How Do Authorised Scams Hide Behind Legitimate Bank Transfers?

The rise of authorised scams means banks can no longer rely solely on identity verification. If a legitimate customer is coerced into making a payment, traditional checks are insufficient. The problem extends beyond the initial transaction, as funds often move through multiple mule accounts, making it crucial for banks to analyze broader patterns of activity rather than individual payments.

Detecting these scams is difficult because individual transactions can appear genuine. Banks are therefore exploring advanced analytics, AI, and network analysis to build a more comprehensive view of customer behavior. This includes examining device and transaction context, beneficiary details, and session activity for signs of manipulation, such as remote-access software or indications of an active scam call, to make more informed trust decisions.

Criminal networks increasingly blur the lines between fraud and money laundering, making isolated approaches by banks less effective. Integrating fraud and AML intelligence, supported by behavioral and network analysis, can help identify connections across cases that might otherwise be missed. This shift necessitates evolving operating models and clear governance to maintain accountability and regulatory oversight.

No single bank can fully address the problem, as fraudsters often target multiple institutions and operate across borders. Network intelligence, which tracks suspicious activity beyond a single bank's systems, is becoming vital. This collective approach, combining technology, shared intelligence, and ecosystem-wide collaboration, is essential for developing a complete picture of criminal activity and combating organised financial crime groups.