WTW and Klarity are working together to help life insurers improve pricing accuracy by integrating wearable technology and data into their underwriting processes.
Klarity has developed a risk scoring tool that produces individual-level mortality scores to predict and classify risks. The model incorporates third-party data obtained from smartwatches and other wearable devices that track physical activity, heart rate and sleep patterns.
The two organisation’s collaboration included testing the efficacy of the model’s mortality score predictions on data from the US, leveraging data from the National Health and Nutrition Examination Survey (NHANES).
WTW said its analysis found Klarity’s model can more clearly identify individual mortality risk profiles, enabling improved risk segmentation and allowing insurers to align pricing more accurately than traditional underwriting metrics alone.
For example, some residual non-smokers had risk profiles similar to risks classified as preferred and, in some cases, best preferred based on traditional criteria alone, meaning these individuals could qualify for better rates, the firms said.
Use of the model also helps to flag more extreme outliers within each class. For example, the model flagged a smaller percentage of applicants who may be considered preferred risks under traditional underwriting metrics but showed hidden risk factors.
The firms said this suggested they may not actually exhibit mortality aligned with preferred risk and, in some cases, even residual standard risk pricing.
Will Cooper, founder and CEO of Klarity, said: “By integrating AI-driven insights with diverse health and behavioral 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 and technology at WTW, said: “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.”
