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11/07/2026 8:29 pm
TL;DR: Chinese-language money laundering networks now dominate known crypto laundering activity, processing an estimated 20% of illicit crypto funds over five years and $16.1 billion in 2025 across more than 1,799 wallets, according to Chainalysis. The scale, fragmentation, and rapid service migration show why disruption must focus on operators and channels, not just venues.
NHIMG editorial — based on content published by Chainalysis: Chinese-language money laundering networks now dominate illicit crypto flows
By the numbers:
- Chinese-language money laundering networks processed $16.1 billion in 2025 across 1,799+ active wallets.
- The share of known illicit laundering activity attributed to Chinese-language money laundering networks reached approximately 20% in 2025.
- Growth of inflows to identified Chinese-language money laundering networks since 2020 was 7,325 times faster than growth to centralized exchanges.
Questions worth separating out
Q: What breaks when laundering networks can rent financial identities at scale?
A: When laundering networks can rent financial identities at scale, KYC and account ownership assumptions stop being reliable.
Q: Why do laundering ecosystems keep growing even after enforcement actions?
A: They grow because enforcement often hits the venue, not the operator network.
Q: How do security teams spot fragmentation used to evade transaction monitoring?
A: Look for repeated small transfers that later converge into larger outbound movements, especially when the same identities, addresses, or communication channels recur.
Practitioner guidance
- Map the operator graph, not just the venue Build cases around linked handles, wallet clusters, Telegram identities, and reuse patterns across guarantee platforms, OTC desks, and mule services.
- Tune alerts for split-and-consolidate behaviour Add detection logic for rapid micro-fragmentation followed by consolidation into larger outbound transfers.
- Treat rented identity as a financial crime signal Escalate account rental, credential leasing, and wallet sharing as indicators of laundering facilitation.
What's in the full report
Chainalysis' full report covers the operational detail this post intentionally leaves for the source:
- Service-by-service breakdowns of running point brokers, money mules, OTC desks, Black U services, gambling services, and money movement services.
- On-chain behavioural fingerprints and typologies that help investigators distinguish one laundering service from another.
- Examples of how guarantee platforms, Telegram channels, and vendor reputations support the ecosystem without directly executing every transfer.
- The enforcement and disruption patterns that explain why networks migrate rather than disappear when one venue is targeted.
👉 Read Chainalysis' analysis of Chinese-language money laundering networks and illicit crypto flows →
Chinese-language money laundering networks: what practitioners need to know?
Explore further
11/07/2026 8:59 pm
Chinese-language laundering has become a trust-management problem, not just a transaction-monitoring problem. The report shows that vendors, marketplaces, and reputation signals now act as a parallel trust layer for illicit finance. That is structurally similar to how credential marketplaces and shadow access brokers operate in cybercrime. Practitioners should therefore look at the identity and reputation mechanics that make laundering services scalable, not only the movement of funds.
A question worth separating out:
Q: Who is accountable when laundering services move across platforms and jurisdictions?
A: Accountability should sit with the institutions that onboard, enable, or process the activity, not only the marketplace where it is advertised. That includes exchanges, payment providers, and platform operators with KYC, monitoring, and offboarding obligations. Cross-border coordination is essential because displacement across jurisdictions is part of the operating model.
👉 Read our full editorial: Chinese-language money laundering networks now dominate illicit crypto flows
