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Brit targets faster catastrophe response with machine learning algorithm

21st September 2021 - Author: Matt Sheehan

Brit Ltd has announced the launch of a proprietary machine learning algorithm designed to accelerate the identification of post catastrophe property damage, based on the use of ultra-high-resolution imagery.

BRIT logoThis proof of concept is being used by the Brit Claims team and its delegated claims adjusters in the wake of Hurricane Ida, to expedite payments for customers.

To this end, Brit’s Data Science team developed and overlaid a machine learning algorithm to access the ariel images and data to identify properties by damage classification within days after a catastrophe event, even before claims are reported.

Brit has been working with GIC (Geospatial Insurance Consortium) since April 2019, a non-profit organisation that captures best in class post-event ariel imagery for first responders and insurance companies.

“A claim is the single most important interaction that an end client will have with their insurer and this will often be at a time of significant difficultly,” said Sheel Sawhney, Group Head of Claims and Operations.

RMS

“We are therefore continually focused on improving the service we offer and how quickly we can provide resolution for our customers. Innovation and technology are critical to the equation. This use of machine learning techniques and the best available imagery is further evidence of how our award-winning claims team is finding new ways to increase the speed and accuracy of claims payments.”

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