Description: This session guides actuaries through the key steps of building a principles-based valuation model for a life product, starting with a brief overview of key requirements in LDTI and VM-20.

Description: Obesity rates in the United States have climbed to historic highs, with nearly 42% of adults now classified as obese—a trend with significant implications for the health care system. Among Medicare-aged individuals, obesity is strongly associated with chronic conditions such as diabetes, cardiovascular disease and musculoskeletal disorders, all of which increase health care utilization and spending. As costs continue to rise, understanding the financial impact of obesity management is increasingly important for policymakers, payers and providers. This analysis uses detailed traditional Medicare claims and eligibility data to examine how obesity levels relate to health care expenditures and how costs change as members move between different diagnosed obesity categories over time

Description: On October 4–5, 2025, actuarial educators and researchers gathered in New Orleans for the Actuarial Mathematics and Actuarial Education Special Session at the American Mathematical Society (AMS) Fall Southeastern Sectional Meeting. The event brought together seventeen speakers from universities, professional societies, and industry to discuss the future of actuarial education, practical applications of actuarial methods, and advances in actuarial modeling. The session featured rich discussions on artificial intelligence in actuarial education, experiential learning through case studies, competency-based assessments, and industry-integrated research courses. Applications-focused talks addressed mortality shocks from COVID-19, disaster aid modeling, queuing systems, health and longevity metrics, healthcare reserving, flood risk in real estate, and value-based insurance contracts. The final segment highlighted advanced actuarial models, including optimal insurance with incentives, variable annuity hedging, extreme risk inference, AutoML for insurance, and privacy-preserving data collaboration. Overall, the session emphasized collaboration, innovation, and adaptability as essential for advancing actuarial science in an era of rapid technological and societal change.

Description: This article explores the evolving role of assumption management in the life insurance industry. The article highlights how behavioral, economic, and demographic assumptions are critical to pricing, forecasting, and explaining financial results, yet many insurers still struggle with fragmented practices and outdated processes. Drawing on survey insights from 15 U.S. insurers, the authors illustrate persistent challenges in governance, data integration, and automation. They argue for a more holistic, technology-enabled operating model centered on centralized assumption repositories. Such repositories provide a single source of truth, enable automated ingestion into models, support sensitivity testing, and enhance governance and transparency across actuarial, finance, and risk functions. The article offers guiding principles and design considerations for building scalable repositories that improve efficiency, consistency, and decision-making. Ultimately, it positions assumption management modernization not as a technical upgrade but as a strategic imperative to unlock clarity, agility, and competitive advantage in a complex market.

Description: The article is a chairperson’s update from Arthur da Silva on the Society of Actuaries (SOA) Emerging Topics Community, written to recap the past year’s accomplishments and outline potential priorities for the year ahead. Its intent is both informational while inviting community member participation and ideas for the year ahead. It also provides insight into the new AI subgroup and how it operates to help community members and other community leaders understand what it delivers and how to get involved.

Description: A news release about Nanyang Technological University being added to the SOA UCAP listing

Description: "This session will provide a comprehensive overview of key aspects related to the GAAP/VM-21 valuation for RILA. We will discuss how VM-21 can reward companies for making conservative decisions and examine the key factors that drive different levels of VM-21 reserves and capital. We will also cover how ALM management for RILA differs from other annuities. Attendees will gain insights into practical considerations, challenges, and solutions in implementing RILA valuation."

Description: The Individual Life Experience Committee continues to unlock valuable insights from the VM51 data as the National Association of Insurance Commissioners (NAIC) releases it. In this session, attendees will get a preview of individual life mortality patterns during COVID-19 for more than 100 companies in the NAIC data from 2020 to 2021, the first years of the pandemic. Attendees will also see early findings from the Committee's latest initiatives. These include integrating predictive analytics into its reporting products, assessing the impact of simplified and accelerated underwriting, exploring joint life mortality, evaluating company differences, and continuing its research into old-age patterns. Attendees will leave the session armed with additional knowledge for assessing best-estimate mortality for valuation.

Description: "This session will explore the critical challenges and solutions surrounding algorithmic fairness in the life insurance industry. The presenters will delve into the fundamental mechanisms of model bias, examining how predictive algorithms can yield outcomes that systematically discriminate against certain groups through flawed machine learning processes, erroneous assumptions, or biased data. Participants will gain insights into the various manifestations of bias in insurance models and understand their profound implications for both consumers and insurers. Real-world case studies and examples from the insurance industry will illustrate these concepts, while a discussion of recent regulatory developments will provide context for compliance requirements. This session is essential for actuaries, data scientists, and insurance professionals committed to developing and maintaining ethical, unbiased predictive models."

Description: "Dr. Hise Gibson, Senior Lecturer of Business Administration, Harvard Business School A retired Colonel with 25 years of distinguished service in the United States Army and a thriving academic career, Dr. Hise Gibson is a sought-after expert in strategy development, crisis management, agile implementation, and inclusive leadership."