Matt Prendergast Profile Picture

Matt Prendergast

Matt is the Product Marketing Director at Yoti and has helped raise the brand, message and ethics of Yoti. Matt strongly believes in the mission of Yoti where AI can be deployed responsibly to protect people and children from online harms and prevent fraud and scams.

Woman surrounded by green plants using her smartphone

Age Check Certification Scheme evaluation for Yoti Facial Age Estimation

We are pleased to announce Yoti has been re-evaluated by the Age Check Certification Scheme (ACCS) for our facial age estimation (FAE) on our latest September 2024 model. ACCS now report our Mean Absolute Error (MAE) for 18 year olds is just 1.05 years, with a Standard Deviation (SD) of just 1.01 years. ACCS first tested Yoti’s September  2020 model in November 2020, reporting the MAE for 18 year olds to be 1.79, demonstrating our continued effort to improve the performance of our model.   Yoti has been training its FAE model since early 2018 by using data captured mainly

3 min read

How Yoti developed over 70 integrations in 9 months

“With the average business using over 130 software products, forward looking SaaS providers like Yoti are focused on connected experiences and making integrations a core competency.” Marcus Edgington VP of Product, Prismatic Prismatic is the world’s most versatile embedded iPaaS, helping B2B SaaS teams launch powerful product integrations up to 8x faster. Learn how Yoti used Prismatic’s embedded integration platform to bring our integrations to life. So far, we have over 70 integrations for businesses to choose from. That’s more than any other identity company. Using the Prismatic platform, we now build an integration in two weeks

2 min read
A man placing his face in the frame to perform a facial age estimation with Yoti

How accurate is facial age estimation?

“How accurate is it?” is the first question regulators, businesses and users tend to ask about facial age estimation. To date, we have mainly presented the technology’s Mean Absolute Error (MAE) as a proxy for accuracy. It’s an intuitive way to understand how accurate a model is. We can say it’s accurate to 1.3 MAE for those aged between 13 and 17 years or 2.5 MAE for those aged between 6 and 70 years. However, the answer is slightly more complicated. Following the COVID-19 pandemic, many people will be more aware of the terms ‘true positive’ and ‘false negative’

5 min read
Digital ID Connect & Disclosure & Barring Service (DBS) logo lockup

34 percent of people choose reusable Digital ID to prove their identity for DBS checks

Since June 2022, Yoti has completed over 1.6 million right to work (RTW) checks and over 930,000 DBS (Disclosure & Barring Service) checks. Of those checks: 34% of UK adults choose to use Yoti, Post Office EasyID or Lloyds Bank Smart ID to prove their identity for DBS checks. 23% of UK adults choose to use Yoti, Post Office EasyID or Lloyds Bank Smart ID to complete their RTW checks. Yoti, Post Office EasyID and Lloyds Bank Smart ID are all certified by the UK Digital Identity & Attributes Trust Framework (UK DIATF) as proof of identity for Right

2 min read
Preview of the Yoti whitepaper: On the threat of Generative AI

On the threat of detecting deepfakes

Learn how Yoti can help you defeat deepfakes As the threat of generative AI in identity and content integrity continues to build, Yoti has developed a comprehensive strategy focused on early detection by using tools to prevent AI-generated content or attacks at the point of source. Yoti’s strategy for detecting generative AI threats targets two attack vectors: presentation attacks (direct) and injection attacks (indirect), with a focus on early detection during the verification or authentication process.  Our proprietary and patented technology can work on: Deepfakes Illicit images Account takeovers Identity theft and fraud Content moderation Injection attacks Bot

2 min read
Woman estimating age on Yoti's technology which has antispoofing and injection attack protection

The importance of anti-spoofing for facial age estimation

It has been claimed that facial age estimation technology can be easily spoofed. The proliferation of news on generative AI and deepfakes has added to the conversation, and there is doubt and concern over the security of online safety systems. Suffice to say, we’ve thought of that. We have developed a suite of anti-spoofing tools to ensure your check is real, valid and accurate. Our experience working with organisations to implement age verification has enabled us to identify and cover risks and vulnerabilities. When we perform an age estimation check, we are actually performing a number of security checks simultaneously.

3 min read