Age verification: the solution to buying age-restricted products in supermarkets

profile picture Yoti 6 min read
Woman using Yoti's age estimation solution at the self checkout in a supermarket

Supermarkets as we know them today are vastly different from the ones we were used to twenty years ago. Doing the weekly shop is quicker and easier thanks to supermarkets implementing technological solutions like scan-as-you-shop and self-checkout terminals. Shoppers are becoming increasingly independent, but how can supermarkets assure that their customers are old enough to buy age-restricted products with minimal staff intervention and manual ID checks?

Across the UK, supermarkets are looking to adopt new ways to check that their customers are old enough to buy age-restricted products, including alcohol, knives, tobacco and vapes. By embedding our leading age verification technology into their self-checkout terminals, supermarkets could reduce the amount of time customers spend scanning and paying for their shopping.

 

Streamline your age checks

Facial age estimation

Our facial age estimation technology accurately estimates a person’s age from a live facial image, offering a secure and private way to prove age. As soon as the customer’s age is estimated, the facial image is deleted. Customers do not need to register to use it, provide any personal details or share any identity documents. It is not facial recognition because it does not uniquely identify anyone. 

How it works

  1. Customers simply look at the camera on the self-checkout and have their age estimated in seconds. 
  2. If the result of the estimation is above the threshold set by the supermarket, then the customer can continue to pay for their items. 
  3. If the result of the estimation is below the threshold, the customer needs to prove their age another way – for example, by using their Yoti Digital ID or with a physical ID document.

The technology is usually used with safety buffers. So in practical terms, if your business needs to check if someone is over 18, you could set an age threshold of 25 – meaning everyone needs to be estimated as 25 or over. The technology will then estimate if someone is above or below the age of 25 – in line with the UK’s Challenge 25 policy. 

 

Digital ID

A Digital ID could allow shoppers to prove they’re over a business’ age policy using their phone. This requires downloading a free Digital ID (such as Yoti, Post Office EasyID or Lloyds Bank Smart ID) and verifying themselves with an ID document and a biometric selfie. They just need to do this once and then can use their Digital ID for life.

How it works

  1. Customers scan the QR code on the self-checkout screen using their Digital ID app. 
  2. They consent to sharing a verified ‘Over Age’ credential in their Digital ID app, which will tell the business they’re over the required threshold.

The UK Government has confirmed that people will soon be able to use digital IDs to prove their age when buying alcohol. This is a significant step forward and demonstrates the growing importance and demand for reusable Digital IDs. 

During the Home Office Sandbox trials held in 5 of the UK’s leading supermarkets, 99,800 age verifications took place during the trials. There were no recorded cases of under 18s being allowed to buy alcohol.  

Customers enjoyed using the technology and were able to complete their shopping faster. The majority wanted to be able to use the technology going forward.

 

Make life easier…

…for staff:

  • Efficient: Age checks account for 50% of staff interventions at self-checkouts. Our innovative age verification technology would empower customers to prove their age independently of staff, who can focus on other tasks in the supermarket. During the Home Office Sandbox trials, retail staff were supportive of the technology and did not see it as a threat to their roles – it simply freed them up to spend more time helping customers on the shop floor. 
  • Safe: Year-on-year, age-restricted sales are an overwhelming trigger for abuse and violence towards supermarket staff. Age verification technology could reduce contact between staff and shoppers, removing some of the friction created by manual checks.
  • Accurate: Our facial age estimation technology is more accurate at detecting age than humans. There are several reasons why an employee might not accurately complete age checks. These include, tiredness, biases or falling prey to fake IDs. Our technology takes the pressure off human error and helps businesses avoid hefty fines for selling age-restricted goods to minors. With Yoti facial age estimation, 99.3% of 13-17 year olds are correctly estimated as under 25 and 100% of 13-17 year olds are correctly estimated as under 30. For more information, read our white paper.

 

…and customers:

  • Faster: Age checks can be done in real-time with accurate age estimations taking less than 5 seconds, dramatically reducing the time spent at checkouts.
  • Accessible: Studies show that about 4.5 million adults in the UK do not own an in-date, recognisable ID. Facial age estimation would allow them to prove their age without carrying a physical ID document.
  • More private: When shoppers show an identity document to prove their age, they reveal a lot of personal information – date of birth, full name, passport number, photo and so on. With facial age estimation and Digital IDs, they can just share the fact that they are over the set age threshold – and nothing else.
  • More convenient: We’re rarely without our phones, or our face for that matter. Shoppers would no longer be denied a sale if they forget their ID document, nor would they risk losing their valuable ID documents, like a passport or driving licence.

If you’re a retailer looking to make age checks more efficient, contact us today for more information.

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
Synthetic identity fraud is committed by the theft of a real piece of persoanl information such as an SSN, and combined with false information to make up an entirely synthetic identity that often bypasses traditional checks

What is synthetic identity fraud? How it works and how to prevent it

What is synthetic identity fraud? Synthetic identities are fake identities, built by combining real and made-up information, earning them the nickname “Frankenstein IDs” due to their pieced-together nature. Synthetic identity fraud is different to traditional identity fraud as it doesn’t involve an obvious, immediate consumer victim. These fake profiles are designed to mimic real customers, often slipping past traditional fraud detection systems because they don’t raise typical red flags. As a result, the primary victims of synthetic identity fraud are businesses and lenders, who bear the financial losses.   How synthetic identities are created and used Fraudsters combine

8 min read
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

6 min read