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: 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: A recommendation for a set of improvement factors that vary by gender and attained age to be used in conjunction with the 2008 Valuation Basic table or the 2015 Valuation Basic table for AG-38 purposes.

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.

Description: This report examines the mortality of Canadian pensioners subdivided by pension level, using data from the Canada Pension Plan (CPP) and Québec Pension Plan (QPP)

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.