Banks tighten consumer scam controls amid AI threats

Leading global banks and payments-security experts outlined new consumer scam controls during a recent online webinar hosted with Outseer. Panelists warned that scam-as-a-service and AI-powered attacks are increasing the scale and sophistication of fraud, and cited an estimate that financial institution losses could reach $55.3 billion by 2030.

Outseer presented consumer survey results from more than 15 markets mapping the scams that worry customers most and what they expect from banks. The research found many consumers want faster, clearer alerts about suspected scams, stronger in-the-moment transaction checks, and simpler ways to report and reverse fraudulent payments.

Outseer Principal Product Manager Martyn Higson and moderator Sharon Kimathi led the session. Panelists described a five-stage framework for intervention-pre-attack, consumer compromise, transaction, receipt and post-attack-and identified which controls apply at each stage and where timely bank action can reduce losses.

Speakers said banks are combining technical detection with behavioural measures. Controls discussed included advanced transaction monitoring, real-time behavioural analytics, authentication that detects unusual account use without adding friction, targeted customer prompts at critical moments, and streamlined post-attack remediation processes.

Panelists outlined how fraud operations have professionalized into service platforms that sell tools and techniques to less-skilled criminals. They described generative AI creating convincing fake messages, deepfakes and spoofed identities at scale and noted that social-engineering attacks increasingly target human vulnerability rather than system flaws.

The session examined cross-market differences and noted variation by region and regulatory context. The discussion emphasized end-to-end approaches that pair machine-learning detection with tailored customer interventions and clearer remediation. Organizers also promoted sharing anonymized scam patterns and control outcomes across institutions to improve collective detection and response.