Wearable fitness devices and smartphones are transforming life insurance underwriting by providing health and activity data. This session examines how AI-driven predictive models built on wearable data can dramatically improve mortality risk stratification compared to traditional methods based on static metrics.

We will highlight insights from recent collaborations with Willis Towers Watson (WTW) and Munich Re Life. For example, daily step count has emerged as a more powerful predictor of mortality risk than many conventional factors (second only to age). A wearable-data-driven model outperformed one using traditional underwriting inputs in stratifying mortality risk. These findings reveal that active lifestyle indicators can trump classical risk factors – for example, smokers averaging 7,000+ steps per day exhibit lower mortality rates than sedentary non-smokers. 

Attendees will learn how incorporating wearable-derived measures (such as steps, heart rate, and sleep patterns) into underwriting can enhance accuracy, expand insurability, and encourage healthier customer behaviours. The presentation underscores a shift toward customer-centric, data-driven underwriting and the significant potential for innovative, more inclusive life insurance products on a global scale. 

Speakers:

Will Cooper, Klarity Health 

Andrew Wibberley, Alea Risk