The hidden fraud crisis threatening Europe’s FinTech boom

European FinTech has won by making money feel faster, simpler and more intuitive. From instant onboarding to seamless payouts, companies such as Revolut have helped set the standard for what users now expect from financial products.

But every FinTech founder, operator and investor faces the same tension: the smoother the product experience becomes, the more attractive it can be to fraudsters.

Behind the growth of European FinTech, a parallel market has been scaling just as quickly: fraud.

Fraudsters are entrepreneurs as well. They research markets and competitors, identify weak points and build creative ways to exploit complexity. They also puncture the credibility of FinTech – if they continue unchecked, the industry will have to hand over all its gains back to traditional banks.

If you’ve worked in FinTech long enough, you see the trend. A new flow comes into effect. It simplifies the lives of constructive users. After a few weeks, you begin observing the initial case of abuse. Then another one, which is a little different. Then ten more. It arrives as a quiet stream of support tickets and risk alerts, until your product suddenly feels more exposed than expected.

Fraud now runs on software economics

INTERPOL put a number on what many teams are already feeling. In its March 2026 Global Financial Fraud Threat Assessment, it warns that AI-enhanced fraud is estimated to be 4.5 times more profitable than traditional methods, and it points to agentic AI systems that can plan and run full campaigns from reconnaissance to laundering. 

That is a different threat model than simply having a few bad actors.

Attackers can now automate targeting, scripting, social engineering, and the cash-out pipeline. All of this is now done with less effort. A defence model that depends mostly on manual review will always be late, because the attacker’s throughput is not tied to headcount and attackers adapt faster than static systems.

This is where the industry has to be honest with itself. If your adversary has automated most of their tasks, you cannot defeat them with numbers of people. But you also cannot blindly automate trust. Automated systems still struggle with context, manipulation tactics, and edge cases, which is exactly where serious fraudsters put their effort.

I consider something more hybrid to be the answer.

The answer is not to replace people with automation. The answer is to use automation for volume and detection, while keeping humans focused on intent, patterns and exceptions. In other words, the answer is a hybrid system.

Digital onboarding is no longer a strong gate

Onboarding is step one in fraud. 

Entrust’s 2025 Identity Fraud Report highlights a 244% year-over-year increase in digital document forgeries, and reports that deepfake attempts occurred every five minutes in 2024. 

This is what that means on the ground. A fake document is no longer something that looks obviously tampered with. It can be clean, high-resolution, and tailored to pass basic checks. You can also expect more attackers to mix document fraud with social engineering, so even a valid identity can be paired with coerced behaviour later.

Modern defence cannot stop at document verification. Passing KYC doesn’t mean much on its own anymore: the real signal comes afterwards, from behaviour and ongoing due diligence (ODD) and enhanced due diligence (EDD) are extremely important. 

Things like device and session signals. Velocity checks. Risk-based step-ups when something looks off. You also need people who know what to look for when verification tools signal a pass but the story does not feel right.

Customers are worried about identity theft

Speed is central to FinTech, but in a sensitive industry, it can also create room for oversight.

Consumer anxiety calls for more caution. Experian’s 2025 U.S. Identity & Fraud Report found identity theft is the top consumer concern at 68%. Users still want to have the speed of FinTech though but accompanied with the confidence that they will be safe if things go awry. They do not want to simply trade their hard-earned money for a convenient model that stops taking responsibility when they are targeted.

That pushes FinTeech toward a smart friction model. That would consist of less blanket review with more targeted intervention. It also means better signals, and a faster response when a scam pattern starts showing up.

Liability is shifting onto payment providers

From traditionally being seen as a matter of security, fraud is now being analysed through the lens of unit economics.

The UK has followed the trajectory of these winds. The Payment Systems Regulator’s authorised push payment scam reimbursement regime went live on 7 October 2024, with a maximum reimbursement level set at £85,000 per claim for Faster Payments. 

Europe is moving in a similar direction. In November 2025, the Council and European Parliament announced a provisional political agreement on a new payment services regulation and PSD3 changes, explicitly framed around stepping up the fight against payment fraud. 

Once reimbursement and fraud obligations tighten, weak controls shift from being a risk to becoming a predictable margin hit. You pay directly in losses, chargebacks and support load. Then you pay again when excessive friction makes it harder to convert users.

Better fraud prevention is undoubtedly expensive, but so is letting fraud become normal.

The outdated collaboration gap 

While fraud groups share playbooks across borders, FinTechs often do not, partly because of privacy law, liability, and reputational risk.

Still, there is a middle ground that the industry underuses.

You do not need to share raw customer data to help each other. You can share typologies, scam structures, and signals. You can share what it looks like rather than who it was. That is often enough to help other teams recognise a pattern earlier.

There are already efforts in this direction. The European Payments Council has described SEPA-wide work on fraud data collection, analysis, and information sharing, alongside references to EU proposals that include data sharing provisions for fraud prevention. 

When we continue to make fraud intelligence a trade secret, we all bear the learning cost individually, while attackers keep reusing the same tactics across markets.

What founders and operators can do now

No one wants to be scammed. No one sets out with that intent. However, people slip through the guardrails because of a mismatch between how fast product surfaces change and how slowly defences adapt.

A few practical shifts help.

• Build controls that change often. If your rules, models, and escalation playbooks only get updated a few times a year, you will always be on the back foot and at a disadvantage.
• Take onboarding more seriously. It’s your first line of defence. And once someone is onboarded, put serious effort into post-onboarding monitoring. Behaviour can tell you what documents cannot.
• Design interventions that protect users without making usage more complicated. Use risk-based step-ups instead of a blanket security wall.
• Finally, model fraud as a business cost. Especially with reimbursement trends, it is no longer a security spend. It is about protecting revenue and the right to keep a low-friction product.

FinTech has spent a decade competing on user experience and ease of use, and we have seen what it has achieved. The next step is to protect that progress without weighing products down with unnecessary friction.

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