Brit has expanded its use of a proprietary machine learning algorithm in its efforts to accelerate the identification of US Tornado property damage.
The technology will be used alongside its own ultra-high-resolution imagery.
Brit successfully deployed this technique to identify insured property damage following last week’s catastrophic US tornadoes.
The machine learning algorithm was developed by Brit’s Data Science team.
It assesses ultra-high-resolution aerial images and data, pinpointing, color-coding, and displaying properties by damage classification in the aftermath of catastrophic events.
“Innovation is a central pillar to Brit’s Claims strategy, and this includes a number of virtual and digital claims solutions for our customers when they need us the most,” Mike Barry, Head of Global Property Claims for Brit.
“We continue to evolve and innovate the use of our best in class aerial imagery and the damage classification algorithm developed earlier this year, enabling quicker and more efficient identification and payment of claims.”