Is Full Integration Really Practical?

A recent report found that more than 57,000 Americans fall victim to scams every day. Financial fraud is rising in the U.S. and other regions worldwide. In response, the National Automated Clearinghouse Association, Nacha, is pushing for real-time fraud monitoring by 2026, requiring closer collaboration between fraud and anti-money laundering teams.

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Both teams have historically struggled to work together because of significant differences in how AML and fraud programs operate. While some say the teams should be merged, others fear that combining these two teams gets “challenging to extract synergies and achieve increased operational efficiency.”

There’s no one-size-fits-all solution due to the diversity of organizations. Smaller financial institutions usually have one top-level organization for AML and fraud under one leader but larger banks face challenges with “territorialism and time constraints,” said Ian Mitchell, founder of Mission Omega, a specialized fraud services provider helping people fight financial crime. “The ideal setup is having both teams under one leader but maintaining dedicated fraud and AML roles to manage their distinct risks effectively.”

While the convergence of fraud and AML functions, referred to as FRAML, gains traction, widespread adoption remains hindered by regulatory and technological challenges. Although some vendors now offer integrated platforms, they often lag in addressing advanced financial crime typologies, such as social engineering, cyber fraud and money mule schemes.

What’s Stopping the Integration?

Fraud and AML have two different fundamental drivers. AML is driven by regulatory and compliance requirements, while fraud is primarily focused on limiting financial losses for banks and their customers.

Given that AML is driven by regulatory and compliance requirements, it is – and needs to be – administratively heavy with extensive documentation, which often leads to slow and rigid processes. This is not the case in fraud-related work, where there is greater flexibility to focus on activities that create value. This difference permeates all aspects of work – from model development to investigations.

Unlike fraud that has a confirmed case, “within AML, a bank often does not know whether a case involves confirmed money laundering; in most instances, it is merely a suspicion,” said Sebastian Nordli, former head of AML risk and analytics at 421. “This impacts work methods in several ways where, for example, it is possible to develop predictive and more advanced models within fraud prevention. Something which can’t be the case in AML investigations,” Nordli said.

While at a high level both the teams seem aligned as both address financial crime and use similar data and infrastructure, such as transaction monitoring and case management, they “have distinct objectives and methods,” Mitchell said.

“Fraud often requires real-time decisions and heavy customer interaction, while AML focuses on longer, in-depth investigations. These nuanced needs lead to separate tools,” he said.

There are few success stories on AML and fraud collaboration, aside from success at a few credit unions and small banks. Nordli has seen numerous reorganizations within the financial crime prevention functions over the years. “While some value has been derived from fostering increased collaboration between fraud and AML teams, the negative effects have typically outweighed the benefits,” he said while citing differences in work culture, “making it difficult for them to work effectively together under a unified structure.”

Regulatory Requirements

In Europe, the rise of public-private partnerships such as the U.K.’s Joint Money Laundering Intelligence Taskforce promotes shared intelligence and better alignment between AML and fraud detection efforts.

Collaborative forums such as the European Banking Authority also emphasize a unified approach to financial crime. Furthermore, the 6th Anti-Money Laundering Directive mandates stricter penalties for financial crimes, increasing accountability for companies not seen to be combating money laundering and predicate offenses such as fraud effectively, said Gabriella Bussien, CEO of Trapets.

Nacha’s new monitoring capability requirement in the U.S. mandates financial institutions to implement systems capable of effectively monitoring transactions in near real time. Nacha’s requirement could serve as a catalyst for banks to integrate fraud and AML monitoring systems.

Collaboration Over Integration

While integration between AML and fraud teams is a desirable goal, experts say it should not be viewed as the best solution. Paul Dunlop, insider risk consultant at a financial services firm, stressed the importance of collaboration over integration. “I am against the oversimplification of fraud and AML integration. Banking risks are multifaceted, involving not just fraud and AML but also cybersecurity, privacy and other domains,” Dunlop said. “Integration decision should be assessed based on the bank’s maturity level, regulatory environment and unique operational needs.”

“Cost should not be the sole factor behind this decision. One must assess operational and risk management trade-offs,” he said.

Meng Liu, senior analyst at Forrester, said that despite AML and fraud being two distinct functions at present, the trend toward more consolidated and integrated financial crime management is real. “From the bank’s external point of view, fraud incidents often coincide with money laundering activities; therefore, it would be more efficient and effective to detect and prevent fraud and money laundering simultaneously,” she said.

Practical Scenarios

Despite the differences in fraud and AML teams, some use cases, such as scams, human trafficking and child exploitation, cry out for better collaboration, Mitchell said. “These require shared data and aligned strategies.”

But high-volume fraud detection such as check and card fraud is less suited for joint efforts due to operational complexity. Vendors have begun offering unified platforms, but these solutions often struggle to keep pace with sophisticated financial crimes involving social engineering, cyber fraud and money mule networks.

Organizations looking to integrate both functions must start with aligning risk taxonomies and collaborate on playbooks, investigations and regulatory reporting. These organizations should leverage people, infrastructure and data to focus on combating cybercrimes rather than worrying about organizational structures.