Financial institutions across Europe are seeing fraud and money laundering become increasingly interconnected issues, driven by digital payment transformation, new criminal typologies and a surge in AI-enabled scams.
The traditional view of fraud and AML as separate risks is eroding as criminal networks exploit speed, anonymity and complexity across digital channels, claims Moody’s.
As instant payments expand globally, financial crime is evolving rapidly, prompting calls for unified fraud and anti-money laundering (FRAML) frameworks.
Real-time transfers continue to gain traction. An article from Payments Industry Intelligence claims that real-time and instant payments could represent 28% of global electronic payments by 2027, while an estimated “15% of total real-time payments in Europe” were instant in 2023.
Instant Payments Regulation and PSD3 aim to offer stronger consumer protections, including reimbursement rules, yet the volume and velocity of payments still create opportunities for criminals. AI-driven deepfakes, impersonation schemes and social engineering attacks add further urgency.
One of the primary challenges is operational separation. Fraud is a predicate offence to money laundering, yet many institutions continue to maintain separate systems, teams and data environments. This division can leave visibility gaps across customer journeys and create inefficiencies in reporting suspicious behaviour. FRAML offers a strategic model to merge processes, improve customer risk profiling and streamline responses to emerging threats.
Data is central to the approach. Master data management supports unified customer, account and transaction records that allow firms to build cross-risk insight. Integrated datasets enable machine-learning models to spot anomalies, related high-risk behaviours, synthetic identities and potential mule activity. Removing silos can also reduce duplicate alerts and improve customer screening.
Interoperability strengthens governance by allowing structured and unstructured data to be standardised and analysed across platforms. This capability supports advanced analytics, scenario testing and dashboarding while helping firms align with FATF expectations, GDPR requirements and forthcoming EU AML regulatory changes.
Financial Intelligence Units (FIUs) may benefit significantly from convergence. Shared records at onboarding and during ongoing monitoring improve suspicious activity reporting, investigations and collaboration — particularly where multiple risk touchpoints are involved.
As FRAML frameworks mature, European institutions are evaluating governance priorities. Areas of focus include ensuring transparency in AI risk scoring, maintaining clear escalation procedures and establishing robust access and encryption controls. Implementing audit trails and documented decisioning processes may help support regulatory obligations without slowing innovation.
The move toward unified financial crime controls reflects a growing recognition that fraud and AML can no longer be addressed in isolation. FRAML positions banks to improve detection, simplify compliance, and build resilience against AI-enabled financial crime. Joint suspicious activity alerts, holistic transaction monitoring and shared investigative workflows could mark a shift toward more effective and efficient defence strategies.
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