Description: We're introducing a new “cutting edge” wealth accumulation predictive framework, the predictive equity analytics (PEA) for life products (annuity, insurance, group employer benefits, retirement plan). PEA enables life insurers and policyholders to avoid market downturns and capture returns from equities (stocks, ETFs and mutual funds) predicted to increase in next one to three trade days via fund prediction advisory by insurers, additionally by individual policyholders. The capability does not exist in insurance markets nor in financial intermediary markets.

Description: Expect to cover key points from the Living to 100 conference around living and social environments for the elderly. Following the review will be a discussion about implications related to LTCI plans and policies around living environments. It will conclude with a peak behind the curtain for pricing for CCRCs.

Description: Health equity is taking a front row focus in many health arenas. Take a closer look at some of the efforts being used to ensure health equity. One area of interest to actuaries is value-based insurance designs (VBID). VBID can be incorporated into exchange plans. These innovations to prevent and treat disease have led to reductions in morbidity and mortality. Learn techniques to improve the quality of care and reduce barriers to high-value care in the form of high-cost sharing.

Description: This webcast will oversee a discussion on the impact of LDTI (transitions and earnings), in addition to day two items and other considerations. Examples include pricing, reinsurance and non-GAAP adjustments.

Description: Develop a better understanding of diversity, equity and inclusion (DEI) across the financial services and risk management industry, with a focus on actuaries. Panelists will address topics such as industry-wide diversity efforts, as well as current challenges facing diverse groups. Come listen to these panelists share perspectives on attracting, fostering, retaining and increasing diverse actuarial talent, in addition to the SOA’s DEI goals in the coming years.

Description: The surge in interest rates over the past few years presents opportunities for life insurers to enhance their Asset and Liability Management (ALM) positions through asset rebalancing to narrow the duration gap and secure higher risk-adjusted yields. This webcast introduces a robust, efficient and readily-executable, liability-driven strategic asset allocation (SAA) framework and implementation considerations. At the conclusion of the webcast, attendees will learn about the key objectives and practical considerations for a successful SAA.

Description: There is increasing industry interest in applying behavioral science to optimize product design decisions and improve outcomes for both insurers and their customers. With a growing set of options within product designs, predicting consumer behavior continues to get increasingly complex. Join this webcast for an overview of key behavioral economic concepts. Key insights will be shared from two SOA projects that explore how behavioral economic techniques can be used in various parts of the life insurance new business process and enforce management.

Description: Disability and group life products can pose challenges for the valuation actuary due to the long-tail runout of traditional disability and group life waiver of premium claims, and due to the sensitivity of the reserves to small changes in assumptions. This session addresses a number of issues of interest to actuaries who work with these products, including recent experience trends and the new 2023 Group Life Waiver Valuation Table. Attendees will learn about best practices in the valuation of these products.

Description: Biases can creep up in models in numerous ways. After discussing various forms of bias, presenting a framework useful to manage bias in models, and contextualizing this effort in the current environment, this session will focus on practical issues faced by the industry.

Description: Global trends in both technology and regulation are causing U.S. insurers to reflect more deeply on their model risk management frameworks. The world has seen a rapid proliferation of AI-based tools accompanied with an overall increased usage of machine learning models, exacerbating model risk and reducing transparency in an unprecedented manner.