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 explores AI bias in insurance and health data, highlighting the ethical role of actuaries and offering cross-disciplinary guidance for fairer decision-making systems.

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: An analysis of U.S. mortality trends by socioeconomic category from 1982 to 2023, emphasizing the continuing effects of the COVID-19 pandemic on mortality disparities.

Description: This report provides a validated, structured dataset of demographic and socioeconomic variables to support mortality heterogeneity research across geographies and population groups.

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 study of socioeconomic inequalities in mortality builds on a previous report in which we identified a large and growing gradient in life expectancy between 1982 and 2019 across U.S. counties classified into 10 socioeconomically homogeneous categories. In this report, we seek to identify the particular causes of death contributing to the growing disadvantage in mortality between populations in the least and most affluent deciles as previously defined.

Description: This report examines the demographic, medical, and pharmaceutical profiles of HIV-positive individuals in Medicare and how their needs differ from the general Medicare population.

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.