Description: Deep learning neural network applied to experience analysis for post-level term lapse and mortality.

Description: While our ability to access and analyze large quantities of data is better than ever, many long-term products suffer from sparse data in critical risk areas, such as deep in-the-money lapse experience and long-term utilization rates for income guarantees. The presenters will explore industry-level annuity experience data for these types of situations, and discuss quantitative approaches to addressing them in pricing and other applications.

Description: This session meets the needs of life insurance actuaries who are focused on experience studies, assumption setting, and/or product development. The presenters will use industry data to illustrate how policyholders react to product design, such as premium jumps in the PLT period and UL with high interest rate illustration, and trends in the life insurance market, including the introduction of smoking distinguished rates and the shift towards an increasing number of preferred underwriting classes.

Description: A short article looking at the results from an annual assumption survey of VA writers with a focus on changes companies observed and planned to make due to COVID-19. In the article we discuss what companies should be considering as they approach the 2020 year end assumption setting and audit season.

Description: Apart from their operating environment and the core risks they help others mitigate, organizations are largely impacted by behaviors--particularly those of their policyholders. This session builds on the first session in this series by considering how medical advances might influence policyholders, while also considering how agents/brokers, product design, and the economy can also be influencers. Weigh whether and to what extent behavioral uncertainties have been adequately integrated into the firms' assessments of business performance, both past and future. The presenters will also highlight activities being undertaken by firms to influence behaviors, in part building on the second session in this series by considering these activities through a regulatory lens. This session is for anyone interested in enhancing their understanding of uncertainty due to behavioral factors.