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 outlines a methodology for estimating mortality improvement factors based on data from insured lives. The report details challenges, methodology, results, comparisons with population data, limitations, and potential improvements.

Description: An overview of the objectives of outbreak modeling, and an examination of the various types of models used both to forecast an uncontrolled outbreak, and to estimate the effects of interventions intended to alter the outbreak’s trajectory

Description: This paper introduces practitioners to the selection and calibration of stochastic interest rate models. Six continuous time interest rate models and their calibration are presented. Actual code and data examples are added to help the practitioner implement them. The emphasis is on hands-on calibration with RStudio. The reader is assumed to have a working knowledge of RStudio, including writing R scripts.

Description: This report introduces quantum computing to actuaries. In addition, this research will assess and identify areas in the insurance field where quantum computing can make a difference, accompanied with suggested algorithms.

Description: This research report educates the actuarial community about the various shades of the flood risk as well as the state of the art in quantitative flood risk modeling.

Description: This report provides insights into statistical methods for imputing race and ethnicity in the context of insurance industry disparities. It discusses various imputation techniques, performance metrics, and the evolution of methods over time. The aim is to address the lack of consistent data collection on race and ethnicity in insurance datasets.

Description: The Society of Actuaries (SOA) Research Institute’s Mortality and Longevity Strategic Research Program Steering Committee issued a call for essays to explore the application of artificial intelligence (AI) to mortality and longevity. The objective was to gather a variety of perspectives and experiences on the use of AI in mortality modeling, forecasting and prediction to promote discussion and future research around this topic. The collection includes six essays that were accepted for publication from all submissions. Two essays were chosen for prizes based on their creativity, originality, and likelihood of further thought on the subject matter.

Description: The document is a report on U.S. Population Mortality Observations updated with 2022 experience by R. Jerome Holman, FSA, MAAA. It covers mortality trends, analyses by factors like sex, age group, and cause of death, and includes methodological details for the data presented.

Description: This podcast series is an exploration of the paper “Long Term Drivers of Future Mortality” written by Yair Babad and Al Klein. The podcast aims to raise awareness of the paper's valuable insights and make it a useful resource for actuaries, underwriters, insurers, demographers, academics, economists, public health officials, and others involved in estimating future mortality trends and their implications.