Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Article originally published in Green Sheet, June 15, 2026 As artificial intelligence rapidly reshapes the fraud landscape, financial institutions are under growing pressure to detect and stop increasingly sophisticated threats in real time. From AI-driven social engineering scams to evolving mule-account activity and instant payment fraud, traditional approaches to fraud prevention are being tested like never before.

The June arrests of Chilean bank workers accused of ties to an international criminal organization has again underscored the need for anti-money laundering (AML) detection to embrace real-time transaction intelligence. Authorities allege that a rogue Santander Chile employee was a key player in an $85-million USD money-laundering operation that channelled funds through accounts at almost every major bank in the country.

Originally published in Vancouver Tech Journal, June 2, 2026. Bijan Sanii is CEO and founder at INETCO It may seem reassuring that JPMorganChase, the largest U.S. bank, is among the 12 launch partners involved in Anthropic’s Project Glasswing. But given the stark cybersecurity warning the initiative represents, including a single financial institution is nowhere near enough.

Picture this: Your payments team starts the week with what looks like a routine performance review. Authorization rates are slightly off. A handful of merchants are seeing more retries than usual. Declines are climbing in one segment of the portfolio. But nothing looks catastrophic…yet. Then the warning signs start stacking up. An AI-driven BIN attack has quietly pushed enumeration activity higher. A few merchants are generating abnormal dispute patterns.