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: 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 upcoming VM-22 standard promises significant changes for the non-VA life insurance industry, impacting regulatory compliance, risk management, and financial reporting. This presentation equips insurance companies to navigate this crucial transition. We'll delve into key considerations from capital, modeling, and hedging perspectives, providing actionable insights for optimizing your VM-22 implementation strategy.

Description: At the end of this session attendees will understand how their company's existing cash flow models can be leveraged to meet the new requirements for principle-based reserves under VM-22.

Description: Driver-based forecasting is a powerful tool to predict and estimate future outcomes. In recent years, driver-based forecasting has gained significant attention as a technique for actuaries to forecast the financial performance of insurance companies. Often there can be frustration around the ability to use forecasts to manage the business. However the objective of a driver-based forecast is to break down historic and projected movement based on the key drivers which impact the results. The key is to understand what the key drivers are on forecasts and what is the relative level of impact and influence we have on the drivers. Listen in on a discussion on the core principles of driver-based forecasting, including how to identify key drivers, collect accurate data, and leverage the latest technology to generate forecasts that traditional models can't match. Explore with us the various driver-based models and how actuaries can leverage them to enhance their decision-making capabilities. Then join the conversation about the challenges actuaries face when implementing this technique and how to mitigate these problems.

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: Attend this webcast to learn more on how to navigate managing ESG principles in the new normal of a post-COVID world. Enhance your ESG insights in a post-pandemic landscape.

Description: Almost half of recent FDA approvals have been for orphan drugs. This trend is expected to continue in 2023. Orphan drugs are priced more than 30 times higher than non-orphan drugs, therefore their cost burden in aggregate has the potential to overwhelm the budgets of payers, especially that of smaller health plans. Hear how the cost impact analysis for smaller health plans require different considerations than for a larger health plan when modeling the impact of rare diseases.

Description: Reunite with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, IFRS 17, product strategy, cross-border communication and discussion, and more. Advance your career through learning and networking opportunities, and share your experiences in the finance and insurance industries, as well as other fields related to actuarial science.

Description: The panel will discuss several product challenges including modeling hybrid/combo long-term care products, modeling benefit options that are difficult to model using deterministic methods, modeling current situs of care versus original situs of care, monitoring assumptions, streamlining experience studies within the Long-duration Targeted Improvements (LDTI) framework, and model decision making with limited credible data. The panel will then move into solutions observed to address some of the aforementioned challenges and the future of long-term care modelling