The INSURTECH Book

Behavioural Design and Price Optimization in InsurTech

By Bernardo Nunes, PhD

Head of Data Scientist, Growth Tribe Academy

Delivering effective pricing is still today a core challenge for many insurers. The main reasons are due to:

1. Asymmetry of information. Buyers of insurance products possess better information about their own desires, preferences, and behaviours than any insurer would ever do. As a result, insurers rely on predictive models to infer premiums that are based on a heterogeneous number of risk factors for each future potential new insured.
2. Post sales risk profiling. Once insured customers are on cover, insurers gain insights on their behaviour to better understand high-risk from low-risk profiles post sales, and hence use this information to refine future pricing strategies.

The good news is that these challenges can be addressed in a much more informative way due to the rise of InsurTech startups and the possibility to observe customer behaviour better through the digital footprints each customer leaves behind when using connected devices.¹ Based on individuals’ behavioural patterns, insurers can develop personalization triggers to “nudge” them towards specific actions and test whether these interventions are effective to reduce potential claim incidences.

There are lots of InsurTech solutions out there, and many of the applications I have seen still seem to offer one-size-fits-all mechanisms, which very rarely consider customers’ differences. Personalization, ...