or the 2015 Valuation Basic table for AG-38 purposes.

Description: This article discusses important implications of the upcoming Long-Duration Targeted Improvements (LDTI) accounting change for the modeling actuary. We discuss the modeling implications of new GAAP standards for Market Risk Benefit (MRB), including identification of MRBs, implementation of fair valuation in actuarial systems and retroactive determination of at-issue valuation inputs for transition. We also examine the modeling implications of the other aspects of the accounting change, including Liability for Future Policy Benefit (LFPB), Deferred Acquisition Cost (DAC), and other transition and disclosure requirements

Description: Latest development in IFRS 17 including a first look at companies disclosures and financial impacts, as well as a discussion of some of the run time issues that companies face.

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: 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.