Uses e-KYC technology and biometric identity verification to enhance security and proactively prevent fraud through real-time accuracy verification.
Uses e-KYC technology and biometric identity verification to enhance security and proactively prevent fraud through real-time accuracy verification.
To mitigate threats from image misuse and deepfake technologies, facial recognition compares the user’s live facial data with certified databases from government agencies or trusted organizations to accurately verify that the individual is the same person. This process enhances security for high-value transactions and remote account opening in compliance with regulatory standards. In addition to improving security, it reduces manual verification steps, increases processing speed, and delivers a more convenient and modern user experience.
Liveness Detection
It serves as the first line of defense against spoofing attacks, and is categorized into two main approaches.
1.1 Passive Liveness
Users simply look at the camera, while the AI system analyzes facial depth, lighting and shadows, and skin texture details to distinguish a real human face from images displayed on paper or a mobile screen.
1.2 Active Liveness
Users are required to follow challenge-response instructions—such as blinking, nodding, turning left or right, or moving their mouth—to verify that a real human is interacting with the system in real time.
Face Recognition / Face Matching
Once liveness is successfully verified, the system matches the facial image against trusted and authorized databases.
2.1 1:1 Matching (Verification)
Compare the current facial image with the photo stored on the national ID card (via Dip Chip) or with the image previously captured during account opening to verify that it is the same individual.
2.1 1:N Matching (Identification)
Compare the user’s facial image against large-scale databases to detect duplicate identities under different names or to determine whether the individual appears on the organization’s blacklist.
