/ USE CASE /
BEHAVIOURAL POLICY PRICING
← Return to Insurance Industry
- Pricing models for car insurance are based on many factors related to customer demographics, location, and car information.
- However, there is little customization for driving patterns and behaviours.
- With the emergence of IoT, it is possible to get detailed driving data from consumers and use this to personalize car insurance packages.
- Designed and built a Machine Learning model to predict a customer’s risk of incident based on driving patterns.
- Used the results from this model to feed a pricing model personalized to consumers driving habits.
- Built a segmentation model to segment customers based on driving patterns and identify safer drivers.
- Improved customer experience by rewarding good driving behaviour.
- Segmentation of driving habits lead to profiling and targeting of potentially safer drivers, reducing future claims costs.