Fraudio takes a fundamentally different approach. Instead of siloed models, it operates a single, centralised AI that learns from and scores transaction patterns across all customers in real time. This is not an incremental improvement it is a structural shift.
The difference lies in how fraud is detected. Legacy systems assess transactions in isolation; Fraudio analyses sequences of behavior. The system identifies patterns that escape typical merchant based solutions such as suspicious cluster of #clean# transactions across multiple merchants, money laundering, authorized push payment fraud, and money mule activity all inherently pattern-based problems.
Fraudio stands out as one of the most compelling companies in European fintech today. It combines a genuine technical breakthrough with a clear market need and the discipline to translate both into a scalable business. Its centralised AI not only improves detection accuracy but compounds in strength with every new client, creating a data advantage that per-client models cannot replicate. This is a true moat structural, not superficial.
A problem the industry can no longer outrun.
The economics of fraud have turned against the industry:
- Global payment fraud losses are set to exceed $40 billion by 2030, driven by the rise of real-time rails, account-to-account payments, and digital commerce;
- Regulatory pressure has intensified in parallel, with PSD3, instant payments rules, and the EU AML package landing on the same desks at the same time;
- And the incumbents, built for an earlier era of rules engines and client-by-client models, can no longer keep up with modern fraud patterns.
Fraudio emerges at exactly this point of friction, opening advanced fraud prevention to the merchants, PSPs, acquirers, and card issuers who have been priced out of it until now.
The team behind the build.
Great architecture does not design itself. João Moura spent more than fifteen years inside payment fraud most recently as Lead Data Scientist at Payvision long enough to understand exactly why client-siloed models hit a ceiling, and stubborn enough to build the alternative. Alongside him, CTO Robin Vastenouw brings the engineering depth to run a model of this kind at production scale, under live transaction loads, without flinching.
The market fit has already been proved: Fazz, Cashflows, and Vialet have chosen Fraudio over incumbents with longer track records and deeper pockets. The company is scaling rapidly, has reached operational break-even, and is shortening its sales cycles as the platform matures — the kind of signals that are hard to fake and even harder to engineer without genuine product-market fit.
An inevitability in the making.
Fraud is becoming faster, more organised, and more sophisticated. The defences have to follow the same curve. We believe that within a few years, it will be unthinkable for any serious payments business to operate without collaborative, AI-driven fraud prevention at its core.
That is why we proudly invested in Fraudio.