The FCA reports that financial firms closed 238,396 suspected money mule accounts in 2025. Its findings suggest criminal funds may move through several accounts before being cashed out, making early identification and intelligence sharing increasingly important. Although the review concerns banking and payments, the message is highly relevant to mortgage firms handling identity documents, deposit evidence, gifted-deposit information and unusual payment patterns.
Machine learning can help detect anomalies at scale, such as inconsistent documents, suspicious transaction chains or repeated patterns across applications. But mortgage firms should avoid treating a risk score as proof of wrongdoing: alerts need proportionate human review, documented escalation and robust data governance. Advisers should also reinforce basic client safeguards, including verifying counterparties, checking firm authorisation and remaining alert to unusual requests to amend financial information.