As seen in Part 1 of this article, money laundering has shifted from shell firms to fast, digital and cross-border platforms. Criminals now exploit instant payments, creator-economy tipping, gaming assets, non-fungible tokens (NFTs), and cross-chain crypto to obscure illicit funds. Stablecoins, with 24/7 liquidity and weak oversight, have become key laundering tools, while embedded finance, buy-now-pay-later (BNPL) wallets, luxury resellers, and even football clubs create new blind spots. Criminals exploit instant settlement, fragmented supervision, and jurisdictional gaps to move funds before anti-money laundering (AML) checks react, often using AI-driven social engineering to recruit money mules.
Many new measures have already been introduced to curb money laundering through non-traditional channels, as outlined in Part 1. However, in all likelihood, they will not be enough. So, what more could be done? This article expands seven ideas that look forward beyond what is already in place and seek to greatly reduce the incidence of money laundering across the UK and the EU.
What more could be done in future?
- Cross-chain “Travel Rule” Interoperability
To stem illicit flows via multi-chain bridges and DeFi, firms must embed message-level standards so that virtual asset service providers (VASPs) and bridging platforms exchange full originator and beneficiary data across chains. The Financial Action Task Force’s “Travel Rule” (Recommendation 16) already mandates that VASPs collect and transmit sender and recipient details when transferring virtual assets.
However, current practice remains fragmented: multiple messaging protocols exist and VASPs may struggle to talk to one another. For example, one exchange on Ethereum sending funds through a bridge to a Solana-based wallet may not carry the required originator data because the receiver uses a different Travel-Rule protocol.
Interoperability means adopting a universal message-format like IVMS101 and ensuring all regulated bridges and VASPs globally honour the standard, so that a transfer from Chain A to Chain B carries the same customer-data payload and meets AML/ combatting the financing of terrorism (CFT) controls end-to-end.
- Real-time AML for Instant Payments
To tackle money-laundering risks inherent in instant-payment systems, businesses must shift from traditional post-settlement reviews to a real-time-first model. For example, applying the same mindset used in card-fraud, where transactions can be blocked before authorisation, firms should deploy pre-credit interdiction, running screening checks before a payment clears. Sharing negative lists of flagged mule accounts across banks enables rapid interdiction when a customer attempts a fragmented funding run. Firms like Napier AI warn that “Pre-validation means knowing who is sending funds, who is receiving funds, and what wallets or accounts are involved” before settlement.
In practice, a UK or EU payment service provider must aim for screening service level agreements (SLAs) of around 10 seconds to match instant-payment finality. According to the white-paper from IMTF Partners, “Real-time AML is emerging as a key capability to detect and prevent suspicious activity before the damage is done.”
- Obligations for Platform Economies
As traditional banks face ever-tightening scrutiny, the focus must shift to platform economies (creator platforms, online marketplaces and gaming operators) when they facilitate value transfers. The Council of the European Union has extended AML obligations to “obliged entities” such as high-value goods traders, sports clubs and agents under the new AML package.
In practice, a creator-economy platform enabling micro-donations or tipping should conduct proportionate customer-due-diligence (CDD), monitor large or unusual flows and maintain records on beneficiaries. For example, a marketplace for luxury bags might now verify buyers and sellers, flag rapid resales and report suspicious instalments. A gaming-platform enabling in-game currency transfers must treat accumulations of transfers from new accounts as red flags. By applying behavioural monitoring and CDD akin to banks, these platforms become proactive gatekeepers rather than passive conduits of illicit funds.
- Beneficial-ownership that actually bites
Under the reforms brought in by the Economic Crime and Corporate Transparency Act 2023, the UK is pushing beyond simply listing beneficial-owners to making the data verifiable and actionable. Companies House now requires directors and persons with significant control (PSCs) to verify their identity via GOV.UK One Login, with full compliance due by 18 November 2025.
This means real-world checks, not just box-ticking. For example, a small and medium-sized enterprise (SME) registered in England must now ensure its PSC gives a unique personal code when filing—a failing may lead to penalties or disqualification. Meanwhile, the register of overseas entities forces all non-UK companies owning UK land to disclose verified beneficial-owners.
Firms conducting CDD will have bulk access to this enriched data set and can cross-match it against customer profiles or transaction flows, making the once-opaque ownership chain suddenly transparent and enforceable.
- Public-private “fusion” centres
A future-focused pillar for disrupting modern laundering is the establishment of formal public-private “fusion” centres: joint hubs where banks, payment service providers (PSPs), crypto-exchanges and law-enforcement pool analytics to monitor instant-payments typologies, mule-network schemata and cross-chain risk signals. In the UK, seven major banks already share customer data under a law-enforcement initiative, revealing new crime networks. At the EU level, the European Financial Intelligence Public‑Private Partnership (EFIPPP) serves as an example of transnational collaboration in AML intelligence.
Building on this, the Authority for Anti‑Money Laundering and Countering the Financing of Terrorism (AMLA) could convene EU-wide playbooks, formalising standardised threat-scenarios, data-sharing protocols and rapid-response workflows. In practice, a fusion centre could flag when a PSP sees a pattern of many small transfers to newly opened accounts, while a crypto-exchange’s chain-analysis tool detects bridging into gaming assets—all enabling law-enforcement and industry to act before funds vanish.
- Outcome-based crypto conduct rules
As the Markets in Crypto‑Assets Regulation (MiCA) regime beds in, the next generation of regulation must pair authorisation requirements with robust marketing-conduct standards and stablecoin oversight. For instance, under the Financial Conduct Authority’s (FCAs) new crypto-asset financial promotion rules, firms must ensure marketing is “fair, clear and not misleading.”
But going further, outcome-based rules should hold platforms accountable for positive consumer and integrity outcomes: e.g., a crypto-exchange must not just be authorised under MiCA or UK draft law, but also ensure its stablecoin offerings are fully backed, transparent and redeemable on demand, thereby reducing abuse of high-liquidity rails. As the UK consultation paper highlights, stablecoin issuers will face liquidity and redemption obligations. In practice, a UK or EU regulator might sanction a crypto-service provider that markets a “stable” token without backing proof or encourages retail purchases via credit, thereby implementing a regime based on behavioural outcomes, not mere box-ticking.
- AI for detection—safely
To counter evolving money-laundering tactics like micro-smurfing and cross-chain chain-hopping, firms must invest in explainable AI models that offer transparency and auditability. For example, graph-based algorithms now identify clusters of small rapid transfers across accounts, indicative of deposit layering, while deep-learning modules detect deep-fake-enabled onboarding fraud. One recent study highlights a “GARG-AML” model offering interpretable smurfing detection. Meanwhile Europol warns that criminals are using generative AI for impersonation and to scale payments schemes.
In practice, banks and crypto-exchanges must deploy systems that not only flag anomalies but provide clear reasoning (“why this looks suspicious”) so compliance teams can act confidently and regulators can challenge decisions. Prioritising “safe AI” means embedding human oversight, transparency logs and bias audits—so the shield becomes as strong as the weapon.
And what about you…?
- How confident are you that your organisation’s current AML systems can detect laundering through non-traditional channels such as gaming platforms, creator economies or instant payments?
- Looking ahead five years, what area of your business do you think criminals are most likely to target for money laundering and how can you pre-empt that risk now?
