Age assurance

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
Woman at desk using multiple screens

Why testing data is as important as training data for machine learning models

When developing machine learning systems for facial age estimation, the conversation often centres on the training data: how much you have, how diverse it is, how inclusive it is, and how well it represents your end users.  Not to mention, where the data comes from.  Intuitively, that focus makes sense. More data presumably leads to better models. But test data is just as important, and in some ways, even more critical for ensuring models perform effectively. Training data: more isn’t always better Common sense would suggest that for a machine learning model “the more data, the better.” And that’s

4 min read
An image of a young male holding a mobile phone. The accompanying text reads 'Texas App Store Accountability Act: United States'.

Texas App Store Accountability Act: what it means for age assurance worldwide

The State of Texas has passed a landmark law – the App Store Accountability Act – that places legal responsibility for age checking squarely on app store operators. Utah was the first state to enact this type of legislation, now followed by Texas. This new regulatory shift has far-reaching implications for digital safety, privacy and innovation around the world. As an age assurance provider, we believe it’s critical to explain the significance of this development, highlight the practical challenges it raises, and offer a path forward that protects both users and platforms. One of the main weaknesses of this

8 min read
Young girl looking at smartphone

Yoti responds to the Draft Statement of Strategic Priorities for online safety

Last week, the Department of Science, Innovation and Technology, published the final draft Strategic Priorities for online safety. We welcome the statement, which highlights the five areas the government believes should be prioritised for creating a safer online environment. These areas are: safety by design, transparency and accountability, agile regulation, inclusivity and resilience, and technology and innovation. These priorities will guide Ofcom as it enforces the Online Safety Act, ensuring platforms stay accountable and users are protected. We welcome this clear direction and commitment from the government to create safer online spaces. It’s positive that age assurance has been

9 min read

Building trust through age assurance

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 Read the report

1 min read