Behavioral biometrics is an advanced approach to identity verification and fraud prevention. It analyzes unique user behavior, like the user's typing patterns, mouse movement, navigation menu flow, and their touchscreen interactions for natural and consistent behavior. By continuously monitoring these traits passively, organizations can add an additional layer of authentication in real time without adding friction, thus providing a more seamless, secure user experience while still effectively enhancing their ability to detect fraud.
Use case / examples of behavioral biometrics
Fraud detection: Detecting a potential account takeover by identifying behavioral anomalies that differ from a user's historical activity profile. This might include inconsistent typing speed during login, suggesting either that a bot is entering the credentials or that they are being cut and pasted in, or identifying that a login is coming from a device or location inconsistent with the user's typical behavior.
Secure authentication: Analyzing biometric and behavioral signals, such as keystroke dynamics or cursor movements, to validate a user's identity in real time. This would include fingerprint or facial recognition.
