Statistics show that each year, fraudulent activities cause an estimated amount of $30 billion loss for U.S. property and casualty insurers. To be able to prevent these losses, a new approach of fraud detection needs to be embraced.

In this paper, we show how TAZI’s Claims Fraud Detection Solution can help SIU members spend less time on clean claims and concentrate more on the suspects. Our solution is based on a patented Continuous and Explainable, No-code, Automated Machine Learning platform. We lay out how our solution detects new patterns of fraud. We also demonstrate how it is possible to discover new micro segments in those patterns by receiving explanations.

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