truuth Liveness

truuth Liveness is a service that verifies a user is a human and present during the interaction. 


While facial recognition is well suited for mobile applications, it is vulnerable to attempts by fraudsters to intentionally fool biometric security measures by presenting non-live biometric data. For example, a fraudster might use a printed or digital photograph, video, or mask to either impersonate a targeted victim or to assert a false identity. This is also called a “presentation attack” or a “spoof.” 


As a result, it’s essential to apply robust liveness detection when using facial recognition for mobile applications, particularly where personal data is accessible or value transfers are possible.

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Dynamic liveness score can be used to define customer authentication journey

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Level 3 face liveness measures skin tone and complexion to detect 3D mask attacks

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Enterprises can add liveness service to existing authentication solutions

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Level 2 face liveness measures key face landmark ratios at different proximity to the device

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Active voice liveness prompts users to read randomised statements pushed to their screen

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Level 1 face liveness tracks complex and microscopic eye movements

How does it work?

Step 1

We track multiple metrics of eye movement including blinking and microscopic iris movement during a face scan.

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Step 2

We analyse changes in facial landmark ratios as the user is guided to move device relative to the face.

Step 3


We analyse face complexion and if the confidence level is below defined threshold, the user is requested to read randomised statements projected on screen.

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Top Use Cases

Liveness lets you...

This matters because...

Why trUUth Liveness?

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Improved Security


truuth Liveness undertakes multiple tests to mitigate the risk from fraudulent actors.  Presentation attacks are increasing in both volume and complexity. Fraudulent actors are using elaborate deep fakes and synthetic identities to fool organisations into accepting fraudulent identities, which can then lead to cascading impacts such as credit card fraud.


truuth Liveness includes both ‘active’ and ‘passive’ components to make it more difficult for fraudsters to predict how liveness is determined.

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Enhanced User Experience


truuth Liveness typically takes less than 3 seconds to complete. Liveness results are combined with other contextual data (e.g. device identifiers, authentication history, location, purchase type) to determine the risk level and only prompts the user for face or voice liveness if the risk level requires it.

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Reduction in Total Cost of Ownership


truuth Liveness reduces the cost of onboarding a customer by enabling fully digital onboarding while mitigating risk of identity fraud.


truuth Liveness can also be added to authentication services to reduce the cost of verifying user identity and complying with regulations such as Anti-Money Laundering (AML) and Counter-Terrorism Financing (CTF).