Discover how Shift Technology's advanced resolution techniques helped save $525,000 by uncovering fraud in a kitchen fire claim. Learn about the unique advantages of AI in insurance fraud detection and how it ensures accurate claim analysis across diverse cases.
This video is part of a series of interesting cases, featuring several of our insurance-focused team of data scientists.
"A cool case that we recently found was a kitchen fire claim. The value of this loss was... about $525,000 to the insurance company. This looked like a brand new occurrence. Shift was able to resolve and reconstruct that policy holder with a claim two years prior using our different entity resolution techniques, and via those techniques we were able to identify with a high degree of confidence that there was a prior loss that heavily over overlapped the current circumstances, and as a result we raised an alert to the insurers SIU team.
After investigation, they ultimately deemed that the current facts of the loss were being misrepresented and they were able to not pay out the claim, resulting in a saved amount of $525,000. The main way that Shift was able to handle this case that maybe other fraud detection providers or insurers might not be able to find is via those entity resolution techniques. Because we work with so many different clients and so many different geographies and insurance scopes, we're able to see a very robust set of features and a very robust sample of data to work with and how best to approach this problem based on the data requirements and the type of alert that the insurer wants to see."