(Image source: Tractable video on Subro AI.)
Tractable, a London-based developer of artificial intelligence (AI) solutions for accident and disaster recovery, has launched AI Subro, a new solution that the vendor says will help U.S. auto insurers resolve subrogation (“subro”) tasks with AI.
According to The National Association of Subrogation Professionals, 15 percent of insurance claims are missed opportunities for subrogation. AI Subro is a development of Tractable’s AI Review solution, which the vendor says is already used by many of the world’s leading insurers to ensure that claims are assessed correctly and repairs are carried out in compliance with procedures and standards.
James Spears, Head of Automotive, Tractable.
Tractable says that AI Subro digitizes and accelerates many of the tasks involved in subrogation, the process by which insurers legally pursue third parties that have caused losses to the insured. Subrogation has historically tended to be a highly manual, time-intensive process, frequently outsourced to service providers.
With AI Subro, insurers can carry out their own subro claims, accurately and efficiently, helping them avoid outsourcing, recover more losses and reduce their loss ratios, resulting in better outcomes for policyholders, the vendor asserts.
Simplifying and Accelerating the Subrogation Process
“Subrogation is a critical part of the insurance process, but today it is often opaque, time consuming, and labor intensive—making it difficult to get right,” comments James Spears, Head of Automotive, Tractable. “Leaders across the industry tell us they are desperate to find a better way forward, and AI Subro is exactly that: it helps insurers identify when and where they should be pursuing subrogation, simplifies and accelerates the process, and helps parties come to terms transparently and efficiently.”
Tractable describes AI Subro as working by reviewing an adverse insurer’s demand packets—the pictures of a claim that would normally be sent to another insurance company. The AI examines the data and ensures the damage estimate is correct, enabling the insurer to make a more accurate loss claim from its counterparty. The technology can also be used as a mediator between the two parties, enabling both to come to agreement more quickly and transparently, and potentially avoiding arbitration.
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