Insurance companies are continually subjected to questionable claims, whether that be actual fraud, waste, or just abuse. Insurance fraud in the U.S. alone represents a USD 32 billion in P&C and USD 84 billion in health care costs per year loss to insurance companies. Each carrier has tens and even hundreds of thousands of claims processed, yet the fraudulent claims are actually a small fraction of the total. This leads to highly unbalanced datasets with sparse data that makes fraud detection especially hard. Combine that with the fact that new schemes are constantly emerging for which there is no available ground truth until well after a scheme is successfully implemented. This leaves insurance companies at a disadvantage.

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