Description: The recent financial crisis created incentives to review investment practices and see what was done well and what could be improved for the future. Looking inward at insurer investment practices, background trend information was generated and a survey developed for insurers to share their thoughts. The research continued with conversations in private and public forums, where initial conclusions were expanded.

Description: This report updates the Canadian Mortality Data through 2021 in the Human Mortality Database and Canadian Human Mortality Database, including methodology, data sources, and internal consistency checks.

Description: This paper investigates the implications of using the Basel II motivated Advanced Measurement Approaches as a method to assess operational risk capital charges for banks and insurance companies with regard to U.S. regulations. The AMA developed in the paper uses actuarial loss models complemented by the extreme value theory to determine the empirical probability distribution function of the aggregated capital charges in the context of various classes of copulas. From Actuarial Research Clearing House, 2006.

Description: This research report introduces the concept of a preference function, which is a generalization of the utility function.

Description: View The Impact of Disaster Events on Investments – Contagion Channels Perspective.

Description: The SOA is pleased to make available a report updating the 2012 risk assessment performed by Porteous et al. The report also provided an economic capital analysis for a stylized US plan with the same member profile and the USS provisions modified to reflect a typical US DB plan.

Description: This report introduces actuaries and risk managers in the insurance and pension industries to current literature discussing growth rates in the past and future expectations.

Description: Research material that developed a Liability-Driven Investment (LDI) benchmark framework.

Description: The Society of Actuaries’ Committee on Finance Research is pleased to make available a research report that develops a framework for applying deep learning and reinforcement learning techniques to optimal dynamic strategic asset allocation for Liability Driven Investment (LDI).

Description: This report covers credit risk loss experience during the period 2003 through 2015 on non-Rule 144A private placement securities (and, with limited exceptions, some specific types of Rule 144A bonds) held by participating companies of the life insurance industry.