Experian has launched Transaction Forensics, an AI-powered fraud detection solution that combines Resistant AI's behavioural analytics capabilities with Experian's proprietary data assets to detect Authorised Push Payment (APP) fraud and AI-generated document fraud in real-time across bank-to-bank payment flows. The system operates 80 individual AI models to identify fraudulent activity patterns, addressing a critical enforcement reality: financial services firms face escalating FCA and PRA scrutiny on their fraud prevention and operational resilience capabilities, with enforcement notices increasingly citing inadequate detection of fraud involving AI-enabled fraud actors.
The solution directly reflects the evolving threat landscape where fraudsters themselves deploy AI to generate convincing documents, impersonate legitimate payees, and orchestrate social engineering attacks at scale. UK financial services firms operating under FCA operational resilience requirements and Consumer Duty obligations must now defend against AI-assisted fraud while simultaneously complying with anti-money laundering and fraud prevention standards. Transaction Forensics addresses that dual challenge by automating high-volume fraud pattern detection while maintaining the audit trail and documentation that regulators require for compliance demonstration.
For financial services firms evaluating fraud prevention technology, the combination of real-time detection and historical data analytics reflects best practice. Beyond point-of-transaction detection, firms should implement document intelligence capabilities—such as Trovix Sift for verifying legitimate customer documentation against sophisticated AI-generated forgeries—to prevent fraud at the application and onboarding stage. Experian's approach illustrates how incumbent financial data providers are repositioning themselves as AI-augmented risk intelligence vendors rather than relying on legacy rule-based systems.
The broader implication is that AI deployment in financial crime is bidirectional: fraudsters use AI to scale attacks, and firms must use AI to defend at equivalent scale. Regulatory expectations will inevitably follow market practice, meaning firms that delay deploying AI-enhanced fraud detection will face competitive disadvantage and potential regulatory criticism as the market standard evolves.
Source: Experian