Description: In this webcast, two points of view are presented - Seven Life Defining Decisions, which presents an individual perspective on lifetime financial choices, and Life-Cycle Fund Design, which discusses the design of a comprehensive life-cycle fund model that includes human capital risk, longevity risk, bequest motive, parameter uncertainty, and different types of annuities and provides a model for financial risk.

Description: Artificial intelligence is no longer an emerging technology — it is rapidly becoming the core engine of risk selection, pricing, underwriting, and customer interaction across insurance and financial services. But as models evolve into autonomous agentic systems and decision pipelines become more complex, traditional guardrails are being stress-tested like never before.

Description: Fairness in life insurance isn’t a checkbox—it’s a set of choices, trade-offs, and consequences. In this webcast, the report’s author will walk through a practical framework for defining and measuring fairness in life insurance workflows, showing why “fair” can mean very different things depending on whether you’re focusing on individuals or groups—and why you often can’t optimize both at once. You’ll get a clear tour of the major fairness criteria used in today’s literature—what they measure, where they fit in insurance, and what can break when you adopt them . Expect straight talk, concrete insurance-oriented examples, and guidance on selecting metrics that align with business objectives, regulatory expectations, and stakeholder priorities—without pretending there’s a one-size-fits-all answer.

Description: Cardiovascular disease (CVD) remains the leading cause of death among older adults in the United States. While genetics play a foundational role in establishing risk, disease progression is heavily shaped by lifestyle behaviors, environmental exposures, and social determinants of health. This Webcast will summarize key insights from an expert panel discussion on the evolving landscape of cardiovascular mortality at older ages.

Description: This webcast will update listeners on the financial status of the U.S. Social Security program, describe half a dozen widespread myths, and discuss the reality of "waste, fraud and abuse" in the program.

Description: "The script is for a Medicare session by the Society of Actuaries, led by Danica Turner, which introduces how revenue works on Part D. It covers the various cash flows and subsidies that Part D plans receive, including direct subsidies, federal reinsurance, and low-income subsidies. The session also explains the different phases of coverage and the upcoming changes due to the Inflation Reduction Act in 2025. The goal is to provide a high-level understanding of the revenue and payment calculations for Part D plans.

Description: What is bias? How do you recognize it? What to do if you see it? This webcast will help respond to these questions and provide initial guidance on how to deal with these thorny issues. Please join us with your questions and we will have a nice conversation.

Description: A comprehensive webcast designed to bring together industry practitioners to discuss the current state of Model Risk Management (MRM) frameworks. This event will delve into the advancements in MRM, the challenges faced by professionals in the field, and emerging trends such as machine learning model validation that are set to shape the future of MRM. Engage with experts, share knowledge, and explore innovative solutions to enhance the effectiveness of your MRM framework.

Description: Presenters will discuss difficulties within the new NAIC ESG, such as how the model deals with interest rate flooring and its treatment of the linkage between equity and treasury bond returns. They will also discuss the documentation and governance process surrounding the new NAIC ESG.

Description: Learn how insurers provide new opportunities for efficiency and value creation from product design and underwriting through customer engagement and claims. Glimpse some industry use cases for Gen AI and its outcomes as observed by the first movers.