A new survey of 200 anti-money laundering (AML) professionals at US mid-size and community banks reveals a growing gap between confidence and capability in the fight against financial crime.
The research, conducted by Quantexa, a pioneer in Decision Intelligence for enterprises and public sector and a pioneering provider of financial crime solutions for the global banking industry, underscores the mounting pressure on institutions that serve as the backbone of the American economy and small business sector.
Regulatory expectations
Globally, the United Nations Office on Drugs and Crime (UNODC) estimates that $800 billion to $2 trillion is laundered every year, roughly 2–5% of global GDP.
While the spotlight often falls on large institutions, mid-size and community banks are uniquely vulnerable as they face the same regulatory expectations as the largest banks, but with fewer resources, leaner teams, and older technology.
Reliance on outdated systems
The report also highlights a notable option for mid-sized and small banks to close these gaps by applying better data
According to the survey, nearly half of AML professionals say reliance on outdated systems is their biggest barrier, with many citing fragmented data and the inability to monitor risks in real time.
Despite these challenges, 94% express confidence in their ability to detect emerging threats, even while 46% admit their investigations remain slow and inefficient.
The report also highlights a significant opportunity for mid-sized and community banks to close these gaps by applying better data, contextual insights, and AI solutions, capabilities that are increasingly available to institutions of all sizes.
Harness better data and AI
“Mid-size and community banks are the heart of Main Street America, powering small business growth and local economies,” said Chris Bagnall, Head of Financial Crime Solutions for North America at Quantexa.
He adds, “With financial crime evolving faster than ever and outdated systems leaving them exposed, these banks have a critical opportunity to harness better data and AI to make smarter decisions and protect the communities and businesses they serve.”
Key survey findings
- Outdated systems and tech gaps: Legacy technology, poor data quality, limited AI/ML adoption (47%), and lack of real-time monitoring (41%) continue to undermine AML effectiveness.
- Resource and expertise constraints: Operational friction from inefficient investigations and high false positives drains scarce resources, while nearly half (47%) of banks lack the internal expertise to modernize.
- Regulatory uncertainty slows progress: With 45% citing unclear guidance around emerging technologies like AI, banks face “decision paralysis” that hinders innovation and adoption.
Adopt AI and real-time monitoring
Looking ahead, respondents identified AI, real-time monitoring, and interbank collaboration as the most promising ways to modernize AML programs. Nearly 93% also said interbank collaboration under Section 314(b) of the USA PATRIOT Act is critical to improving detection of illicit activity.
The report outlines a five-point call-to-action urging mid-size and community banks to modernize outdated systems, adopt AI and real-time monitoring, and make greater use of contextual data to strengthen detection capabilities.
It emphasizes the importance of collaboration across institutions and with regulators to share intelligence and help shape expectations around emerging technologies. Finally, it calls on banks to invest in their people and processes to build sustainable expertise, resilience, and a more proactive stance in the fight against financial crime.
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