Description: This article series highlights the growing impact of climate change on health, property, and financial institutions, emphasizing the need for actuaries and risk analysts to evaluate and adapt their practices to manage evolving climate-related risks.

Description: The Society of Actuaries Research Institute’s Catastrophe and Climate Strategic Research Program is pleased to release the following essay addressing current and potential uses for the Actuaries Climate Index.

Description: This document discusses the process of obtaining regulatory approval for actuarial innovations in the United States. It includes information on the research project conducted by the Society of Actuaries and Milliman, insights from interviews with actuaries and regulators, as well as advice for presenting and defending innovative ideas.

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.

Description: The Society of Actuaries' Committee on Finance Research (CFR) is seeking proposals for research projects that will produce information, data, theoretical models and/or empirical tools useful to actuaries practicing in investment and other finance-related areas.

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: The Society of Actuaries’ Committee on Finance Research and Joint Risk Management Section Research Committee are pleased to make available a research report developing a framework for quantifying and analyzing various forms of contractual designs.

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).