Verifying age with email address age estimation

profile picture Sofi Summers 5 min read
Illustration of email based age estimation to determine if user is over 18

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Woman presenting a 2d image trying to perform a presentation attack

Why early detection is critical in stopping deepfake attacks

Digital identity and age verification are becoming integral parts of customer onboarding and access management, allowing customers to get up and running on your platform fast. However as customer verification tools become more advanced, so too are fraudsters seeking to spoof systems by impersonating someone, appearing older than they really are or passing as a real person when they’re not. Deepfake attacks, which can mimic a person’s face, voice or mannerisms, pose a serious threat to any business using biometric customer verification. In this blog, we explore why detecting deepfakes early is essential for maintaining trust, security and regulatory

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An image of a woman trying to buy a bottle of alcohol at a supermarket self-checkout terminal.

"We need an army of Elliots" - why it’s bonkers we’re not using facial age estimation to sell alcohol

Let’s just get this out there: humans are not great at guessing ages. Don’t just take our word for it. Studies have proven this to be the case. Most of us reckon we can largely say if someone is under 25 using the Challenge 25 technique but when put to the test, the truth comes out: retailers do let some under 18s buy alcohol. Not always and not everyone, but some people are incorrectly estimated to be older than they really are. Let’s be honest, this is not ideal. Now, to be fair, not all humans are created equal.

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Woman using facial age estimation technology at a self-checkout

Why facial age estimation, the most accurate age checking tool, shouldn’t be left on the sidelines

Many of us have been there: standing at a self-checkout, scanning our shopping, only to hit a roadblock when the till flags an age-restricted item like a bottle of wine or a pack of beer. With age verification accounting for between 40 – 50% of interventions at self-checkouts, it significantly disrupts and slows down the checkout experience. We wait for a retail worker to approve the sale. The retail worker does a visual estimation of our age – they look at our face and guess whether we’re old enough to buy the item. Most retailers follow the Challenge 25

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