Catching what rules miss.
HOW IT WORKS
The system learns what normal activity looks like and flags departures.
Unlike fixed rules, it adapts as patterns change.
WHY THIS SUITS AI
Fraudsters adapt continuously. Rules written today are circumvented tomorrow.
Anomaly detection does not require examples of the new method.
THE TRADE-OFF
Sensitive settings catch more fraud and produce more false positives.
Every false positive is a legitimate customer blocked, who may not return.
WHERE THE BALANCE SITS
A business decision, not a technical one. It depends on the cost of fraud against the cost of friction.
WHAT MUST HAPPEN
A route for a wrongly blocked customer to reach a person, quickly.
A customer trapped by an automated block with no human recourse is a serious service failure.
WHAT TO MONITOR
False positive rate, by customer segment. If particular groups are disproportionately blocked, that is a fairness problem.
FOR MERCHANTS
Your payment gateway includes screening. Understand its settings rather than accepting defaults.
WHAT NOT TO DO
Treat a flag as proof. It is a prompt to look.
