Building trust through age assurance

profile picture Rachael Trotman 1 min read

Governments around the world are increasingly prioritising online safety and age regulations, with new laws emerging across multiple countries.

This report explores the growing demand for privacy-preserving age assurance and how businesses are adapting to meet regulatory requirements. Using proprietary data, our latest report explores:

  • The growing demand for privacy-preserving age assurance
  • How businesses are adapting to meet regulatory requirements
  • Key trends in age assurance
  • How Yoti’s solutions are protecting young people, safeguarding privacy, and helping businesses implement robust, trusted and effective age checks

Keep reading

How accurate can facial age estimation get?

Facial age estimation using machine learning has advanced significantly in recent years. But, a common and fair question still arises: How accurate can it really be? Can a system look at your face and accurately guess your age, especially when humans often get it wrong? The short answer is that it’s very accurate – but not perfect. We explain why.   The myth of 100% accuracy It’s important to set realistic expectations. No facial age estimation model can achieve 100% accuracy across all ages.  Human aging is highly individual and shaped by many external factors, especially as we get

6 min read
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.

3 min read
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

6 min read