A health risk score was created to investigate the possibility of using data provided by wearable technology to help predict overall health and mortality, with the ultimate goal of using this score to enhance the pricing of health or life insurance. Subjects were categorized into low‐, increased‐, and high‐risk groups, and after results were adjusted for age and sex, Cox proportional hazards analysis revealed a high level of significance when predicting mortality. High‐risk subjects were shown to have a hazard ratio of 2.1 relative to those in the low‐risk group, which can be interpreted as an equivalent increase in age of 7.8 years. Our findings help to demonstrate the predictive capabilities of potential new rating factors, measured via wearables, that could feasibly be incorporated into actuarial insurance pricing models. The model also provides an initial step for insurers to begin to consider the incorporation of continuous wearable data into current risk models. With this in mind, an emphasis is placed on the limitations of the study in order to highlight the areas that must be addressed before incorporating aspects of this model within current pricing models.
- actuarial science