BioCatch, which prevents financial crime by recognizing patterns in human behavior, announced the launch of the latest edition of its behavior-based scam-fighting tool: BioCatch Scams360^™. For the first time ever, financial institutions will now be able to consistently identify and prevent the majority of authorized push payment (APP) fraud in real time. APP fraud relies on the psychological manipulation of victims to willingly transfer their money away to financial criminals. Banks deploying BioCatch's latest scam-detection solution, Scams360, provide their customers with unprecedented, purpose-built protection against romance, investment, business-email-compromise, purchase, impersonation, and other social engineering scams that continue to proliferate in both scale and sophistication in every country in the world.

"Already, we're seeing a 50% improvement in our ability to detect non-impersonation scams," BioCatch Chief Product Officer Ayelet Eliezer said. "Scams360's current alert rate – the percentage of total transactions requiring banks to intervene – is also best-in-class, helping banks deploying Scams360 to keep their operational costs low while stopping more scams in real time, before any money leaves the would-be victim's account."

The Global Anti-Scam Alliance estimates scams now account for more than $1 trillion in consumer losses every year. And that total continues to grow. The GenAI era has revolutionized the creation, execution, reach, targeting, and refinement of social engineering scams and promises further – and potentially exponential – improvement of all those scam metrics in the future.

Legacy defenses – often based on transaction data or device and network intelligence – fail to detect modern scams that manipulate their victims. In most cases, those social engineering scam victims willingly authorize their scam payments, eluding the detection of traditional fraud systems. Scams360 leverages BioCatch's market-leading behavioral and device intelligence to arm financial institutions with the contextual understanding needed to distinguish genuine user intent from signs of manipulation. Examples might include the speed of the user's typing, how quickly they respond to prompts, unusual mouse behavior, hesitation, erratic inputting of information, mouse-doodling, prolonged periods of inactivity, the presence of malicious apps, and/or an active phone call during an online banking session. BioCatch tracks as many as 3,000 of these different behavioral and device-related datapoints to distinguish the legitimate from the criminal.