The Society of Actuaries develops and funds a variety of research on enterprise risk management (ERM). Learn about emerging risks, effective modeling techniques and much more on ERM. See our research projects and research on newly developing topics.
Risk Management Research
This Society of Actuaries Research Brief has been constructed to highlight some of the key features of the COVID-19 epidemic and contemplate the risks for the actuarial profession to consider in their work.
Effective ERM Stakeholder Engagement
The Joint Risk Management Research Committee announces the release of a new report on enterprise risk management (ERM) stakeholder engagement. Authored by Kailan Shang, this report examines current practices and identifies challenges to achieving ERM stakeholder buy-in. It also offers strategies to help overcome these challenges and improve ERM stakeholder engagement.
COVID-19 from the U.S. Insurance Industry Regulation Perspective
This special episode of the SOA’s Research Insights Podcast highlights how the COVID-19 pandemic is impacting actuaries and their interaction with U.S. insurance regulators. We were pleased to be joined by Mike Consedine, Chief Executive Officer of the National Association of Insurance Commissioners (NAIC).
Policyholder Behavior in the Tail Joint Risk Management Section Working Group Variable Annuity Guaranteed Benefits 2019 Survey Results
As part of its work, the PBITT working group issued its annual survey to gather the range of assumptions actuaries use in pricing, reserving, and risk management of minimum guarantees on Variable Annuity products, such as death benefits, income benefits, withdrawal benefits and maturity benefits.
2019 Universal Life with Secondary Guarantees Survey: Survey of Assumptions for Policyholder Behavior in the Tail
The PBITT Working Group presents a summary of the 2019 UL with Secondary Guarantees Survey.
Machine-Learning Methods for Insurance Applications-A Survey
The Society of Actuaries is pleased to make available a research report that provides a literature survey of methodologies applying machine learning to insurance claim modeling.