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The Biocatch Biometric Authentication Platform authenticates users transparently and continuously.  Using Cognitive Biometrics, BioCatch rapidly detects behavioral anomalies that indicate both account takeovers and the presence of malware, without creating any friction for end users. BioCatch allows organizations to reduce  fraud and dramatically increase security while slashing the need for secret questions and out-of-band authentication.

 

BioCatch analyzes over 500 parameters to automatically create a unique behavioral profile for each user that cannot be lost, stolen or imitated. From the moment of login and throughout the session, BioCatch protects the organization from account takeover, remote access attacks, malware, and post-login attacks. Since BioCatch identifies suspicious behaviors—even before users are profiled—it catches malware and new account setup fraud.  Creating a behavioral profile is based on the following parameteres:

 

 

 

 

 

 

 

 

 

 

 

 

 

Image: BioCatch Behavioral User Profile

 

Biometric Authentication Features

 

  • Transparent continuous authentication 

  • Invisible cognitive challenges 

  • Automatic user profiling creates a unique behavioral signature for account-holders  that cannot be imitated, lost or stolen – no active enrollment required.

  • Account takeover detection 

  • New account setup fraud detection 

  • New device/location verification 

  • Enhanced mobile authentication 

  • Secure user profiles

Behavioral Authentication

Mapping the good guys and the bad guys 

RESOURCES

HIGHLIGHTS

  • Biometric-grade authentication 

  • Continuous authentication

  • Invisible cognitive challenges 

  • Enhanced mobile authentication 

Consider Behavioral Biometrics
BioCatch User's Profile
  • Cognitive traits such as eye-hand coordination, applicative behavior patterns, usage preferences, device interaction patterns and responses to Invisible Cognitive Challenges™

 

  • Physiological factors such as left/right handedness, press-size, hand tremor, arm size and muscle usage

 

  • Contextual factors such as device ID, network, geolocation, transaction and navigation

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