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Reading: Chinese-Language Money Laundering Networks Process $16.1B
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Blockchain Technology

Chinese-Language Money Laundering Networks Process $16.1B

Last updated: January 27, 2026 9:05 pm
Published: 2 hours ago
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Tanzeel Akhtar has been reporting on cryptocurrency and blockchain technology since 2015. Her work has appeared in leading publications including The Wall Street Journal, Bloomberg, CoinDesk, Bitcoin…

The illicit on-chain money laundering ecosystem has expanded rapidly over the past five years, growing from roughly $10 billion in 2020 to more than $82 billion in 2025, according to Chainalysis’ latest 2026 Crypto Crime Report.

Chainalysis said the sharp increase reflects the growing accessibility and liquidity of cryptocurrencies, alongside a shift in how laundering activity is conducted and who is facilitating it.

The firm noted that laundering services have become more sophisticated, industrialized and increasingly embedded in global criminal networks.

Chinese-Language Networks Now Account for 20% of Known Laundering

Chainalysis found that Chinese-language money laundering networks (CMLNs) have increased their share of attributed illicit laundering activity to around 20% in 2025.

These networks have also become a key endpoint for scam proceeds. Chainalysis noted that CMLNs now consistently launder more than 10% of funds stolen in pig butchering scams, as criminals shift away from centralized exchanges, which can freeze assets.

Since 2020, inflows to identified CMLNs have grown 7,325 times faster than those to centralized exchanges, far outpacing growth in DeFi-related laundering and intra-illicit transfers.

Chainalysis said Telegram-based services operating in Chinese-language channels now account for a disproportionate share of the global laundering landscape.

CMLN Ecosystem Processed $16.1B Through 1,799 Wallets

Chainalysis identified six major service types within the CMLN ecosystem, which together processed $16.1 billion in inflows during 2025. The number of active entities has risen sharply reaching more than 1,799 active on-chain wallets last year.

The report highlights the speed at which these operations scale. “Black U” services reached $1 billion in processing volume in just 236 days, while other typologies such as OTC desks and money mule networks scaled over longer periods.

Chainalysis estimates the ecosystem is processing nearly $44 million per day showing the industrial capacity of these networks.

Guarantee Platforms Anchor a Sophisticated Underground Market

At the center of the ecosystem are “guarantee platforms,” which function as marketing and escrow hubs connecting laundering vendors with buyers. Chainalysis said services such as Huione and Xinbi have dominated this market, even as enforcement actions disrupt individual accounts.

Vendors offer a wide range of laundering techniques, including running point brokers, money mule “motorcades,” informal OTC services, Black U discounted illicit crypto sales, gambling-linked laundering, and mixing and swapping-as-a-service.

Chainalysis noted that these networks demonstrate resilience, often migrating across platforms when challenged, while maintaining operational continuity.

Enforcement Actions Highlight Growing National Security Threat

Recent sanctions and advisories have drawn attention to the national security risks posed by laundering facilitation networks. Chainalysis pointed to actions including OFAC’s designation of the Prince Group, FinCEN’s rule targeting Huione Group, and advisories on Chinese money laundering networks.

Experts cited in the report warned that crypto has allowed rapid cross-border movement of illicit funds. Chainalysis concluded that disrupting these networks will require coordinated public-private collaboration, combining blockchain analytics, intelligence sharing, and proactive targeting of underlying operators rather than individual platforms alone.

Chainalysis emphasized that on-chain transparency offers unprecedented visibility — but only if matched with global enforcement capacity and systemic cooperation.

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