1 second response time
Our streamlined user experience enables users to authenticate themselves instantly with a simple selfie.
User-centered design
An easy, secure, and safe way for your users to confirm they are who they say they are. No unnecessary actions or extra information is required.
Secure authentication
Prevent unauthorized access or account takeover with liveness detection, fraud checks, and anti-spoofing capabilities.
Seamless identity assurance
Combine biometric authentication with our identity verification solution to provide an added layer of protection.
Ensure hassle-free authentication for your users
Mobius ( Powered by Veriff )’s Biometric Authentication solution uses AI and facial biometric analysis to swiftly and securely authenticate users, granting instant access to products and services. This fast and fully automated process can be integrated into any stage of the user journey such as account access, high-risk activities, or account recovery.
How Biometric Authentication Works
Mobius ( Powered by Veriff )’s biometric authentication confirms that a returning user is who they claim to be. Users can authenticate on any device and platform of their choice, as Veriff supports iOS, Android, mobile web, and web SDK or API.
Once the user’s selfie has been enrolled, either from an identity verification session or by taking a biometric enrolment selfie, the user can simply use their face to authenticate themselves.
User selfie
The user simply takes a quick selfie, replacing cumbersome, outdated, and less secure authentication methods such as passwords, shared secrets, or one-time passcodes.
Biometric analysis
Get a decision
Provides a clear and actionable result with detailed explanations of the events that occurred during the authentication process, empowering you to make an informed final decision 一 whether to allow, deny, or request additional verification.
Passive liveness detection
Mobius ( Powered by Veriff ) validates that the user is real and present during the authentication session without requiring the end user to complete any
additional or unnatural actions. Our liveness models are capable of
detecting spoof attempts such as presentation attacks using masks or
presented screens, or an Al-generated selfie.
Face matching
Artificial intelligence analyzes and compares the biometric template
from the authentication session to the stored biometric template from
the enrolment session to determine if it's the same user or not
Adaptive technology
Al models adapt to evolving fraud patterns, providing proactive
protection against emerging threats. Liveness detection methods to
identify synthetic and Al-generated media, face blocklisting, device
fingerprinting, and dynamic fraud checks creates a robust security
approach without impacting user experience.
Optional background video
Optional background video recording, enables us to conduct
advanced fraud prevention checks with minimal input from your users.
Account takeover mitigation
Prevent fraudsters from unauthorized access to your users' accounts
by confirming it is the genuine account holder through a secure selfie
authentication method.
Step-up authentication
Dynamically adjust the level of authentication required based on the
associated risk. Seamlessly integrate biometric authentication as a
step-up authentication method to authorize high-value transactions or
high-risk actions.
Account recovery
Selfie-based biometric authentication provides stronger assurance
that the user requesting the account recovery is the genuine account
holder.
Network and device analytics
In addition to selfie checks, Veriff automatically analyzes over 30 risk
signals such as behavioral, network, and device analytics to combat
evolving fraud typologies.
User-centred authentication
Our fully automated solution provides a response in under a second,
enabling your users to authenticate themselves instantly with a simple
selfie and eliminating the burden of remembering and managing
complex passwords. Users do not need to leave the journey to receive
a one-time passcode or use third-party authenticator apps.
Assisted Image Capture
Mobius ( Powered by Veriff ) uses machine-learning technology to assess client sessions in
real-time and guide users during the photo capture process. Clear and
actionable user feedback due to poor lighting, glare, cropped ID, and
obstructed facial images are just a few examples of how Assisted
Image Capture pre-validates images and boosts first-time pass rates.
Cross-platform
Users can complete authentication on any device and platform of their
choice that has a user-facing camera. Veriff supports iOS, AndroidTM
mobile web, and web SDK or API.
Flexible enrolment
Depending on the use case or user journey, users can be enrolled
either via Mobius ( Powered by Veriff )'s Identity Verification solution or simply taking an
enrolment selfie. The enrolled selfie is stored as a biometric template
for analyzing future authentication sessions.
Integrated with IDV
Combine Mobius ( Powered by Veriff )'s Biometric Authentication with Veriff's Identity
Verification solution to add a layer of security and assurance that the
user is bound to a verified identity document. Use the selfie from the
IDV enrolment for future authentication sessions.
Explainable decision making
Mobius ( Powered by Veriff ) sends you a clear and actionable result with detailed
explanations of the events that occurred during the authentication
process, enabling you to make an informed final decision to allow,
deny, or request additional authentication from your users.
Fully automated
Fully automated facial analysis technology delivers 1 second response
time, enabling users to authenticate themselves instantly with a simple
selfie.
