Description: The presenters will explore the current state of the North American mortality baseline and long-term improvement assumptions and determine what we can learn from the UK's approach. They will share research done by the Society of Actuaries and other organizations to describe how to build a better model, plus show the impact socio-economics and other factors have on longevity expectations. The presenters will offer suggestions for how U.S. and Canadian pension plan and insurance actuaries--and the industry itself--can best use this research to develop a better model for the risk management of pension plans and group annuities

Description: The session offers high-level initial steps to get started using R, as well as a list of helpful resources for both general data science and actuarial science with R. Attendees will learn about popular R packages to perform practical tasks such as importing, transforming and visualizing data, as well as packages commonly used by actuaries. You will also be introduced to the markdown package for creating reproducible and reusable analyses and workflows. By the end of the session, you will be familiar enough with using R and RStudio to begin incorporating these tools in your day-to-day work as an actuary

Description: Last year, the COVID pandemic significantly increased the pace of change in the life insurance industry, particularly in Accelerated Underwriting (AU). In the past, underwriting process changes occurred relatively infrequently and over a matter of years. Now, with new data sources and predictive models constantly evolving, the frequency of underwriting enhancements and decisioning changes, particularly in AU programs, is occurring every few months. With so much change occurring quickly, how can a company effectively monitor and understand the effects of these changes to make continuous adjustments with confidence and agility? Well-designed data visualizations allow a reviewer to navigate and comprehend detailed results quickly because our brains can process data in a picture format more than 15 times faster than text. Today’s advanced BI tools can make AU program monitoring more efficient and help companies adjust quickly to the results from program changes.

Description: This paper compares two mortality projection models – the latest version of the CMI Mortality Projections Model and the latest version of MIM-2021.Both models were applied to data for England & Wales and the US, and the results were compared.

Description: The Group Life COVID-19 Mortality Survey gathers a high-level view of U.S. Group Term Life Insurance mortality results during the COVID-19 pandemic through June 2023, as compared to prior period baseline mortality results. This new report is an update to the survey report released in May 2023, which contained data through December 2022.

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

Description: A data format for mortality tables along with applications.

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 2009 Estonia experience study includes both mortality and persistency studies of policies in force any time during the 2006-2008 study period. The study applies to the entire portfolios of the contributing companies and these companies represent the vast majority of the Estonia individual life insurance market. Separate studies were performed based upon policy counts and insurance in force. Actual mortality was compared to expected mortality based upon the SOA 1975-80 select and ultimate mortality table.

Description: The presenters will address innovations in health and wellness designed to mitigate and/or manage mortality risk. The presenters will briefly review the latest research on the leading causes of death and share ways that life insurers and insurtech partnerships are using technology, customer engagement and scientific advances to enhance/extend the lives of policyholders. The presenters will draw from industry research and reinsurer studies and from the latest initiatives in health and wellness innovations.