Description: EHRs are a source of digital health data that present both an opportunity and a challenge for insurers. These rapidly maturing data sources contain valuable insights and can create a faster, better applicant experience, but the costs can quickly add up. Listen to panelists discuss various use cases for EHRs, their protective value in relation to traditional underwriting approaches, and other considerations for expanding EHR use. We will take a look at how using EHRs could promote a smart ordering approach allowing us to be quicker and more cost effective, all while understanding the impact to mortality.

Description: Our panel will discuss techniques for efficiently modeling assets and liabilities while minimizing the computational expense of full-blown nested Monte Carlo simulation. These techniques include: • Neural networks • Data clustering and selection of representative contracts • Scenario reduction • Proxy functions for estimating the value of complex assets and exotic derivatives embedded in liabilities. Attendees will learn about the theory behind these techniques and implementation practicalities, and we will present case studies illustrating their benefits.

Description: Session 7A: Integrated Analytics for GLP-1 Therapy Management: Optimizing Clinical and Financial Value

Description: Session 9C: Adventures in AI - Group Insurance Perspectives

Description: The life insurance industry is facing a rapidly changing landscape, with several emerging risks demanding the attention of actuaries and industry professionals. While actuaries commonly examine historical experience to guide our estimates of future outcomes, we are often faced with evidence that some of the forces that dictated past performance no longer persist and in some instances may even turn into contrary forces. This session aims to explore the key challenges and opportunities presented by risks with limited historical context, and discuss strategies to effectively manage them. We will delve into critical emerging risk areas, such as interest rate and asset risk, the rise of AI, climate change, predictive analytics in underwriting, and more. The session will feature speakers who are experts in managing risk, as well as results from interviews with top corporate risk professionals, such as CROs and ERM leads from major insurance and reinsurance companies. Attendees will gain valuable insights into emerging risks and practical strategies to navigate the evolving life insurance landscape.

Description: Have you ever struggled to make business decisions because your internal mortality studies lack credibility? Have you ever launched a new product or initiative and wanted to understand mortality risk before claims experience emerged? This session will discuss how predictive models can help actuaries enhance their traditional mortality studies with leading mortality leading indicators to be more nimble to market demands.

Description: Session 1G: Rethinking Catastrophic Claims - Strategies for Sustainable Stop-Loss Pricing

Description: There has been a shift in finance and actuarial modernization in the insurance industry over the past 2 to 3 years. Discuss the latest trends in the marketplace and the key changes we see actuaries and actuarial employers needing to make in the future of work. Learn how actuarial work is evolving and about the changing manner in which work is performed. Brainstorm specific ways actuaries can thrive in the future, including performing more strategic work.

Description: Highlight the importance of assigning granular policyholder behavior assumptions to cohorts of a block that behave differently for universal life products. The case study assumption testing will focus on potential cash flow impacts of surrender, lapse and premium persistency behavior— individually and combined. The case study will be based on testing data related to typical demographics for a ULSG product and not on any specific company data.

Description: Hear about some applications using quantile regression-derived individual and group claim distributions and how they may be used in various traditional health care modeling situations. The session will not focus on the technical use of quantile regression to obtain estimates of claim distributions, but more so is intended to focus on the uses of the distributions in actuarial modeling and the additive framework in assessing claims distributions. Presenters will show how actuaries can better assess risks by focusing on the individual- and group-specific claims distributions as opposed to traditional point-estimate-centric models.