Description: This paper studies the statistical theory underlying minimum surplus required to protect a group insurer from the insurance, or C2, risk. Followed by 2 submitted discussion papers

Description: Credibility is a mechanism for estimating a quantity of interest by combining subject experience and relevant experience to improve the estimate.

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 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 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: 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: This project enhances the current understanding of cyber risks in the smart home ecosystem from the insurance industry's perspective. In particular, the quantitative framework and pricing strategies developed in this project can be immediately adopted/adapted by actuaries to price the cyber risks for smart homes, a fast-growing insurance market.

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 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: 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