Description: Genetic algorithms [GAs] and neural networks [NNs] are currently being used in actuarial and financial modeling. Nonetheless, while there is a general awareness of the nature of these techniques, there is often only vague familiarity with the details of how they are implemented. This paper is intended to help alleviate this situation. Its purpose is to present an overview of GAs and NNs, which includes an explanation of what they are, how they work, and an example of how they are implemented.

Description: This paper reviews the applications of operations research methods in the insurance industry. From Transactions of Society of Actuaries 1995, Vol. 47.

Description: This is a Request for Proposals document issued by the SOA Research Institute, focusing on developing a framework for actuaries to bridge the gap between climate scenario outputs and actuarial assumptions. It outlines the background, research objectives, proposal requirements, selection process, submission guidelines, and appendix with cost estimates.

Description: Tree models have been found to provide a good fit to group long term disability recovery and mortality rates. This research paper provides an overview of tree models, and details how they have been used for developing these rates.

Description: This research report examines readers to Insurance-linked securities (ILSs) emphasizing catastrophe bonds (CAT) and industry loss warranties (ILWs).

Description: 2020 Generally Recognized Expense Table (GRET) recommendations.

Description: The Product Development Section, the Financial Reporting Section, the Modeling Section and the Committee on Life Insurance Research are pleased to present new research on modeling and forecasting cause-of-death mortality. Authored by a Milliman team led by Alexandre Boumezoued, the report develops a framework for forecasting cause specific death rates. Included also is a Cause of Deaths Forecasting Tool and a user guide for the tool.

Description: The aim of this research is to survey emerging data analytics techniques and discuss their evolution and growing use in the actuarial profession. Data analytics’ applications in life and non-life insurance will also be provided.

Description: The Casualty Actuarial Society, Canadian Institute of Actuaries, and the Society of Actuaries' Joint Risk Management Section and the Joint Risk Management Research Committee are pleased to make available a new report on the application of ERM. Authored by Bonnie-Jeanne MacDonald, Sim Segal, Michael Wolfson and Heidi Walsh, the report provides a novel demonstration on how ERM can be applied to serve the Canadian public by informing decision makers on the risks facing the current and future delivery of long-term care.

Description: The multi-risk scenario generator is an output of the Smaller Insurance Company Section’s sponsored Principle- Based Reserves Simplified Methods study performed by Mark Birdsall, Steve Strommen, and Brian Hartman. The scenario generator can be used for all material assumptions in an actuary’s cash flow projection software.