U.S. Post-Level Term Lapse and Mortality Predictive Modeling


Aisling Bradfield, FSAI
Julien Tomas, PhD
Joanne Yang


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.


U.S. Post-Level Term Lapse and Mortality Predictive Modeling

Data Visualizations


These interactive dashboards are visualizations of key metrics found in the report. They provide filtering, drill-down, and other interactive capabilities that allow you to focus on specific subsets of the data.

Tableau dashboards - Shock Lapse

Tableau dashboards - Lapse

Tableau dashboards - Mortality


The researchers would like to express our gratitude to all the participating companies for making this project possible. Your contributions have led to a new industry benchmark of experience results and predictive modeling for shock lapse and post-level term lapse and mortality experience. We would like to thank the SOA, along with their staff, for their guidance and support on this research project.

At the Society of Actuaries:

Korrel Crawford 
Cynthia MacDonald, FSA, MAAA
Mervyn Kopinsky, FSA, EA, MAAA 
Ritesh Patel

The researchers’ deepest gratitude goes to the following members of the Project Oversight Group (POG) for their diligent work overseeing the data request development, discussing data and predictive modeling results, and reviewing and editing this report for accuracy and relevance. Project Oversight Group members:

Brian Carteaux, FSA, MAAA [Chair]

Michael Niemerg, FSA, MAAA

Larry Bruning, FSA, MAAA

Tony Phipps, FSA, MAAA

Brian Holland, FSA, MAAA

Mark Rosa, ASA, MAAA

Donna Megregian, FSA, MAAA

Mary Simmons, FSA, MAAA

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If you have comments or questions, please send an email to research@soa.org.