Until recently, anti-financial crime convergence was for many in the financial industry a strategic ambition. Today, faster payments, converging crime typologies, and heightened regulatory scrutiny have made it an operational requirement for effective financial crime prevention.
According to Sebastian Hetzler, co-CEO of IMTF, anti-financial crime convergence became an operational necessity because financial crime itself has converged —forming the basis of a more holistic approach to financial crime compliance.
He explained, “Today’s typologies rarely sit within a single domain: fraud increasingly feeds money-laundering flows, cyber-enabled attacks accelerate account compromise and mule activity, sanctions evasion exploits trade and crypto channels, and instant payments compress detection and response windows to seconds. Treating these risks in isolation creates blind spots at exactly the points criminals exploit.”
At the same time, Hetzler remarks, regulatory and supervisory expectations are shifting from control coverage to outcome effectiveness.
“Supervisors increasingly expect institutions to demonstrate timely detection, coherent investigations, and explainable decisions across the full lifecycle of a case, not just within individual AML, fraud, or sanctions frameworks,” said Hetzler. “Without convergence across data, workflows, and investigative teams, institutions struggle to connect signals, act in real time, and provide defensible outcomes under scrutiny.”
Evolution of compliance
As criminals increasingly blur the lines between fraud, AML and cybercrime, how must compliance structures and investigation models evolve?
Hetzler believes a key part of this is that compliance structures must move away from domain-specific ownership of risk and toward a shared, integrated view across the investigation lifecycle.
He added, “Criminal activity now unfolds across multiple stages (scam, account takeover, mule movement, crypto conversion, and instant payouts) often within hours or minutes. As a result, linear handoffs between fraud, AML, sanctions, and cyber teams are no longer effective.”
Domain-specific investigations often delay response and can prevent institutions from recognising how isolated events form part of larger laundering or sanctions-evasion schemes.
“Investigation models therefore need to evolve into cross-functional, intelligence-led workflows, where alerts, customer context, network relationships, and external intelligence are assessed together,” Hetzler said. “This requires shared case views, common prioritisation logic, and coordinated decision-making, ensuring investigations start with context rather than isolated signals.”
Compliance reshaped
If 2025 was defined more by acceleration than innovation, which financial crime trends most fundamentally reshaped compliance operations?
In the opinion of Hetzler, three accelerating forces had the most profound operational impact in 2025 – the first of these being speed.
He explained, “Instant payments and faster settlement dramatically reduced the time available to detect, assess, and intervene, forcing compliance teams to operate closer to real time rather than relying on retrospective controls.”
The second force is that threat sophistication increased as hybrid typologies, including fraud-driven laundering flows, sanctions evasion networks and AI-enabled identity abuse, are increasingly linked in a single chain, requiring broader visibility and faster correlation across data sources.
The third and final force is technology adoption at scale. Whilst AI and advanced analytics were not new, their operational use expanded substantially in behavioural monitoring, anomaly detection, investigation support and alert prioritisation. This, Hetzler made clear, delivered productivity gains while also raising expectations around governance, explainability and human oversight.
“Together, these accelerators reshaped compliance operations more fundamentally than any single new regulation or technology,” said Hetzler.
Data integration across silos
One of the biggest obstacles to effective financial crime prevention has been data integration across silos. Why is this the case?
For Hetzler, modern financial crime detection depends on connecting signals across domains, not analysing them in isolation. “Customer behaviour, transaction patterns, counterparty relationships, sanctions exposure, and adverse media often sit in separate systems owned by different teams. When data remains fragmented, institutions struggle to form a coherent picture of risk quickly enough.”
For effective detection and investigation, a true 360-degree view is required across the customer lifecycle, transactions, entities and networks. Despite this, Hetzler made clear that many institutions still operate with siloed systems and domain-specific datasets.
He remarked: ” In practice, without integrated data and contextual case intelligence, teams lose speed, miss connections, and struggle to produce consistent, explainable outcomes under rising supervisory expectations. Data integration is therefore not just a technology challenge, but an organisational one: without aligned data models and shared access to contextual information, even advanced analytics and AI models cannot deliver their full value.”
The AI transformation
The topic sucking all the air out of the room at present is artificial intelligence, with its break-neck speed evolution leaving many in its wake. How is this technology transforming AML decision-making and fraud detection, and where is strong human oversight still vital?
“AI is materially improving compliance by enabling behavioural analysis at scale, identifying subtle anomalies, prioritising alerts, and supporting investigators with enriched context and summaries. In practice, this reduces noise, accelerates response times, and allows teams to focus on higher-risk cases,” said Hetzler.
That being said, the IMTF co-CEO makes clear AI does not replace human judgement. Strong human-in-the-loop oversight, he said, remains essential for transparency, explainability, accountability, bias mitigation, and regulatory defensibility.
“As AI becomes more embedded in decision-making, institutions must strengthen governance frameworks, model validation, and documentation to augment expertise while preserving accountability,” said Hetzler.
A credible AML programme
What does a credible real-time AML programme look like in the age of instant payments?
Here, Hetzler stated, “A credible real-time AML programme combines speed, context, and control. It relies on real-time monitoring and risk-based controls that can assess behaviour as it unfolds rather than after the fact, enabling timely intervention when necessary.”
He explained that, crucially, real-time AML is not just about faster alerts – it also depends on cross-domain data integration and anti-financial crime convergence, bringing together fraud, AML, sanctions, payments and customer data within a single investigative context,supporting a holistic, end-to-end view of financial crime risk in real time.
He added, “Entity resolution, network analysis, and unified case intelligence then allow investigators to quickly understand how transactions, accounts, and counterparties are connected and to detect patterns as they form. Fast, automated workflows with clear audit trails and explainability ensure investigations start with context, not isolated signals. This capability is increasingly essential as instant payments materially compress response windows and accelerate the need for real-time monitoring.”
Who will be the winners?
A million-dollar question at the feet of many in the industry right now is what the right capabilities are – whether this be technological, human or organisational – to separate the winners from the losers. For Hetzler, a sure sign a company might not make it is if institutions treat these three groups as separate workstreams.
He explained, “Institutions that treat technology, organisation, and skills as separate workstreams will struggle to keep pace with the speed and complexity of modern financial crime. In contrast, leading institutions in 2026 will distinguish themselves through integration rather than incremental optimisation.”
Hetzler remarked that this starts with a strategic orientation toward integrated financial crime typologies, recognising that modern crime rarely fits neatly into fraud, AML, sanctions or cyber categories. This holistic view of financial crime risk becomes the organising principle for technology choices, operating models, and skills development.
“Executive teams must make a deliberate choice to adopt this integrated view, as it sets the foundation for closer alignment across data, teams, and operating models.
Technologically, this means unified platforms that combine real-time monitoring, advanced analytics, workflow automation, and AI capabilities supported by strong governance and explainability,” the IMTF co-CEO remarked.
On the organisational side, he stated that this requires convergence operating models that can connect sanctions, fraud, cyber, payments and AML risk, underpinned by consistent processes and cross-functional investigation teams.
Finally, Hetzler said that on the human side, success will depend on upskilling in analytics and AI oversight, building multidisciplinary expertise, and strengthening the ability to supervise and validate AI outputs under tighter regulatory scrutiny.
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