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

Description: "Explore a general introduction to the opportunity of applying a relatively newer area in machine learning called uplift modeling, which has been successfully used in retail (Wayfair etc). The concepts are parallel to the intervention programs in health care, where we are interested in measuring the treatment effects and ultimately directing the right members to the most effective programs, driving the highest value for the programs both from a financial and health outcomes perspective. Uplift modeling can also be viewed in context of causal modeling where we are interested in assigning cause to a treatment relative to a member not receiving the treatment. Check out an introduction on the concept, seehow it relates and builds on existing work, and use a demo to showcase the potential of integrating this ML approach to current work."

Description: This session will share insights on how to effectively evaluate and price the management high-cost claimants from three views: clinical, payer, and provider. Can predictive analytics help with underwriting? What are effective clinical mitigation strategies? Can VBC arrangements be used to reduce total cost of care, and how can that be priced in?

Description: Generative AI has become a hot topic since ChatGPT became one of the most well-known Machine Learning models ever. There are many different generative models out there, and in this presentation, we explore the possibilities, benefits, reservations, and alternative use-cases of using Generative Adversarial Networks to generate health insurance claims data.

Description: The session will provide attendees with a framework of what goals to think about when building and utilizing a predictive modeling framework in New Sales and Renewal Underwriting mid-market, level funding, balance funding, and self-funding group health business.

Description: Insurance carriers today must balance a multitude of factors to remain relevant and innovate- -process improvements and efficiency (automated or traditional); -customer experience (less intrusive, more data); -distribution (aging traditional, product focus, emerging opportunities); and -mortality. While these factors are not new, true innovation in these areas require a convergence of engagement among actuaries, underwriters and data scientists to determine the specific pain points and appreciate both the benefits and consequences of various paths. Explore examples of how best to approach these topics, engage different disciplines, avoid pitfalls and ensure a holistic view. Real life examples and lessons learned will be shared during this session.

Description: Dana M. Peterson, chief economist for the Conference Board, has established herself as a visionary, and the go to expert providing insightful analysis and predictions to corporations, associations, and government organizations looking for clarity and foresight into how economic drivers might impact their businesses in the short- and long-term. With over two decades of experience in the field, she serves as the globally recognized think tank’s public face and primary spokesperson on all things related to the economy.

Description: This session will examine bias from a social science perspective. It will discuss the three types of systemic biases using the National Institute of Standards and Technology (NIST) model. The NIST model details the three types as historical bias, societal bias, and institutionalbias. The session will also provide several examples of each type to provide a framework for identifying the social structure of bias.