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: This report provides an educational background on the process of building predictive models, as well as a detailed presentation of the model results. Predictive models provide a method to capture variation by multiple variables and understand the relationship between these variables. This allows for a deeper understanding of key variables than is possible under a traditional approach.

Description: As more term insurance policies move to the post-level period, actuaries are evaluating policyholder behavior and expected mortality. Enough experience has now emerged to provide a spectrum of outcomes that can model the relationship between premium increases, persistency and mortality. The presenters will share findings and consider how different post-level premium structures produce different results.

Description: This report provides an educational background on the process of building predictive models, as well as a detailed presentation of the model results. Predictive models provide a method to capture variation by multiple variables and understand the relationship between these variables. This allows for a deeper understanding of key variables than is possible under a traditional approach.

Description: Term Life insurance is a popular product in the U.S. As a growing number of policyholders have been reaching the end of the level term period, the SOA has been committed to studying policyholder behavior in the post-level term (PLT). Shock lapse, post-level term lapse and mortality have previously been analyzed in SOA PLT studies conducted in 2010 and 2014. This study provides an update of experience and some valuable new insights.