Description: IUL continues to be the strongest selling UL product. Companies have great profit/pricing expectations, but are those results being achieved? Learn about potential areas of underperformance for IUL including behavior related issues, hedging inefficiency, and mortality issues. The session will also discuss ways to monitor these risks and discuss different means to address potential issues of underperformance in hedging, pricing and in force earnings.

Description: In this session, we will provide examples and highlight real-world analytics that have been done to compare providers of tertiary and quaternary (T/Q) services (i.e., complex and potentially rare conditions). We also will address the need for analytics like this, who the potential audiences are, the data necessary to complete an analysis, and we will walk through actual case studies.

Description: Insurers have long relied on scenario analysis to understand the long-term impacts of potential business decisions, but the advent of rapidly changing market environments and a growing desire to optimize capital has spurred business leaders to leverage new tools in order to explore potential options.

Description: COVID19 highlights the need for greater complexity expertise in risk management. Crisis like the current COVID19 pandemic and 2008 Financial meltdown and others help us to turn into focus inwards for introspection on how we can better manage our resources and provide a deeper understanding of what our objectives should be and how we can achieve them through applying complexity science.

Description: Unique Data Analysis Techniques to help plans find that 1% edge in opportunity and value. The discussion will vary from a conversation on members who are at high catastrophic risk to provider networks and referral patterns. The goal of the session will be to help show ways plans can create savings through outside-the-box techniques.

Description: In this session, actuaries and data scientists will describe how the Cleveland Clinic has utilized large language models to support caregivers with difficult end of life conversations with patients and their loved ones. While artificial intelligence is often prefaced with words of caution, it can also be harnessed for good.

Description: This will be the most fun you'll ever have learning about applying health status based risk adjustment methodologies in the real world! Quantifying relative differences in the use of finite healthcare resources – due to differences in health status – isn't just fun, it's the very heart and soul of ASOP 45! Get ready for a rollercoaster of statistics, probability, and a few puns that might just make you laugh harder than a data outlier!

Description: This interactive session will compare industry predictions versus what happened with the unwinding of continuous coverage requirements in Medicaid that were first put in place due to the COVID-19 public health emergency. The audience will be able to participate in a guessing game as the panelists review how enrollment could be stabilizing.

Description: Model Risk Management at insurers has been an established practice for well over ten years now. Until recently, a primary focus of model governance was on actuarial models. The Gen AI evolution we’ve experienced in the last two years, has shone a spotlight on “all things AI”. Along with the increased capabilities AI brings, there is increased concern for the proper use of these models, protection of IP, safeguarding of PII, and overall security. This session will bring together a diverse panel to discuss how we can adapt our established practices for these new models to minimize the risks that come with Gen AI and help our organizations optimize the benefits of AI.