Onboard good customers in seconds, not days with biometric FaceMatch technology.
It is not enough just to know a document is real. You need to be confident that the person presenting the document is the real owner. For that, we recommend you use our sophisticated face matching algorithm to compare the portrait picture on the document with the face of the customer.
Deter fraudsters with an added layer of security by using document-to-selfie comparisons which means a person needs to be digitally present to set up an account with you.
There’s no trade-off between getting customers onboard quickly and compliantly. Our technology needs minimal user interaction and works to your risk-based approach.
Instant validation of facial features between a printed document and a live face image from a smartphone, tablet or webcam.
FaceMatch provides instant validation of facial features between a printed document face (e.g. a passport photo) and a live face image captured by a smartphone, tablet or webcam. After taking a photo of an identity document, a user can further authenticate themselves by placing their face in the viewfinder of the forward-facing camera on their device.
Identifying against a set of 68 facial landmarks for each image, FaceMatch uses these to extract the facial features and compare against the document to produce a reliable judgement of how similar the two faces are and confirm that a genuine presence is being presented.
Modern passports, and an expanding number of other identification documents, contain a chip called NFC which holds biometric data, as well as a copy of the data on the visible document. Our document verification technology can access this chip and use the data within. We can compare the image on the visual document to that on the chip, which should be identical. The portrait image on the chip is checked against the document, and both are checked against the selfie, for an extra layer of verification.
Are you an existing customer? Talk to our customer support team.
Active liveness requires an action from the user. This can be smiling, frowning or moving your face right or left.
Passive liveness does not require an action from the user. It detects a face and movements from a single frame.
The analysis may return a refer result if we are unable to authenticate the action. The most common reasons for this are low quality or fuzzy images, high glare or shadowing.
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