Catch the odd one while the money is still there.

Fraud detection AI learns what normal looks like for each customer or employee — amounts, times, devices, payees, locations — and scores every new transaction, claim or application against it as it happens. Unusual ones are held with the reasons they looked odd, a person reviews them, and their decisions are used to improve the model.

Some genuine transactions will be held — that is the trade-off. Judging each customer against their own normal, and tuning thresholds with your team, keeps it low.

Reviewers decide faster and more fairly, and auditors and regulators expect decisions to be explainable.

It works alongside them: rules for patterns you already know, models for the ones you don’t.

Yes — the same approach finds duplicate bills, inflated claims and suspicious cash-on-delivery patterns.

In your infrastructure or a private cloud in India, with access logged — important for regulated lenders.