How behavioral biometrics, dynamics of interaction could prevent online bank fraud

Behavioral biometrics technology developed by BioCatch to prevent online bank fraud has been featured by CNN International, with CEO Howard Edelstein and COO Gadi Mazor explaining how coupling learned behavior with artificial intelligence and machine learning can instantly identify the user.

The technology developed by BioCatch outlines the user’s online habits to build a profile. Whether it is mouse movement, pressure put on the device, phone angle or agility in clicking a link, the technology can identify who is behind the device; the legitimate user or a fraudster.

In just ten years, analysis of digital idiosyncrasies has expanded from click, swipe and typing analysis into advanced technology that leverages neuroscience and cognitive analysis of human-device interaction, BioCatch writes in a blog post. The innovation behind behavioral biometric profiling for fraud prevention consists of psychology and social engineering tactics.

The technology can be applied to the new account opening process to identify fraud based on three use cases: application fluency, low data familiarity, and expert behavior. Familiarity with the new account opening process, personal data and computer skills displayed could reveal if the technology is dealing with a legitimate user or a criminal using compromised or synthetic identities, fragmented typing patterns or advanced technical skills.

There are hundreds of risk indicators confirming behavioral differences, but according to company research, segmented typing alone increases fraud risk four times. As many as 44 percent of confirmed new account opening fraud cases occurred because of this risk indicator, confirming the importance of behavioral biometrics in fraud prevention, BioCatch argues, because they cannot be spoofed.

Article Topics

artificial intelligence  |  behavioral biometrics  |  BioCatch  |  biometrics  |  fraud prevention  |  identity verification  |  machine learning