Brite introduces algorithm to accelerate claims settlement after disasters

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Brit has announced the development and proof-of-concept launch of a proprietary machine learning algorithm designed to expedite the identification of property damage after a disaster.

The proof of concept will be used by the Brit Claims Team and its delegated claims adjusters to improve claims service and expedite payments after Hurricane Ida, Brit said.

The algorithm accesses ultra-high-resolution aerial images and data that it can use to locate, color-code and display property by classifying damage within a few days of a disaster. In this way, the claims team can proactively identify, sort and assign response activities – even before claims are reported.

The algorithm is part of a collaboration between Brit and Geospatial Insurance Consortium (GIC), a nonprofit that takes aerial photos after the event for first responders and insurance companies. Using the images from GIC and the machine learning algorithm, the Brit Claims team can have a virtual claims settlement platform that can expedite payments in places that local field salespeople cannot immediately reach in the days following a disaster, the company said.

Continue reading: Brit works with aerial photography providers

“A claim is the most important interaction an end customer has with their insurer, and it often happens during times of significant difficulty,” said Sheel Sawhney, group head of claims and operations at Brit. “We are therefore constantly focusing on improving our service and how quickly we can provide solutions for our customers.

“Innovation and technology are critical to the equation. This use of machine learning techniques and the best images available are 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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