WTW-重新分类死亡风险（英）

Reclassifying mortality riskHow wearable-driven mortality modeling reshapes risk stratification in life insurance underwritingwtwco.comReclassifying mortality risk / 2CONTENTSSection 1: Executive summary 3Section 2: Background5Section 3: The Klarity Model 7Overview7Data and methodology 7Mortality scoring 9How does the model compare with current preferred guideline risk assignment? 9Benefit gained from activity data 15Section 4: Use cases and next steps 18Section 5: About Klarity 20Section 6: About WTW 21Reclassifying mortality risk / 3Section 1:Executive summary“Sitting is the new smoking” is a catchphrase often used to encourage people to get some level of physical activity. Medical personnel, underwriters, actuaries and mortality researchers understand activity level is an important measure to assess one’s health and expected longevity. Unfortunately, activity level information is often overlooked or has been measured only through self-reporting or correlation to other measures such as body mass index (BMI) in the life insurance risk selection process. Since the proliferation of multiple risk classes, companies have used traditional measures such as cholesterol level, blood pressure, BMI, tobacco usage, and personal and family history, to name a few, for stratifying and determining risk class criterion and placement for applicants. While each is an important health metric, these traditional approaches and metrics often misclass applicants because the measures only provide part of an individual’s health profile and often miss important individualized measures such as resting heart rate, heart recovery rate, sleep and activity versus inactivity levels. Over the past 10-plus years, the industry has been moving toward changing the underwriting process. For life insurance, this has meant rethinking the data sources used, improving the customer’s experience and shortening the time from application to policy issue. This has added to the challenges for risk classification and difficulty in truly differentiating the risk profiles of the preferred risks as well as the healthier impaired. The need to rethink the risk stratification process in the life insurance industry has become increasingly evident over the past decade. With the proliferation of new data sources and advancements in technology, there is a significant opportunity to enhance the accuracy and efficiency of underwriting processes. The Klarity model aims to address this need by leveraging nontraditional data to produce individual-level mortality scores that can predict and classify risks more effectively than traditional methods.Over the past year, WTW's Insurance Consulting and Technology (ICT) team has analyzed a new risk scoring tool developed by Klarity, which incorporates data obtained from a wearable device such as a fitness watch, a smartphone or other device that captures activity levels, sleep patterns, heart rate and pulse data. The model, originally trained on U.K. nationa