Description: Model design is an important part of being an actuary, and the SOA highlights the importance of the actuarial control cycle of model design, evaluation and monitoring. What tools are at our disposal for these steps? When should we be concerned or excited about model performance? Can we, and should we, use machine learning tools to assist with model improvement or development?

Description: Analyze the market volatility behavior in context with historical extreme events during this webcast. There will be a focus on understanding volatility clustering and relationships, both contemporary and temporal, in addition to key economic and capital market variables. You'll also learn from a comprehensive attribution analysis, which uses economic data, asset data, retail investor data and event data as explanatory variables. Dive into investment-related Reddit comments used to capture features of retail investors and tree-based models, including Random Forests and Gradient Boosting Machines to justify changes in volatility modeling. Expect this webcast to end with an example of liability-driven investment optimization that illustrates the potential impact of increased volatility assumption, how to adopt stochastic volatility models, how to reflect volatility clustering and return jumps.

Description: The session will discuss key areas of statutory reserving that contain some ambiguity or areas where there are simplifications being used in the industry. The content will be based on current practices used in the industry and possibly accompanied by an industry survey to be completed prior to the session. The focus will be heavily on CRVM, AG38, and PBR statutory frameworks and will include a Q&A portion for audience participation. Some potential topics will be reinsurance modeling, DBO3/ROP treatment, segmentation, deficiency reserves, system differences and multi-tiered designs

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: 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: 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: 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: 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: 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.