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U.K.-based auto insurance broker 1ST CENTRAL (Haywards Heath, West Sussex) has selected Shift Technology (Paris), a provider of AI-native fraud detection and claims automation solutions for the global insurance industry, to support its fraud detection initiatives. 1ST CENTRAL will deploy Force, Shift’s fraud detection solution, to uncover and identify suspicious behaviors in both the insurer’s application and claims processes.
1ST CENTRAL offers a customer-centric market proposition that seeks to combine affordable premiums with a focus on simplifying the overall insurance experience for policyholders. The company has also identified minimizing the impact of fraud on its business has as a driving principle. Following what Shift characterizes as an exhaustive evaluation of the fraud detection solutions available, 1ST CENTRAL selected Force due to its market-leading technology.
“Identifying fraud quickly ensures we can protect our honest customers, and as fraud continues to evolve, it’s extremely important that we have the technology to keep one step ahead of fraudsters,” comments Paul Priestley, Counter Fraud Director, 1ST CENTRAL.
Shift describes Force as using artificial intelligence and advanced data science to identify suspicious actions which may indicate an attempt to defraud insurers. The technology can also identify links between seemingly unassociated individuals or networks of individuals. This insight into fraud networks gains further power when combined with the insurer’s own data and that from third-party sources, according to the vendor.
Keeping Loyal Customers
“For insurers like 1ST CENTRAL, which place incredible value on delivering an exemplary customer experience, stopping fraud is of primary importance,” comments Jeremy Jawish, CEO and co‑founder, Shift Technology. “Identifying fraud within the claims process, and not passing those costs along to honest policyholders is one way to keep loyal customers. Mitigating the risk upfront, and not writing policies for bad actors to begin with is another.”
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