Getting Down and Dirty with Behavioral Biometrics Technology

Aug. 29, 2019 | by BioCatch

Say goodbye to fraudsters, and hello to BioCatch, the industry leader in behavioral biometrics solutions. BioCatch uniquely analyzes more than 2,000 physical and cognitive behavioral attributes to address various use cases in the digital lifecycle. Typically used for account takeover fraud detection, identity proofing and risk-based authentication, behavioral biometrics has become a key component for driving secure and seamless online experiences.

A Bright Future for Behavioral Biometrics Technology

The promise of behavioral biometrics technology is well established, with an estimated projected CAGR of 24% for the next five years according to recent analyst reports. However, implementing behavioral biometrics is not always so straightforward because of its broad applicability and the fact that it is a risk-based modality. 

So this week, we want to get practical, to get down and dirty, on how enterprises can implement our technology to generate high rates of return, cut down on fraud losses and minimize the backend costs associated with false positives. 

Implementing the BioCatch System

The BioCatch system goes beyond a risk score, instead providing a host of system outputs to provide full visibility into what is actually happening in the digital channel. Having the added information makes it easier for fraud analysts and system operators to configure actions based on real-time behavioral information and adapt the technology to their environment. 

The table below explains the BioCatch system outputs, which get incorporated into backend systems. Security teams then configure actions and step-ups depending on the use case and the specific conditions present in a session. All the BioCatch system outputs are available in the Analyst Station for offline analysis and processing.

BioCatch System Output

Description

Risk Score

Range of 0-1000 that specifies the degree of risk inside the session; the higher the score, the higher the risk

Genuine/Risk Factors

Behavioral patterns observed during a session that are indicative of legitimate user behavior and/or fraudster behavior

Threat Indicators

Confirmed presence of specific cyberthreats such as remote access, bots, etc.

Top Contributors

The underlying genuine/risk factors that drove the risk score

 

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Topics: Behavioral Biometrics, Continuous Authentication