Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The US Federal Bureau of Investigation (FBI) warns that Americans lost just under $900 million to AI-powered scams in 2025, Malwarebytes reports. Total reported losses to scams last year reached nearly $21 billion, a 26% increase from 2024. The researchers note that the true losses are likely much higher, since many attacks go unreported. “The main drivers behind the rise in AI-powered scams are voice cloning, deepfake images and videos, and AI‑generated scripts,” Malwarebytes says.

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.

When the weather starts to get warmer, it is a sign that summer time is around the corner. But just as the weather heats up and travel plans get booked, scammers capitalize on the season by performing nefarious schemes to separate victims from their money and other valuables. Recent McAfee research found that more than one in three Americans have experienced a travel-related cyberthreat, with 41% of those affected losing money, often costing victims over $500.

Brand impersonation account takeover (ATO) happens when attackers use fake brand assets to expose customers, harvest credentials, and attempt access on the legitimate site. The impersonation stage happens outside the enterprise’s login environment, but the ATO risk appears when stolen credentials, attacker devices, or exposed users reach the legitimate login environment. That distinction matters because brand impersonation and account takeover are often handled as separate problems.

Brand impersonation account takeover (ATO) happens when attackers use fake brand assets to expose customers, harvest credentials, and attempt access on the legitimate site. The impersonation stage happens outside the enterprise’s login environment, but the ATO risk appears when stolen credentials, attacker devices, or exposed users reach the legitimate login environment. That distinction matters because brand impersonation and account takeover are often handled as separate problems.

AI-generated fraud schemes are now the dominant type of fraud, according to a new report from AU10TIX. AI-assisted forgeries overtook physical manipulation for the first time, as these tools allow attackers to fool humans and technology with very little manual effort.

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.