By Marc de Beaucorps, Co-founder and CEO of Finovox
The UK’s rollout of new digital IDs is being pitched as a straightforward upgrade involving safer age checks, smoother access, and fewer fakes. But from a fraud perspective, “simpler” can be a dangerous word. Identity fraud rarely disappears; it mutates. And when you digitize identity, you don’t just change the interface. You change the attack surface.
Across England and Wales, pubs, bars and retailers have now been given the green light to accept digital IDs for age verification. The hope for this system is that if verification becomes faster, more consistent and more tamper-resistant, then the traditional fake ID, printed, photoshopped, or passed off with a bit of confidence, may finally be tossed aside. Yet there’s a very real chance that thanks to AI, this new system won’t fix these problems at all. It’ll simply change the way fraudsters operate.
Latest research from fraud-detection specialist Finovox suggests the challenge is already evolving. Eleven per cent of Britons admit to having committed document fraud at least once, and 67% point to AI as a key factor making document fraud easier. Add to that the increasingly accessible tools people can use to manufacture convincing paperwork in minutes rather than days, and you start to see the problem. When fraud becomes more automated, scalability stops being a barrier for criminals, and it starts becoming a burden for businesses trying to keep up.
What’s more, the statistics around success tell you a lot about the current reality. Eighty-two per cent of those who committed document fraud succeeded, and 37% say they’d be willing to do it again. That’s not just alarming; it shows how effective it is. And the most falsified documents- proof of residence, medical documents and driving licenses, aren’t edge cases. They’re everyday essentials that many systems and services rely on.
If digital IDs are introduced without equally strong anti-fraud controls, robust verification standards, and a clear understanding of how AI-enabled manipulation works, then the likely outcome may be fewer fake cards but more digital impersonation.
How AI is changing the threat
Digital ID systems are often sold as a way to streamline verification, but they also need to be built to actively defend against the way fraud is evolving. The real challenge is that artificial intelligence doesn’t just make fraud easier, it makes it more scalable and much harder to spot, because attackers can automate document forgery, create synthetic identities, and even generate deepfake biometrics designed to slip past traditional checks.
With automated tools, criminals can produce hyper-realistic digital identity documents at scale, which can sail through basic onboarding validations if those checks are too shallow. AI can also blend fragments of real personal data with entirely fabricated details, allowing criminals to manufacture believable synthetic personas that look “clean” across standard screening. And when biometric checks are involved, machine learning can generate fake selfie videos and manipulated voices, potentially undermining facial recognition and liveness detection during what should be the most secure moment of verification.
Just as importantly, the attack doesn’t have to stop after opening the account. AI-driven fraud can extend into account recovery takeovers and unauthorized high-value payments, turning a one-time deception into an ongoing crime pipeline. That’s why verifying the authenticity of documents at the very start of the digital identity journey matters more than ever, and the next step is looking at how digital ID systems can fight back against these specific AI-enabled threats.
How Digital ID Systems Fight Back
Digital ID systems can fight back, but they have to do more than ask for proof; they must actively assess whether that proof is believable. One of the most effective defenses is advanced liveness detection, where AI is used to spot micro-expressions and subtle signs of tampering at the pixel level, making it harder for criminals to bypass checks with synthetic video injection.
That same principle applies to behavioural biometrics, where platforms don’t just look at what a person shows on screen, but how they interact, tracking typing cadence, swipe patterns, and device handling routines to identify unusual behaviour that doesn’t match the expected profile, triggering stepped-up security when risk rises.
Finally, strong systems should use layered adaptive authentication, adjusting the strength of verification in real time based on the risk score of the specific request. In practice, routine actions can move quickly with minimal friction, while sensitive tasks, those most likely to be targeted by fraudsters, demand deeper proof, creating a moving barrier that attackers can’t easily plan around.
Digital ID could be a genuine step forward for age checks and day-to-day access, but from a fraud perspective, the picture is clear. Identity crime doesn’t stand still, and AI will only make it evolve faster. If the UK’s digital rollout focuses mainly on convenience, without stronger verification, liveness assurance, behavioural signals, and layered, risk-based authentication, then the outcome may not be fewer fakes. It may simply be the same fraud, delivered in a more convincing, more scalable, and harder-to-detect form. The real test, then, isn’t whether digital IDs can verify identity, but whether they can reliably defend it when attackers start using AI to impersonate, manipulate and take over.
