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.
Providing proof of life remotely is very easy with biometric technology. It helps build user trust and speed up authentication. It also prevents users from remembering multiple passwords and switching between devices. Increasingly, governments and organizations around the world are choosing biometric technology to combat identity fraud to protect access and data, reduce costs, and improve the overall user experience.
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.
We provide smart solutions for detecting, counting, and analyzing the video. We can detect and count the faces, people, cars, bicycles, etc. We do this automatically using Artificial intelligence and machine learning models.
PresentID dynamic face liveness detection can detect whether the person in front of the video is real or fake.
The PresentID PhotoID matching (face matching) API evaluates whether two faces belong to the same person or not.
PresentID selfie matching compares selfie image with liveness and shows whether or not they belong to the same person.
PresentID profile pic matching compares profile picture with liveness and shows whether or not they belong to the same person. (Liveness = liveness detection)
PresentID MRZ scanner API locates and recognizes machine readable zone/travel documents (MRZ/MRTD) from single input image.
Establishing trusted identities consists of registering the identity and verifying its authenticity. We provide the workflow process for identity registration and for applicant biometric verifier registration.
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Selected as one of the top founders by 50intech in TechCrunch 2019.
Featured in panorama of French fintech startups by blackfin and France fintech.
Selected as a finalist in the "best use of AI in financial technologies" category at ifta2020.
NVIDIA has released its female-led AI startups in the EMEA region and we are proud to be part of the NVIDIA cybersecurity ecosystem.