How have AML/CFT risks evolved with the shift to cashless payments?

The move away from cash, which accelerated during the COVID-19 pandemic, has now settled into a permanent feature of the global payments landscape. At the peak of the pandemic, central banks on several continents, including China and the United States (US), ordered banks to disinfect and quarantine banknotes before recirculating them. 

What began as a public-health response has matured into a structural shift toward digital payments. Consumers grew comfortable with notes and coins receding from daily life, and the convenience of digital alternatives did the rest.

The numbers reflect how durable that shift has become. Digital wallets now account for roughly half of global e-commerce transaction value, and the global mobile wallet user base is forecast to exceed 6 billion in 2030, more than half the world’s population.

Cashless and contactless payment methods were already gaining ground before COVID-19. But the crisis accelerated the shift to a new normal, and with it came a new set of anti-money laundering and countering the financing of terrorism (AML/CFT) risks for e-payment providers.

Below, we will explore the six key AML/CFT risks associated with cashless payments and how to mitigate them.

1. The rise of E-commerce

The behaviors formed during lockdowns have proven sticky. As of 2026, Latin America is the world’s fastest-growing e-commerce market, and Southeast Asia’s e-commerce market is projected to reach $325 billion by 2028; digital payments are expected to account for 94% of total e-commerce payments in the region by then. Real-time and account-to-account wallets are reshaping checkout in both regions.

The accessibility of online marketplaces such as Mercado Libre in Latin America, Amazon and eBay in North America and Europe, and Lazada, Shopee, and Alibaba across Asia makes it straightforward to set up a fake online store as a front or pass-through company, thereby increasing AML/CFT risk.

Aside from providing consumers with a secure platform to pay for their online purchases, e-payment providers now find themselves acting as a first line of defense against money laundering and fraudulent transactions. In practice, this means conducting customer due diligence (CDD) checks throughout each client’s lifetime and offering tokenization, among other measures. AI-driven customer risk scoring can further strengthen this process, automatically flagging anomalies in onboarding data that rule-based checks are more likely to miss.

eWallets and their AML risks

The surge in e-commerce activity in Asia has also led to increased adoption of eWallets. In the Philippines, where consumers have historically paid for online purchases through cash on delivery (COD), COVID-19 has forced consumers to turn to virtual wallets. GCash, the country’s largest mobile payments platform, saw a 150% surge in registered users between March and June 2020. 

However, AML eWallet compliance can vary widely from one platform to the other. Some eWallets may have inadequate customer identity verification measures. Others allow multiple users to access different eWallet accounts on one device. Either way, these exploits make eWallets susceptible to CFT/AML risks.

eWallet providers can protect their platform by implementing transaction monitoring for AML, identifying discrepancies in customer identity during registration, and flagging frequent and rapid cash withdrawals of funds moved between accounts.

2. eWallets and their AML risks

The surge in e-commerce activity worldwide has also driven the adoption of eWallets. In markets where consumers historically paid for online purchases through cash on delivery (COD), digital wallets have become the default. The Philippines is a clear example: GCash, the country’s largest mobile payments platform, has grown into one of the region’s most widely used financial apps, serving tens of millions of registered users. Also, in East Africa, M-Pesa processes some 33 billion transactions a year and serves over 60 million customers.

AML eWallet compliance can vary widely from one platform to the next. Some eWallets have inadequate customer identity verification measures. Others allow multiple users to access different eWallet accounts on a single device. Either way, these gaps make eWallets susceptible to AML/CFT risks.

eWallet providers can protect their platforms by implementing transaction monitoring for AML and identifying discrepancies in customer identity during onboarding and throughout the customer lifecycle. Where transaction volumes are high, agentic AI can triage alerts autonomously, resolving routine cases without analyst intervention and surfacing only the activity that warrants human review.

3. Prepaid cards and their AML risks

The accessibility of prepaid cards and the relative anonymity they afford, with no need to link to a bank account, makes them a target across all three money laundering stages: placement, layering, and integration. A common tactic is “smurfing,” where multiple cards are loaded with amounts below the know your customer (KYC) threshold.

Prepaid card providers can reduce this exposure by securing their virtual card management platforms and the cards themselves more effectively. Automated monitoring systems can be configured to detect structuring patterns across multiple cards in near real time, addressing the complexity of smurfing schemes that manual reviews and traditional software would miss.

4. Online money transfers and AML risks

Remittances have rebounded strongly since the early pandemic slump. Officially recorded remittances to low and middle-income countries reached an estimated $685 billion in 2024, surpassing foreign direct investment (FDI) and official development assistance (ODA) combined, and are forecast to grow further. Globally, digital apps are now firmly the preferred way to send and receive money across borders.

The rise of money transfer apps such as Remitly and Wise has made it easier to move money across borders and, in turn, easier for money launderers to do the same. Criminals can use money mules to move money on their behalf or use fake identity documents to bypass customer due diligence checks.

Remittance firms should implement automated transaction monitoring systems that automatically detect AML red flags, such as suspicious remittance patterns and transfers to high-risk countries and websites, by cross-referencing behavioral patterns and geographic risk signals simultaneously. AML compliance for online remittance services should also align with Financial Action Task Force (FATF) guidelines.

5. Online gaming and micropayments

Online games, particularly massively multiplayer online role-playing games, have long been viewed as an underreported avenue for money laundering due to their use of in-game credits, which effectively serve as virtual currency. Criminals break down a large sum by purchasing in-game currency, then sell those credits to gamers at a discount without triggering AML alerts. This scheme is known as micro-laundering.

With the right transaction monitoring rules in place, game developers can build systems to detect micro-laundering. The key is having the proper rules in the regulatory technology workflow to identify micro-laundering risks. This allows the AML system to flag not just large, single transactions, but also less obvious tactics, for example, hundreds of smaller transactions of $100 each. Agentic AI systems go further, learning from historical alert patterns to identify micro-laundering behavior that falls below fixed-rule thresholds and would otherwise go undetected.

6. Escrow services and their AML risks

Escrow services are used by online gig marketplaces, buy-and-sell platforms, and a range of online financial transactions, from buying a domain name to purchasing a vehicle. These services can be exploited to launder money through money mules.

For example, a user can post a freelancer “job” on a gig marketplace for the amount of money they need to launder. That same user can open another account with a different IP address, or have a money mule apply for the fake job. The job is marked complete, and the marketplace releases the now-laundered funds.

The most effective safeguard is to apply KYC procedures that verify the identity of every user, seller, or buyer involved when money is held in escrow. Though complex connections can be difficult to surface through manual due diligence alone. Automated identity verification and ongoing monitoring can detect when multiple accounts share behavioral or device-level characteristics.

Best practices for preventing e-payment AML risks

To ensure effective AML/CFT risk compliance, e-payment providers should implement automated, intelligent transaction-monitoring systems that analyze customer and transaction data to identify red-flag activity. Automated AML data solutions help identify risks before they become threats, reduce the risk of human error, and support ongoing compliance by adapting to global watchlist databases and changing legislation.

On an administrative level, e-payment providers need to be proactive in meeting all applicable licensing and registration requirements. By adapting to regulations and implementing policies that fit the new normal of payments, e-payment platforms can reduce the threat and potential damage of digital money laundering.