Fraud detection

What it means

Fraud detection is the set of checks that decide whether an action looks like genuine use or abuse of your business. It scores sign-ups, logins, orders and payouts from signals such as device, location, speed, spending pattern and history, then allows, challenges or blocks.

It differs from ordinary security because the fraudster often uses your product exactly as designed. There is no exploit to patch. Detection looks at behaviour across many events, which is why it sits beside, not inside, the checks that guard a single request.

Why it matters

Fraud is paid for directly: chargebacks, stolen goods, rewards paid out, and compute spent on accounts that never pay. Card networks also monitor dispute levels, and a merchant with too many may face extra fees or lose the ability to take cards.

Detection that is too loose lets abuse through; too tight and it blocks real customers, which costs sales and support time. The balance needs measuring. Done well, it complements rate limiting and account takeover defences rather than replacing them. It also needs regular review as fraudsters change tactics.

How it shows up

You meet it at sign-up, sign-in, checkout, withdrawal and any reward claim. Typical pieces are rules (more than three cards in an hour), device and network reputation, velocity limits, address and identity checks, and models trained on past cases. Many teams buy a service and add their own rules for their own product.

The repeated mistakes are a tool that scores but does not feed the decision, rules nobody reviews as fraud changes, and logs too thin to investigate with. Test it by behaving badly on purpose, in a safe environment, and see what is noticed. Detection is not a substitute for fixing business logic flaws.