Face Match & Liveness Detection API

Face match and liveness detection is the critical biometric layer in modern digital onboarding. As remote customer acquisition becomes the norm, businesses face increasing threats from deepfake attacks, photo replay fraud, mask-based impersonation, and synthetic identity schemes. digiverification 's Face Match & Liveness Detection API uses advanced AI models to verify that the person presenting themselves is who they claim to be.

Our Face Match API compares a live selfie or photograph against a reference image — typically from an identity document like Aadhaar, PAN, passport, or driving license. The AI engine analyzes facial geometry, proportions, and unique biometric features to generate a match confidence score. High-confidence matches confirm identity; low scores trigger additional verification steps.

Liveness Detection goes beyond face matching by confirming that the person is physically present and not using a photograph, video replay, or deepfake to impersonate someone. Our passive liveness detection analyzes subtle facial cues — skin texture, light reflection, micro-movements, depth perception, and 3D face geometry — without requiring the user to perform specific actions like blinking or head turning. This provides a frictionless user experience while maintaining high security.

Active liveness detection is also available for higher-security scenarios. Users are prompted to perform random actions like smiling, blinking, or turning their head. The AI system verifies these actions in real-time, making it virtually impossible to fool with pre-recorded videos or static images.

For video KYC mandated by RBI, our API provides the biometric verification layer that enables fully compliant remote KYC workflows. Combined with document verification and OTP authentication, businesses can complete the entire KYC process remotely with the same assurance as in-person verification.

Our face match engine achieves over 99% accuracy on standard benchmarks, with false acceptance rates below 0.01%. The API handles varying lighting conditions, angles, facial accessories (glasses, masks), and age differences between the reference photo and live image.

The API is used across fintech, banking, insurance, telecom, and government applications for onboarding, transaction authentication, and continuous verification.