AI can help identify unusual activity for investigation. A warning is not proof of fraud, and no system catches every case.
How it can help
Depending on the system, AI may examine transaction patterns or messages and flag activity that differs from expected behaviour. A team can investigate those alerts alongside other evidence.
Limits and trade-offs
A system may miss fraud or flag a legitimate customer. Performance depends on the data, design and testing; it does not necessarily learn new threats automatically. Monitor errors, review outcomes and update the approach when needed.
Protect people and their data
Use only information appropriate for the task, control access and assess privacy and fairness risks. Decisions that affect a person may need additional safeguards and expert advice. Provide a way to correct mistakes.
Combine technology and people
Clear procedures, staff training, secure systems and human investigation remain important. Compare AI with existing rules and processes before deciding whether it adds value.
What to check before acting on an alert
An alert is a reason to investigate, not a conclusion about a person. Give the reviewer enough context to examine the relevant records, ask for further information and decide whether the warning has an innocent explanation.
For example, a system might flag an invoice requesting a change to a supplier’s bank details. A reviewer can compare the request with the approved supplier record and confirm the change through a trusted contact already on file. A genuine supplier may have changed banks, so the alert alone should not decide the outcome.
To assess the system, compare reviewed alerts with their final outcomes and look for fraud discovered through other checks. Counting alerts alone cannot show what the system missed. Include the time spent investigating and the effect of incorrectly flagged activity on customers or suppliers.
The ICO explains false positives, missed cases and statistical accuracy.
Review both missed incidents and legitimate activity that was incorrectly flagged. Record what happened after an alert, who made the decision and how a person can raise an error. Access, retention and review procedures should fit the information and consequences involved.
The ICO’s guidance on AI and data protection is a starting point for assessing personal-data risks.
