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: 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: 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."

Description: This session will cover the regulatory testing requirements issued by Colorado in its SB21-169 regulation, New York Insurance Circular Letter No. 7 issued in 2024, as well as other US States. It will also explore the actual implementation of these requirements on a company using Large Language Model on external data for life underwriting.

Description: Modern Actuarial work, being quite data intensive, provides many opportunities for actuaries to use the statistical skills that are part of their basic training. Furthermore, modern computing allows us to analyze vast quantities of data intensively, and each package will provide statistical "answers" to any questions the actuary might ask of it. However, in this particular field, it is often worth taking a step back, and ensuring that we recall and consider the warnings that come with each of the statistical procedures we might attempt to use. This will allow us to ensure that we guard ourselves against drawing inappropriate conclusions, which could come back to haunt us later.

Description: With LDTI in the rear-view mirror for 2023 adopters, and 2025 adopters still working to meet the requirements before reporting on an LDTI basis for the first time at year-end 2025, there remain many opportunities and challenges for all companies subject to LDTI. These may include further enhancements to modeling, improvements in end-to-end processes (such as automation and reducing the close financial timeline), development of robust management reporting and analysis frameworks, and enhancements to financial planning and analysis under LDTI.