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: 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: 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: 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: The Society of Actuaries (SOA) is pleased to present historical U.S. population mortality rates by gender and single year of age for calendar years 2000-2020. To develop these rates, the SOA relied upon data furnished by the Centers for Disease Control and Prevention, Centers for Medicare and Medicaid Services, the U.S. Census Bureau, and the Social Security Administration. A document summarizing key observations and the process used to develop the rates, along with a table of the rates themselves, can be found below.

Description: Tree models have been found to provide a good fit to group long term disability recovery and mortality rates. This research paper provides an overview of tree models, and details how they have been used for developing these rates.

Description: This report explores the adoption and impact of artificial intelligence and large language models in the Greater China insurance industry, drawing from surveys and case studies.

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.