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As end users increasingly rely on digital platforms for online transactions, organizations need strong security controls to protect these interactions. However, traditional authentication practices can add complexity to the login process and may not provide enough protection. Appgate’s behavioral biometrics service extends the company’s market-leading Zero Trust security portfolio by leveraging machine learning to observe and learn how end users interact with their keyboard and mouse during a given online session. The service is designed to identify anomalies and automatically adjust authentication strength to protect users and information.

By learning how each user interacts with a digital platform, the service can identify malicious activity with a high level of accuracy, while also giving more confidence in genuine sessions, reducing the need for more intrusive forms of authentication. Appgate’s behavioral biometrics service allows organizations to set parameters for risk scoring and easily configure and adjust how they respond to risky logins. Depending on the risk score for a given session, the customer authentication system can prompt action such as step-up authentication.

Appgate’s behavioral biometrics service is designed to:

• Enhance customer protection with real-time decision-making: Organizations can qualify the risk of any given login according to how it fits with normal user behavior and use automated responses to protect users and data
• Provide a seamless user experience: The service is invisible to the end user, providing robust protection without interfering with or slowing down the customer’s online interaction
• Support unique organizational requirements: The service is API compatible and affordable, allowing organizations to easily implement and customize it to meet their specific needs
• Deliver real-time risk scores: Appgate’s behavioral biometrics service provides information on potentially compromised sessions, enabling organizations to respond quickly