Banks Find the Big Money in FinCEN’s $4.9 Billion Smuggling Data

Financial institutions have long sought to identify suspicious financial activity. However, new data from the Financial Crimes Enforcement Network (FinCEN) reveals that the key question may be their ability to collectively detect enough of such activity. FinCEN reported that financial institutions flagged nearly $5 billion in potential human smuggling-related activity between 2023 and 2025, based on 67,540 Bank Secrecy Act reports.

The report highlighted recurring indicators, including unverifiable relationships between senders and beneficiaries, payments along common migration routes, and excessive cash activity near the U.S. Southwest border. The most striking finding, however, is that money services businesses (MSBs) filed approximately 97% of the reports, despite representing only about 3% of depository institutions.

This discrepancy highlights the unique observation point MSBs have for cross-border money movement. MSBs frequently identified transactions deviating from customers' normal patterns, such as money moving through migration route locations and attempts to structure transactions to avoid reporting requirements. Banks, on the other hand, identified funnel accounts receiving money from multiple individuals, suspected cash structuring, and travel agencies arranging transportation for migrants.

While banks may see the convergence of multiple payments, MSBs may detect individual suspicious transactions. Traditional anti-money laundering (AML) systems were primarily designed to flag individual transactions or customers that significantly deviate from expected behavior. However, FinCEN's findings suggest that the more significant challenge lies in connecting seemingly explainable activities when viewed collectively.

To address this, banks and financial institutions need tools that can integrate various data points, such as accounts, merchants, cash activity, peer-to-peer payments, travel spending, and external intelligence, into a comprehensive network intelligence system. This should involve utilizing artificial intelligence and graph analytics to better understand the relationships between parties, assess the legitimacy of those relationships, track the movement of money, and identify changes in behavior following increased law enforcement or regulatory scrutiny.

Ultimately, the key lesson for financial institutions is that more reports alone will not solve AML issues. Instead, the ability to connect scattered transactions into usable network intelligence will provide law enforcement with more valuable leads and improve banks' chances of preventing suspicious money from moving too far.