Rethink the way insurance providers understand their customers

Discover patterns in driving behaviour that can reduce risk for underwriters, lower premiums for good drivers, and promote safer driving habits that benefit everyone.


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Aioi Nissay Dowa Insurance UK (AND-E UK), a black box car insurance provider in the UK, is constantly looking for ways to encourage safer driving patterns in their customers through a merit-based reward scheme and rewarding safer driving with cheaper policies upon renewal.

They needed a way to automatically detect safe patterns of driving from those that could be deemed dangerous, or outside of the terms of a customer’s policy.


Connect with an expert


Data scientists at Mind Foundry worked closely with domain experts at AND-E UK to develop a fully automatic, end-to-end pipeline with state-of-the-art Machine Learning methods to separate out the safest drivers from those who engaged in risky driving behaviour, off-policy behaviour (such as using their personal coverage for commercial delivery driving), or activities designed to conceal unsafe, risky or undesirable behaviour.

The solution was built to be explainable and collaborative, by design. It included different levels of granularity at multiple stages so that it could not only flag which “trips” on a policy were safe or unsafe, but also which moment or moments in the trip were most influential in shaping this conclusion.

As domain experts investigated and confirmed or corrected each “flag”, the model improved itself through continuous metalearning.


The price is right -1


To date, Mind Foundry’s continuously learning predictive model has reached a precision over 90%, validated manually by domain experts at Insure The Box.

The model has enabled AND-E UK to extract more value from their data to further advance their business processes, as well as gain a better understanding of their customer’s need.

This successful engagement between Mind Foundry and AND-E UK is an example of why Machine Learning will be at the core of the future of insurance.





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