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Acuant 3 Face Options Overview
Facial Recognition Match can offer robust fraud prevention, but it must include a liveness test. A liveness test ensures that there is a real person present instead of a photo, video playback or even a mask. Acuant has 3 Face options: Standard, Passive and Enhance.
Acuant Face Standard
It matches facial biometrics using The face picture from an identity document with a selfie image. Acuant Face is paired with a device liveness detection blink test for one seamless process. Results are achieved in seconds and help prevent fraudsters from using static images.
Acuant Face Passive
It is a containerized algorithm in
Acuant SaaS for detecting whether a live person is on the other end of a transaction. It uses a single facial shot that is run through the engines within the container.
There are three main parts to the algorithm face detection, quality engine and liveness engine. The face detects engine uses 68 focal points to make sure there is a person and also rejects images of multiple persons. The quality engine gauges facial position for good analysis measuring roll, yaw, pitch and angle of the face.
Lastly, the liveness engine analyzes presentation attack detection recognizing a live face and preventing flat photos, videos, masks and pictures of a picture.
Acuant Face Enhanced
It is designed for high-risk environments, for those seeking utmost certainty and fraud prevention.
High-performance facial recognition matching paired with sever based enhanced liveness detection. Prevents presentation attacks from printed images, masks recorded video or synthetic video from passing the liveness check.
The ability for replay detection where a similar face presented in quick velocity triggers an alert for possible fraudulent activity
Why a liveness test is critical?
Application of liveness test in face recognition
Employing a liveness test is critical in preventing spoofs, known as Presentation Attacks, such as photos from passing as the real person during facial recognition matching. Common Presentation Attacks include printed photographs, cut-out photos, screen displays, video replay and masks. Until now most systems used some form of active liveness, such as blinking, smiling or moving a head back and forth to detect liveness, assuming that a photo cannot mimic the actions of a live person. However, active liveness tests create friction, take time, and inform fraudsters of the steps necessary to break the system. In fact, many are now easily broken.
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Passive liveness on the other hand, eliminates these concerns, requiring no additional steps from the user.
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Customer Onboarding
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Verification
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Re-Verification
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KBA (Knowledge Based Authentication) Replacement
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Secure Password Reset or Password Replacement
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Multi-Factor Authentication (MFA)
How it really works?
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User takes a selfie
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Selfie image is used by the facial recognition system to determine a match
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The same selfie image is used for the liveness check
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Proprietary algorithms analyze the image for liveness
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The system returns a liveness score
More points for you to use this
Face Recognition Technology
KYC & AML compliant
Legal and effective to prevent identity theft and fraud.
Easy Integration
All data is encrypted, nothing is stored on devices or cloud to protect PII
Secure
All data is encrypted, nothing is stored on devices or cloud to protect PII
Multi-platform
Mobile/Web/Cloud solutions for any device & operating system
Supported Documents
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Passports / ePassports
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Passport Cards
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Driver's Licenses
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Visas
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Military Identification
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Voter Identification
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Government
(PIV, CAC, TWIC) -
Alien Registration
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Border Crossing Cards