Description: The SOA Research Institute along with the Corporate Finance & Enterprise Risk Management Curriculum Committee, Financial Reporting Section, and Individual Life & Annuity Curriculum Committee are pleased to make available a research report that aids students and practitioners with their understanding of the rating agencies as they affect the insurance industry.

Description: Learn more about improving the modelling of individual decisions.

Description: This study explores the use of geospatial imagery and high-resolution image technology in the property and casualty (P&C) insurance industry, focusing on improving risk determination through accurate building location data. It introduces new methods like structure footprints and high-resolution elevation information to enhance underwriting, rating, and claims settlement. The study includes two case studies: one on flood risk in Hillsborough County, Florida, and another on wildfire risk in three California communities, demonstrating the significant impact of precise location and elevation data on risk assessment and insurance premiums.

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 predictive Modeling and Analytics Call for Essays is a collection of articles giving insights into how actuaries use predictive analytics in their work.

Description: Results of a survey to examine the various changes life insurance companies have recently made, or are thinking of making, to improve the new business process.

Description: Summary report of the 2005 Individual Life and Annuity Expense Study. Document contains a description of data used in the study, description of unit cost formulas, list of companies contributing to the study, tables and graphs, etc.

Description: At the request of the Society of Actuaries’ Risk Management Task Force, an analysis was performed on fixed annuity data consisting of sources from Korea and a single U.S. company. The purpose of the study was to explore lapse experience in the tails and see if this required a special model with special parameters. Parameters suitable for the Logit Surrender Rate Model were developed covering not only tail experience but also under “normal” conditions. Parameters were also developed and are linked to variables such as interest spread, duration, unemployment rates, economy growth rates and seasonal effects. The methods used may be applied to any company’s experience. For the data tested, the Logit Model closely fit the experience of the data even under extreme financial conditions.

Description: Bellagos Care Level Transition Matrix. Excel spreadsheet for 2018 Student Case Study Challenge.

Description: This web page contains the 2011-2014 Group Annuity Experience Report and Pivot Tables.