A UK scale-up this week unveiled an industry-first approach to identity verification: asking users to turn their heads.
Onfido, an Oxford University spin-out, launched the software amid surging identity fraud.
Similar developments have been observed around the world.
These trends have triggereda boom in the ID verification market.
Increasingly sophisticated fraudsters are also forcing providers to develop more advanced detection methods.
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Onfidogave TNW an exclusive demo of their new entry to the field: a head-turn capture experience dubbed Motion.
This was the sweet spot.
The uptake of biometric onboarding has been curbed by two key problems.
A little bit of friction can reassure customers but too much scares them away.
Motion attempts to resolve both these issues.
Onfido says the systems false rejection and acceptance rates are under 0.1%.
The verification speed, meanwhile, is 10 seconds or under for 95% of users.
In our demo, the process felt swift and seamless.
After sharing a photo ID, the user is directed to provide their facial biometrics via a smartphone.
As they move, the system provides feedback to ensure correct alignment.
Moments later, the app delivers its decision: clear.
The video is sequenced into multiple frames, which are then separated into different sub-components.
Next, a suite ofdeep learningnetworks analyzes both the individual parts and the video in its entirety.
The networks detect patterns within the image.
In facial recognition, these patterns range from the shape of a nose to the colors of the eyes.
Each web connection builds a representation of the input image.
All the information is then aggregated into a single score.
Onfidos confidence in Motion derives, in part, from an unusual company division: a fraud creation unit.
In total, they created more than 1000,000 different examples of fraud which were used to train thealgorithm.
Each case was tested on the system.
This generated a feedback loop of finding issues, resolving them, and improving the mechanism.
Motion also had to work on a diverse range of users.
Despite stereotypes about the victims, fraud affects most demographicsfairly evenly.
To ensure the system serves them, Onfido deployed diverse training datasets and extensive testing.
The company says this reduced algorithmic biases and false rejections across all geographical regions.
Plotting fraud
Sabathe demonstrated how Motion works when a fraudster uses a mask.
When the system captures his face, it extracts information from the image.
It then represents the findings as coordinates on a 3D chart.
When Sabathe puts the mask on, the system plots the image on the fraud cluster.
As soon as he takes it off, the point enters the genuine cluster.
Onfidos head-turn technique resembles onerevealed last month by Metaphysic.ai, a startup behind the viralTom Cruise deepfakes.
Researchers at the company discovered that a sideways glance could expose deepfake video callers.
Di Nola notes that such synthetic media attacks remain rare for now.
Its definitely not the most common pop in of attack that we see in production, she said.
But it is an area that we are aware of and that we are investing in.
In the field of identity fraud, both attacks and defenses will continue to rapidly evolve.
Story byThomas Macaulay
Thomas is the managing editor of TNW.
He leads our coverage of European tech and oversees our talented team of writers.
Away from work, he e(show all)Thomas is the managing editor of TNW.
He leads our coverage of European tech and oversees our talented team of writers.
Away from work, he enjoys playing chess (badly) and the guitar (even worse).
