Money laundering typologies — what emerging patterns are you seeing?

Our training program needs an update on current money laundering typologies. The traditional ones (structuring, layering through shell companies, trade-based ML) are well covered but I feel like we're behind on newer patterns.

What emerging laundering methods are you seeing in practice right now? Particularly interested in:

• Crypto-enabled schemes
• Anything involving DeFi or stablecoins
• Novel uses of legitimate fintech platforms for layering
• Real estate methods that have evolved

Also — does anyone reference FATF typology reports in their training? Are they practical enough to be useful or too academic?

Good timing on this — money laundering typologies are evolving quickly. Here's what we're tracking:

Crypto-enabled schemes:

• Chain hopping — Moving funds across multiple blockchains to break the transaction trail. Launderers convert from one crypto to another through decentralized exchanges where KYC is minimal or nonexistent.
• Mixing/tumbling — Still prevalent despite law enforcement takedowns. Newer mixing services use more sophisticated algorithms.
• NFT wash trading — Using NFT sales to move value between wallets with artificial transaction histories.

Fintech exploitation:

• Multi-platform layering — Using a combination of neobanks, P2P payment apps, and prepaid cards to layer funds. Each platform sees only a fragment of the overall flow.
• Mule account networks — Recruitment of money mules through social media and job boards, using their legitimate fintech accounts to move funds.

Traditional with a twist:

• Nested shell company structures — Corporate layering using jurisdictions with poor registry transparency
• Real estate through LLCs — Not new, but increasingly using layers of LLCs to obscure beneficial ownership even in jurisdictions implementing the Corporate Transparency Act

The FATF reports on these patterns are worth reading — they're based on real cases from member countries. The 2023 report on crypto-enabled laundering was particularly useful. They're not perfect for training directly but they're good source material that you can adapt into case studies.

For training, we'd recommend building scenarios from actual enforcement actions (FinCEN, DOJ press releases) rather than abstract descriptions. Real cases stick with analysts better than theoretical frameworks.

On the FATF reports — I use them as a starting point and then adapt. The raw typologies are too generic for analyst training. What works better is taking the FATF money laundering typologies and mapping them to your specific institution's product set. "Here's the typology, and here's exactly how it could manifest in OUR wire transfer system / OUR commercial lending / OUR mobile banking."

Makes it way more actionable than abstract descriptions of money laundering methods.