Description: Over the last 10 years, Artificial Intelligence (AI) healthcare foundation models have made tremendous strides when it comes to delivering highly accurate predictive results when compared to traditional models. This is especially true for models developed and trained on the ‘language’ of healthcare. When trained on healthcare data sequences (claims, EHR, CPT, ICD, pharmacy, lab, etc.), these models deliver far more accurate results as to WHAT beneficiary-level health events will occur and even WHEN they will occur.

Description: The speakers will work through hands-on Excel examples of bootstrapping interest rate curves—including forward, spot, and par rates. The presenters will also cover models such as Hull-White and the Forward Market Model with an emphasis on derivative valuation and exposure calculations.

Description: Indexed universal life (IUL) continues to be the most popular universal life (UL) product with sales reaching $1B in Q4 2023, according to LIMRA. There is little long-term experience for IUL and many companies value and model IUL just like UL, but there are material potential differences that need to be considered for valuation and projection purposes.

Description: This three-part series provides an overview of the rapidly evolving and dynamic gene and cellular therapy landscape, from the clinical, historical, and risk transfer perspectives. It covers the actuarial considerations in pricing cell and gene insurance and reinsurance, the value assessment of the therapies, manufacturer pricing, and reinsurance cost.

Description: Review a recently completed research project for a multi-stakeholder data consortium on social determinants of health (SDOH). In this project, claims, external SDOH data, geospatial analysis, and machine learning models were used to examine several questions: How to identify SDOH vulnerabilities? How sensitive are the findings with respect to provider coding pattern variations? How much variability in cost can be explained by SDOH vs. morbidity? What are the key risk drivers revealed by machine learning models? The session will review the methodology and main findings from this project.

Description: Worried about the latest wildfires? Can't keep up with the latest geopolitical landscape? Wondering how close AI is to taking over? Join us as we discuss the results of the 18th edition of the Emerging Risk Survey. This is an annual survey which is jointly sponsored by the Casualty Actuarial Society and the Society of Actuaries Research Institute.

Description: Are you ready to supercharge your career? Join us for an exciting webcast where industry experts will share how to leverage mentoring and networking for career success. Discover how these powerful tools can transform your professional journey, provide invaluable insights, and open doors to new opportunities. In this dynamic session, our speakers will share their personal stories and practical tips on building meaningful mentoring relationships. You’ll learn proven networking strategies to connect with influential professionals and accelerate your career growth. Don’t miss this chance to gain insider knowledge from industry leaders and receive actionable advice. Whether you’re just starting out or aiming to advance your career, this webcast will equip you with the tools and inspiration you need to succeed.

Description: In this webcast, we will speak with actuarial leaders who developed their personal brand over several years to better understand just how powerful having a personal brand can be in actuarial work.

Description: This session shows the fascinating world of Generative AI, focusing on the principles of Retrieval Augmented Generation and Agentic Workflows. Attendees will gain a comprehensive understanding of how these advanced AI techniques can revolutionize processes by integrating external data retrieval with generative models. Practical examples and expert insights will illustrate the transformative potential of this technology in various industry applications.

Description: This session will discuss essential theories and practical applications of deep learning for actuaries. Participants will gain insights on leveraging these cutting-edge techniques to enhance actuarial models and drive predictive accuracy.