Behavioral Biometrics

Featurespace’s Behavioral Biometrics uses behavioral data on websites and mobile apps to detect anomalous activity to stop new fraud attacks and specific attacks such as Malware, MITM, Account Takeover and Phishing Attacks, all in real time using machine learning.

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Behavioral Biometrics provides an additional tool for fraud analysts, enabling them to visualise and compare a user's behavior in different sessions, spot anomalies and identify cases of account takeover, chargeback fraud, and bot and malware detection.

The system tracks a broad range of features including the way a user types on a keyboard, mouse movements or tap behavior, the time spent between text fields, and system features such as device, browser, operating system and timezone to produce a 'session fingerprint' and build a profile of 'normal' activity for each user. 

Crucially these profiles are so accurate that phishing and malware activity can be spotted even if the session is generated by a genuine customer.

    Key Features

     
    Self-learns from customer behavior in real time


    Automatically detects and stops new fraud types


    Easy to deploy using proven, scalable technology


    Non-intrusive technology

    A sample abnormal session, as presented in the ARIC UI

    Featurespace by numbers

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    Multi-Award Winning Fraud Prevention

    Our Customers

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