Digital identity verification is especially important these days because many transactions take place remotely, and identity theft and cyberattacks have increased dramatically during the global pandemic. PresentID provides a seamless remote user identity verification solution through the combination of in-house developed technologies including ID card OCR + dynamic face liveness detection + voice verification + eye tracking to ensure the highest levels of accuracy in identity verification and fraud detection.

One of the key elements of the online identity verification process is dynamic face liveness detection. PresentID dynamic face liveness detection can detect whether the person in front of the video is real or fake. It can tell if the user is physically present. It prevents masks, photos or video deepfakes from fooling the system. We use convolutional neural network (CNN) deep learning algorithms to prevent fraud. We use a combination of biometric authentication algorithms such as face, voice, eye, head detection and tracking to have the highest accuracy to prevent fraud.

To maintain authentication at an optimal level of security, in the third part, we ask the user to read a randomly displayed message. By comparing the latest voice to the new, our platform can clearly confirm whether the person is exactly the right user.

Biometric sign in