Traditional Fraud Detection Solutions Are Failing

BioCatch’s unparalleled approach to fraud detection goes beyond traditional tools to detect malware, robotic and aggregator activity, social engineering and other remote access threats, stopping cybercriminals in real-time.

Typical fraud detection solutions, such as device recognition, proxy detection and IP geo-location, are easy for fraudsters to circumvent. With malware infections and Remote Access Tool (RAT) attacks on the rise, cyber criminals are able to take over accounts and automate fraud despite traditional fraud detection measures. Using social engineering and technical subterfuge, fraudsters gain access to victims’ machines and steal credentials, trick users, intercept consumers online, or monitor and intercept consumer activity.

Today’s fraudsters are also patient and willing to leverage any opening to infect or attack. Savvy cybercriminals wait until after a user authenticates themselves and is logged in to commit fraud, bypassing traditional fraud prevention tools. By triggering malware well after it has been installed, a fraudster’s work can go undetected for an average of 170 days.

Fraud Detection for the Most Severe Cyberthreats

BioCatch’s Threat Detection Module offers a new level of fraud detection and prevention against malware, bots, aggregator and other Remote Access Trojans. Each of these forms of attack behave differently than a human being would, meaning they exhibit their own unique behavioral patterns that BioCatch’s fraud detection technology can identify. Many of today's RATs are human as well, using social engineering to take over sessions by tricking victims into logging into their own accounts. BioCatch’s patented technology analyzes hundreds of human and non-human behavioral parameters every second to detect behavioral anomalies in a session and prevent advanced fraud tactics in real-time.

Here’s how our fraud detection technology works:

Create the User Profile: The BioCatch system collects and analyzes over 2000 traits including hand-eye coordination, pressure, hand tremors, navigation, scrolling and other finger movements, etc. To create the user profile, the system detects the parameters that are most strongly associated with the user meaning that, for those parameters, the user does not behave like the rest of the population. Each person’s profile is made up of different unique parameters and can be linked across devices.

Produce Actionable Risk Score: The system looks for different kinds of fraudulent activity – criminal behavior, malware, bots, RATs, aggregators, etc. – and analyzes the behavior in a session to compare against the user’s behavioral profile. A high risk score generates an alert in real-time.

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