Abstract
Life insurance companies, as equity stakeholders in policyholders’ lives, have incentives to mitigate their health risks. I introduce a framework that enables life insurers to evaluate the financial viability of developing and implementing health engagement programs. By leveraging a proprietary big database of health and mortality information from a large U.S. life insurer, I use machine learning techniques to quantify the benefits and use a rational addiction model to calculate the costs associated with these programs. The estimated net benefit available to the life insurer from the smoking cessation program is USD 87 million and the aggregate benefit from including other chronic conditions is USD 872 million. I explore the broader application of this framework in a general health policy context.
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