AI vs. Scams: Turning Cyber Intelligence Into Prevention

Financial institutions worldwide face growing pressure to address scams as interconnected financial, cybersecurity, and cross-disciplinary crime risks. Socially engineered attacks targeting customers, members, and employees can expose credentials, compromise accounts, and facilitate money laundering via payments into criminal networks. As artificial intelligence makes impersonation more convincing and scalable, FIs need protection that extends beyond identity verification and transaction monitoring to recognize how trusted individuals are being manipulated. 

This report examines how AI can be used as an asset, not just a risk, by playing a key role in connecting cyber-threat intelligence—compromised personal information, exposed credentials, previous scam encounters—to authorized behavioral and transaction data to identify conditions associated with heightened scam risk. AI can detect manipulative communications, recognize unusual financial behavior, and uncover relationships with suspicious recipient accounts. Javelin’s research, however, finds that advanced scam-predictive modeling remains uncommon, creating an opportunity to develop dynamic risk profiles and deliver personalized interventions as scam tactics evolve. For financial institutions and employers, these capabilities can strengthen customer and employee protection through targeted education, timely warnings, identity theft support, and more informed payment reviews. 

Key questions discussed in this report:

• How can AI combine identity exposure, behavioral, and transactional intelligence to identify customers and employees at heightened risk of emerging scam typologies?
• How can financial institutions use predictive insights to deliver personalized education and timely interventions before scams result in financial loss, account compromise, or broader criminal activity?
• What data-sharing, privacy, integration, and performance requirements should guide partnerships with identity protection providers to ensure effective, measurable scam prevention?
• How can financial institutions apply MITRE ATLAS, ATT&CK, and the Fight Fraud Framework (F3) to align AI-driven scam detection, identity intelligence, and coordinated cyber-fraud prevention?

Companies Mentioned:

MITRE, NIST