Rohan.
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What my PhD taught me about insurance fraud

Fraud detection is not just a classification problem. It is a question of where actuarial judgement and machine learning meet.

Most fraud is rare, which makes it a hard signal to learn. The interesting work is less about the algorithm and more about how you frame the label, the cost of a false positive, and the feedback loop with claims teams.

The cost matrix matters more than the model

A model that catches more fraud but blocks honest claimants can cost more than the fraud it prevents. Getting the cost matrix right is an actuarial question first.