Description: The life insurance industry has a lot going on. Come discover some key highlights of the life insurance market mixing quick hits with some in-depth conversations about the headlines and hard lines happening in the life insurance sector. Topics include underwriting, regulation, product changes and distribution to name a few. If you enjoy the PTI show for sports, you will enjoy hearing about the life insurance industry in this format and hosts will run down the headlines of the insurance industry in PTI fashion.

Description: Model runtime is a common challenge for actuaries in the life and annuity space. In particular, applications such as pricing and forecasting may require the use of nested-stochastic calculations, which may require extensive computing resources or use of rough approximations. There are also other areas where runtime may be a challenge, such as projecting certain reserves or layering solving algorithms within actuarial calculations. Recently, runtime challenges have been exacerbated by the development of increasingly complex insurance products and changes in reporting frameworks, such as IFRS 17, LDTI, PBR, and Solvency II. Many approaches have been explored by actuaries in the past to address model runtime challenges. To further this research, the SOA has recently published the paper Predictive Analytics and Machine Learning - Practical Applications for Actuarial Modeling. The authors of the paper will share their insights on innovative techniques using the implementation of artificial intelligence and machine learning (AIML). Come examine an introduction into AIML, review how AIML can be used to circumvent nested stochastic and other runtime challenges, explore case studies, review how costs and benefits can be measured and discuss model risk management considerations. Key learning objectives include: - Understanding the fundamental concepts of AIM - Understanding applications of AIML for actuarial modeling - Learning about the costs and benefits - Learning how AIML can be applied in practice to improve model runtime

Description: The audience will learn about practical applications for actuarial and operational problems by using data science, how to collaborate effectively between actuarial, data science, data engineering, data management, legal and others and specific questions they need to ask the data science team to make effective data science solutions.

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. By attending this session, you will: Gain an understanding of AM Best’s building block approach to ratings and how the BCAR results fit into the process. Learn the differences between RBC and BCAR models. Learn how various factors—e.g. liquidity, financial flexibility, financial leverage, the org structure—impact the final AM Best assessment of health companies' capital."

Description: With the mandated health plan transparency files, health plans and providers are now able to substantially enhance their provider contracting efforts. Although the files are large and cumbersome they are market disruptors and provide new insights for provider contracting efforts. Explore a demonstration on the type of information now available and how it can be used to enhance this from both a health plan and health care provider perspective.

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: 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: How might retirement income strategies be designed and their suitability assessed when retirees may differ substantially in their objectives, preferences and personal circumstances? Gain a wide-ranging overview of the key elements involved in formulating retirement strategies, drawing on the report, Primer on Retirement Income Strategy Design and Evaluation, which was recently released by the Society of Actuaries (SOA) Research Institute's Aging and Retirement Strategic Research Program. Hear about three types of income objectives-income floor, income target and income optimization-and how they imply different retirement strategies along with a different set of metrics to evaluate outcomes. We will also touch on key member attributes to account for: The nature of income risk, approaches to investing and drawing down on available assets to generate income, and how stochastic modeling can support the analysis. You will find something of interest in this session, regardless of prior familiarity with strategies for retirement.

Description: The frequent use and complexity of today's actuarial projection models has increased the importance of having efficient models. Model optimization can reduce both cloud costs and overall end-to-end clock times, thereby allowing companies to do more with less such as reducing close times, increasing controls, enhancing analysis, doing more complicated calculations, and/or improving employee workloads during the close. From design and data to execution and audit, come explore techniques that can be applied throughout the actuarial modeling process to optimize actuarial models for improved run-time, accuracy, and reliability. There will be a focus on techniques that don't rely on model compression. Topics covered include model design pitfalls, data handling, improving convergence on asset-liability projections, strategies for interacting with the cloud, and other tips for optimizing actuarial models.