Enterprise Rent-A-Car Entegral, in partnership with InsurTech Tractable, has launched Smart Assist, a vehicle claim assistance product designed for use with mobile devices, in North America.
Tractable’s AI leverages deep learning for computer vision, as well as other machine learning techniques to make accurate decisions. The technology is also able to make recommended repair operations and guides the claims management process.
Entegral is an integrated and open platform that facilitates communication and collaboration among tens of thousands of collision repair shops, insurance providers, vehicle manufacturers and other industry professionals globally.
Designed to provide value to industry partners, Enterprise Holdings launched Entegral in 2019 to help simplify the post-accident process, reduce claims cycle times and enhance the overall customer experience.
This new software as a service ((SaaS) offering, according to Enterprise and Tractable, puts more control directly into the customer’s hands after a collision.
Moreover, it helps to digitise and automate the claims journey from first notice of loss.
The product was launched on Sunday with a demo at Guidewire Connections 2022 in Las Vegas, where Entegral is a sponsoring PartnerConnect Solution partner.
Joe Rector, Entegral vice president, said, “Managing the full lifecycle of an auto claim is complex for everyone involved – not to mention incredibly stressful for the vehicle owner. By connecting people, systems and data on an open platform, Entegral is simplifying and harmonizing the automotive claims experience for industry partners and vehicle owners alike.
“The launch of Smart Assist illustrates how we’re continuing to invest in advanced solutions to improve claims processing. By removing inefficiencies from the process, we enable partnerships to come to life and expedite the accident recovery timeline.”
Earlier this year, Beesafe, which is part of the Vienna Insurance Group, leveraged Tractable’s AI technology to assess car damage and accelerate claim processes.
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