A Machine Learning Approach to Incorporating Industry Mortality Table Features into a Company's Insured Mortality Analysis

September 2019

The Product Development Section, the Modeling Section, the Reinsurance Section and the Financial Reporting Section announce the release of a new research report that introduces a novel framework for leveraging the “architecture” of an industry mortality table within a company’s predictive analytics-based insured mortality analysis. Authored by Marc Vincelli, the paper presents methodology for insurers to better model the relationships between mortality cells across ages and durations when faced with sparse experience data. One potential application of the approach is in the initial calibration of an industry mortality table, via its learned features, to a company’s own experience. 


A Machine Learning Approach to Incorporating Industry Mortality Table Features into a Company’s Insured Mortality Analysis

Appendix A Files

Appendix D Tables

Thank You

The Sponsors would like to thank the individuals who served on the Project Oversight Group:

June Quah – Chair

Mary Bahna-Nolan

Larry Bruning

Tom Farmer

Sara Goldberg

Andrew Harris

Michael Kula

Nora Li

Yuanjin Liu

Michael Niemerg

Yvonne Ren

Zachary Stenberg

Si Zhang

Mervin Kopinsky, SOA Experience Studies Actuary

Jan Schuh, SOA Sr. Research Administrator

Ronora Stryker, SOA Sr. Practice Research Actuary

Questions Or Comments?

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

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