Description: This report examines the adoption and challenges of predictive analytics in life and annuity reinsurance, including current practices, regulatory context, and advanced AI applications.

Description: Award-winning essays on addressing unwanted bias in life and annuity insurance processes.

Description: This report is a technical paper on a Predictive Analytics Framework and Reusable Workflow for Experience Analysis in actuarial studies. It covers data analysis, machine learning models, methodologies, and model interpretation techniques.

Description: The objective of this paper is to provide a practical guide with concrete case studies to help actuaries implement artificial intelligence and machine learning (AIML) to help accelerate the speed of analysis for life and annuity actuarial modeling. We do so by researching the existing literature regarding AIML and its applicability to stochastic modeling and exploring case studies.

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: The Modeling Section, Predictive Analytics and Futurism Section, Committee on Life Insurance Research, Product Development Section and Reinsurance Section releases a report that can help to educate actuaries on how best to implement predictive modeling into relevant areas of actuarial practice. This report includes a review of existing literature and current industry practices, as well as a comprehensive set of considerations for predictive modeling in insurance applications.

Description: This project obtains ensemble simulations of surface atmospheric temperature over North America.

Description: This is a collection of essays from the Society of Actuaries Research Institute, focusing on the potential impact of AI on human longevity and its consequences for modeling future survival/mortality. It includes various essays discussing AI's role in mortality modeling, life expectancy, and implications for actuarial methods.

Description: Toward a Predictive Analytics Framework files

Description: This report provides actuaries and other professionals working with risk, data and analytics or program evaluation in the health care space with considerations and frameworks related to the use of determinants of health (DOH) in data and actuarial work streams. Such frameworks can leverage new data sources to enrich health care data analysis to move beyond traditional data elements, such as age, gender, zip code or health diagnosis.