WTW, an advisory and broking firm, is working with UK-based health data analytics company Klarity to test whether wearable technology can improve how life insurers assess and price individual risk.
Current life insurance underwriting methods typically rely on factors like cholesterol levels, blood pressure, BMI, smoking status, and family medical history.
While useful, these indicators often give only a partial picture of a person’s health and can miss relevant day-to-day data such as resting heart rate, recovery time, sleep quality, and physical activity levels.
Klarity has created a new risk scoring tool that uses over a decade of health data, covering more than six million life years.
The tool incorporates data from wearable devices like smartwatches to produce individual-level mortality risk scores. These scores are intended to help insurers make more informed decisions during the underwriting process.
WTW tested Klarity’s model using US data from the National Health and Nutrition Examination Survey (NHANES). According to their analysis, the model was able to highlight variations in individual mortality risk that standard underwriting approaches might miss.
This includes identifying individuals who may qualify for lower premiums based on wearable-derived data, even if traditional methods wouldn’t place them in a preferred category. Conversely, some applicants flagged as low risk through conventional metrics showed signs of elevated risk when evaluated through the wearable-based model.
The findings suggest that while traditional underwriting offers a broad categorisation, the use of more granular, behaviour-based data could provide added context. The model also pointed out applicants with unexpected risk factors that might otherwise go unnoticed.
This collaboration reflects a growing interest in applying newer data sources to established insurance practices. While the model’s impact on pricing and classification appears promising in tests, how widely and effectively it can be implemented across the industry remains to be seen.
Will Cooper, Founder and CEO of Klarity, commented: “By integrating AI-driven insights with diverse health and behavioural data, we’ve built a model that not only enhances underwriting accuracy but also strengthens customer engagement and loyalty.
“Our collaboration with WTW not only validates the model’s performance in North America – it also reveals how many applicants are under- or over-classified by traditional methods. This opens the door to more accurate, inclusive and dynamic underwriting.”
Mary Bahna-Nolan, Senior Director, Insurance Consulting & Technology, WTW, added: “The life insurance industry has a unique opportunity to harness the power of data to deliver more personalised outcomes that reflect real-world health habits.
“Klarity’s model is a prime example of how predictive analytics – coupled with data representative of an individual’s health indicators and habits such as movement or activity, heart rate and sleep – can redefine risk assessment and improve mortality prediction. Eventually, this will open the door to more personalised pricing and rethinking customer experience and engagement.”
With 62 million people in the US using fitness trackers in 2024—a number expected to exceed 92 million by 2029—smartwatches and other wearable devices have become a common part of daily life.
Data collected from these devices offers ongoing insights into users’ habits and health patterns, which can be used to better estimate lifestyle-related risks and support more tailored life insurance assessments and pricing.
link