Description: An application of GLM trees to mortality modeling using the Individual Life Experience Committee 2009-2015 dataset. GLM trees are a hybrid of GLMs and decision trees which are analogous to the way actuaries have analyzed data. The major benefits include speeding up actuarial analytic workflows, improving data understanding, and improving data visualization.

Description: The presenters will cover the latest research undertaken by the Individual Life Experience Committee (ILEC). With several years of very robust individual life insurance experience data accumulated through the mandatory Statistical Agent data calls, this vast amount of data allows for various deeper dives into specific segments of business, such as large face amount, older age or juvenile. Speakers will cover studies the committee is currently involved in, future planned efforts, and results from a variety of sub-segments of business. Attendees will learn about emerging statistical techniques in scrubbing data, more refined quintile-grouped data segments, and interesting ways of conceptualizing how A/E results have changed from year to year. There will be something for everyone!

Description: The Canadian Institute of Actuaries (CIA) and Society of Actuaries (SOA) engaged RGA Reinsurance Company (RGA) to undertake a research project on level premium term life insurance products with a particular focus on the magnitude and impact of the “shock lapse” at the end of the level premium period. This project is similar to the SOA-sponsored research completed by RGA in 2014 for USA business.