Description: Is Takaful the same as mutual insurance?

Description: Operationalizing LLMs

Description: ERM in General Insurance

Description: This session on Innovations in Underwriting will explore the latest advancements in underwriting technology and methodologies. It will focus on how these innovations are transforming the insurance industry, making underwriting processes more efficient, accurate, and customer-friendly. Topics will include the integration of artificial intelligence (AI), machine learning, and big data analytics into underwriting workflows. Additionally, we'll discuss emerging trends in risk assessment, automation of underwriting tasks, and the implications of these changes for underwriters and insurance professionals. Attendees will have the opportunity to learn from industry experts and participate in discussions on how these innovations are reshaping traditional underwriting practices. Learning Outcomes: - Gain an understanding of the latest technological advancements impacting underwriting, including AI, machine learning, and data analytics. - Learn how these innovations can streamline underwriting and pricing processes, improve accuracy, and reduce costs. - Explore new risk assessment methods and discover how automation is changing the underwriter's role. - Identify best practices for integrating innovative technologies into existing underwriting and actuarial pricing frameworks.

Description: According to Oliver Wyman's 2023 Asset-Liability Management (ALM) survey, long-term care (LTC), universal life, and whole life insurance products have among the longest liability duration profiles, often with material asset-liability duration mismatches. Deploying an optimal strategic asset allocation (SAA) framework for these products is particularly challenging due to their: - Long-tail profile. Liability cashflows for long-duration insurance products often extend beyond the investment horizon of currently available assets (e.g., 30-year U.S. Treasuries) - Liquidity needs. Depending on the type and age of the insurance product, achieving your desired levels of projected liquidity becomes instrumental Solution: A robust liability-driven SAA framework with an emphasis on minimizing cashflow mismatch while considering a company's risk appetite and investment guidelines aims to reduce interest rate and liquidity risks. Case studies: LTC and life-focused case studies will provide insights into hypothetical SAA frameworks, including ways companies optimize their fixed-income assets. We will also explore techniques used to extend asset duration beyond a typical fixed-income portfolio, using derivatives and alternative assets.

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: 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: 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: "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 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.