Across Borders, Beyond Sight

Cross-border payments are essential to the functioning of today’s global economy, facilitating international trade, investment, and commerce. However, they also present significant financial crime risks that must be effectively managed to protect the integrity, security, and stability of the global financial system.

Whereas a domestic payment usually flows between two banks that know their own customers, a cross-border transaction can involve multiple financial institutions and intermediaries across jurisdictions, each introducing potential challenges for transparency, monitoring, and financial crime detection.

Cross-border financial crime comes in many forms:

• Nested correspondent activity and payable-through risk: A bank that offers correspondent services to another bank is often processing payments for that bank’s customers too, and sometimes for other banks further down the line. It may have no direct relationship with the people moving the money. The Russian Laundromat is a good example. Between roughly 2010 and 2014, an estimated $20 billion or more was moved out of Russia through Moldovan and Latvian banks and on to accounts across Europe and elsewhere. Each bank in the payment chain saw only part of what was happening.
• Sanctions evasion: Sanctioned parties almost never pay in their own name. They set up front companies and shell entities and route goods through transshipment hubs to keep their distance from the transaction. Since 2022, Western-made electronics and machine parts have continued to find their way to Russia through middlemen in third countries, paid for through banks with no obvious connection to anyone sanctioned. Individually, those payments may have appeared as routine trade.
• Trade-based money laundering: Illicit actors leverage the complexities of cross-border trade to disguise the proceeds of crime and move value through the use of trade transactions. Invoices are inflated or deflated, goods are misdescribed, or nothing ships at all. The Lebanese Canadian Bank case shows how this works in practice. U.S. authorities found that money was wired to the United States to buy used cars, which were then shipped to West Africa and sold, with the proceeds making their way back to Lebanon through a network linked to Hezbollah. The paperwork backed up the payments but didn’t reflect what was actually going on.
• Fraud and authorized push payment scams: In investment, romance, and impersonation scams, the victims send the money themselves, often to accounts overseas. With instant payments, that money can cross a border and move again before anyone notices. Getting it back at that stage is very hard, and the victim’s bank is usually left answering questions about why it didn’t step in.
• Money mule networks: Criminals need accounts to receive and move illicit funds, so they recruit people to provide them, often through fake job ads on social media or online relationships. With mules in several countries, money can be split up, moved around, and withdrawn quickly. Europol’s yearly crackdowns on money mules routinely turn up thousands of them in a single operation, which says a lot about how organized this has become.
• Digital asset on- and off-ramps: You can trace digital asset transactions on a blockchain. What’s harder to follow is the moment money moves between crypto and fiat currency, and that’s where criminals tend to break the trail. Garantex, a Russia-linked exchange, was sanctioned by the U.S. Treasury in 2022 and kept processing funds tied to ransomware, darknet markets, and sanctions evasion until U.S. and European authorities took down its infrastructure in 2025. Poorly controlled exchanges and peer-to-peer brokers are still the weakest point.

Where Controls Fall Short

While financial institutions have spent heavily on compliance over the years, much of the controls were designed when payments were slower and simpler.

• Checks happen too late: Plenty of transaction monitoring systems look at activity after it has settled, sometimes days afterward. That made sense when payments took days to clear. Now that money can leave the country in seconds – an alert the next morning tells you what happened; it doesn’t stop it.
• Screening catches names, not networks: Sanctions screening is good at flagging a known name. It’s not s good at picking up a brand-new company, a shared address, or a series of payments that only look suspicious when you put them side by side. Evasion schemes are built specifically to get past name checks.
• Teams don’t talk to each other: Fraud, AML, and sanctions teams often review the same payment using different systems, data, and priorities. The fraud team might flag a mule account that the AML team never hears about. Criminals aren’t constrained by an org chart, and they take full advantage of the gaps.

What Good Practice Looks Like

The institutions handling this well aren’t trying to slow down payments but rather working to see more of the payment journey and acting on it.

Many are making much better use of payment data. Payment messages carry far more structured information than they used to, and the stronger institutions are putting it to work: screening more accurately, connecting related transactions, and spotting patterns across counterparties, instead of checking the same few fields they always have.

They’re also paying closer attention to their partners. Correspondent banks, payment providers, and fintechs are treated as relationships that need ongoing oversight, not boxes ticked at onboarding. That means knowing who those partners serve, how much nested activity runs through them, and whether their controls hold up.

Breaking down internal silos makes a big difference too. When fraud, AML, and sanctions teams share data, review cases together, or work from a single view of the customer, something one team spots becomes useful to all of them.

None of this works without people who know what they’re looking at. Analytics and AI can flag unusual activity in real-time and help manage alert volumes, but someone still has to understand the typology behind an alert and decide what matters. That’s why investing in staff pays off. Practical training that keeps teams current on how financial crime is evolving, like the programs the Institute for Financial Integrity runs for institutions worldwide, is what turns better data into better decisions.