Description: While the major market crash subsequent to the widespread contagion of the COVID-19 virus was readily predictable, the rapid recovery and ongoing growth subsequent to it was not. Market dynamics around the recovery resist characterization by most traditional analytical approaches. In examining the circumstances around the emergence of a large retail class of investors, one sees that ingrained human tendencies, particularly optimism bias, have fueled much investor behavior responsible for the recovery. Understanding this makes it possible to predict potential future crashes and develop behavioral interventions for subsequent market recoveries.

Description: This article summarizes key points from the recently published research paper “Deep Learning for Liability-Driven Investment,” which applies reinforcement learning and deep learning techniques to liability-driven investment (LDI).

Description: Feature article discussing key accounting concepts in finance.

Description: In this session, presenters will share the impacts of transition to IFRS 17 on equity and various KPIs across insurance companies (Life & P&C), as well as share some observations of what the IFRS 17 landscape looks like across different global regions. The session will conclude with lessons learned and expectations for emerging practices under IFRS 17 globally.

Description: Call for essays on how actuaries can apply their financial skills to support non-profit financial management and promote societal purpose.

Description: Insurers have long relied on scenario analysis to understand the long-term impacts of potential business decisions, but the advent of rapidly changing market environments and a growing desire to optimize capital has spurred business leaders to leverage new tools in order to explore potential options. Companies are beginning to explore new analytical solutions that trade-off accuracy for speed for a more robust approach to impact quantification. In particular, they are looking at the use of additional what-if scenario models, built from the top down, to support decision-making processes. Actuaries can help take charge in the development of these top-down analyses by leveraging data and actuarial techniques to supplement their existing models. In this way, business leaders can simultaneously rely on the actuarial rigor of typical standalone cash flow projection models, while also receiving support for real-time business decision-making. The potential of what-if scenario modeling can help actuaries unlock a powerful new approach to scenario analysis to enable more rapid decision-making. Learning objectives: In this session we will discuss the fundamental concepts of what-if scenario modeling in an actuarial context, including: - Core principles and components of what-if scenario modeling - Common challenges and considerations around the implementation of what-if scenario modeling - Potential solutions to challenges and their implications

Description: This session will discuss basic and advanced hedge modeling concepts. It will explain common hedge strategies used to support guarantees and options embedded within life and annuity products and the materiality of these products within the US. Attendees will learn how Machine Learning acts to reduce the computer processing needed to simulate the dynamic hedging of product liabilities projected in the future across many stochastic scenarios. Actuaries working in consulting, software development, and a large life insurance company will provide a wide range of hedging viewpoints ranging from a broad industry perspective to a hedging practitioner. Attendees will obtain a comprehensive understanding of a novel ML approach to modeling dynamic hedges and the hedge optimization opportunity it presents.

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: "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: Join a discussion on the evolution of asset and liability projection processes in the life insurance industry. Familiarize yourself with the broad set of inputs, stakeholders, and financial planning and analysis use cases. Notable areas of focus will include, but are not limited to, historical background, modeling needs, interactions between stakeholders, industry pain points, and a composite of an ideal future state informed by perspectives gleaned from leading companies within the industry.