Seven Practices Help Banks Balance AI Fraud Controls and Customer Experience

Financial institutions are increasingly using artificial intelligence to strengthen anti-money laundering, or AML, controls and fraud detection through automated monitoring and real-time analysis. The technology can identify suspicious behavior more quickly, but overly sensitive alerts, repeated identity checks and poorly explained account restrictions can inconvenience legitimate customers. The challenge is significant because banks must meet compliance obligations and reduce financial-crime exposure without undermining trust or making routine services harder to use.

The latest report outlines seven practices for improving customer experience alongside AI-driven controls, including risk-based interventions, low-friction verification, transparent communication, human review, cross-functional coordination, continuous monitoring and model governance. It does not identify a financial institution implementing the framework or disclose investment amounts, performance metrics or a specific publication date. The recommendations therefore represent an operating blueprint for financial-services providers, rather than a dated deployment or measurable result from a particular bank.