Passive Liveness Detection

A single selfie to decrease abandonment

The longer it takes a customer to complete verification, the greater the likelihood of abandonment. At the same time, liveness detection is a crucial step to determines if the person being verified is a real human being – and standard active liveness technology is being undermined by deep fakes.

greenID’s breakthrough Passive Liveness detection technology provides the ultimate solution, being performed in the same instance as the face match selfie is captured. The process is completely frictionless for your customer, as they are not required to undertake additional steps or gestures – increasing speed and decreasing abandonment rates.

While our Passive Liveness tool leverages deep neural networks and proprietary algorithms to deliver high accuracy, its background processing makes it imperceptible to fraudsters.

Customer drop-off can exceed more than 50% at the active liveness check during the onboarding process

Performance with Passive Liveness is at least 10x faster, and is more effective and accurate than active liveness

Single-image passive liveness detection with proven high accuracy performance

Running in the background of the facial verification process makes it more difficult to spoof

Needs only one frame to tell if the person is real and alive, eliminating the requirement for additional user actions or gestures

Achieved through combination of unique deep neural network machine learning and calibrated real-world data analytics

greenID is the first passive liveness detection technology to be iBeta level 1 and 2 ISO 30107-3 compliant

Achieved perfect score in detecting all spoofs and identifying all real users (bona fide) correctly in ISO/IEC 30107-3 Presentation Attack Detection (PAD) test

Gold medal winner Facebook Deepfake Detection Challenge

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