Description: Similar to how states had made adjustments to their capitation rates to reflect acuity adjustments caused by the onset of the pandemic, states will need to modify the rates to reflect the unwinding since utilization patterns and average acuity per enrolled member will change. When the continuous coverage requirements set forth by the COVID-19 Public Health Emergency (PHE) ended, Medicaid-managed care programs across the country adopted various approaches to phasing out maintenance of effort (MOE) as a result of changes to the PHE-era continuous eligibility requirements. Phasing out the MOE requirement will ultimately result in members who no longer meet eligibility requirements losing their Medicaid coverage. Further, states are facing a wide variety of circumstances and are implementing diverse approaches to the MOE phase-out. This topic will be of significant interest to all actuaries and stakeholders of the capitation rate development process for Medicaid-managed care programs. Join us as we discuss the operationalization of the PHE unwind while referencing the SOA's research project which models the effects of the unwinding on Medicaid eligibility and population costs. You will learn about the various approaches that different states have adopted to manage the unwinding process, which will be instrumental for accurately pricing managed care rates.

Description: Hear AM Best rating analysts discuss the rating process and the best capital adequacy ratio (BCAR), a quantitative foundation for AM Best’s assessment of carriers’ financial strength. The benchmarking of BCAR scores for various company types (national MCOs, BCBS plans, smaller regional plans) will be discussed. Look at how changes in investment and underwriting environment impacted the results over the past several years. Further, AM Best’s view of the quality of capital and various factors impacting the overall assessment of the balance sheet strength will be discussed.

Description: Cover a variety of topics centered around the unsupervised learning technique called 'clustering'. The presenters will take you through a wide array of topics that range from 'What is Clustering?' to 'How can I use this technique to solve problems I didn't even know existed?' In the health care industry, everyone is looking for an edge in reducing total spend-cluster analysis finds the unambiguous in an ambiguous framework of results.

Description: ALM and hedging can reap significant benefits from innovation in computation and operations research. Explore applications of static and dynamic optimization in two different ALM and hedging use cases. Insurers are increasingly moving offshore by establishing Bermuda captive reinsurers. In calculating the Bermuda Best Estimate Liability ('BEL'), reinsurers will need to segment assets to support liabilities in each treaty. A Linear Programming ('LP') problem can be formulated to tactically select assets in a way that minimizes the BEL and consequently the total asset requirement. Learn more about what US Variable Annuity Insurers face with the regulatory requirement to reflect 'future hedging strategy' in their statutory funding calculation. The traditional numerical method of finding the optimal hedging target and then allocating assets may encounter the curse of dimensionality with expanding product and economic environment complexity. A Reinforcement Learning algorithm may well fit this problem and provide insurers a solution for dynamic hedging.

Description: Both LDTI and IFRS 17 have introduced numerous new metrics with most companies having only crossed the finish line, just complying with what's needed for reporting due the complexity and large amounts of data required to simply comply. How do you leverage all the work you did to get proper business insights across the organization that tie back to these reporting metrics?

Description: The session begins with a brief introduction to Gen AI, including “what it is” and how to optimize outputs. Then, we will to provide some insight into what we are seeing within the Actuarial space – this would include the extent to which actuaries are using Gen AI on a day-to-day basis, how they are going about using it, and some predictions as to where this will go.

Description: This session will explore governance considerations for insurance carriers leveraging machine learning models. During the session, panelists will share insights on the evolving predictive model and AI regulatory landscape, as well as techniques for developing or enhancing AI governance frameworks that comply with emerging regulatory guidance.

Description: One of the most effective ways to convey quantitative results is via data visualization. However, many times actuaries have been ineffective in doing this. In this session, you will see a demonstration of certain dataviz choices that make communicating results more effective in terms of graph type choice, graph element styles, colors and more. All examples will be in Excel-and doesn't require Visual Basic for Applications (VBA)! Nothing too fancy! I want to distribute working files to attendees before the session so they can follow along with how to build the graphs, make changes, etc. Graph choices will include line graph, tile grid map and jitter graph.

Description: Modeling Approaches and Challenges focuses on approaches to real world simulation and the challenges and considerations in real world simulation. Topics include: A frequency domain approach to build realistic multi-horizon scenarios. (Ortec approach) Cascade models structure linking models for major asset classes and economic variables. (Moody’s approach) Overview of models, calibrations & approaches within the context of different use cases. Deterministic & stochastic approaches. Importance of model re-calibration flexibility. We will also discuss specific insights into considerations and challenges in real world simulation, which include topics like: Setting capital market assumptions and/or calibration targets. Assumptions about correlation and causality. Calibrating the model to capital markets assumptions. Validating the model against capital market assumptions. Role of history, market data and stylized facts. Importance of back testing. Calibrating the model to multiple investment horizons. Inclusion of alterative asset classes such as private equity, infrastructure, and direct real estate. Associated issues of limited data, illiquidity and greater uncertainty about calibration targets.

Description: Emerging Applications of ESG Methods offers ground-up insights on cutting edge applications of economic scenario generation. The course will focus on the incorporation of climate change risk in scenario modeling and investment applications of ESGs. The following topics will be covered: Approaches to climate risk modeling. Climate risk is very different than classical financial economic risk. Radical uncertainty is amenable to scenario analysis and lack of data. Building special deterministic scenarios that go beyond NGFS requirements as well as bespoke scenarios. Holistic Approach to Climate Risk Modeling. Overview of different Climate Risk Modeling Applications. Use of ESG scenarios for Strategic Asset Allocation (SAA). Liquidity risk management.