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Chinese-Language Money Laundering Networks Processed $16.1B in Illicit Crypto: Chainalysis

The illicit on-chain cash laundering ecosystem has expanded quickly over the previous 5 years, rising from roughly $10 billion in 2020 to greater than $82 billion in 2025, in keeping with Chainalysis’ latest 2026 Crypto Crime Report.

Chainalysis stated the sharp enhance displays the rising accessibility and liquidity of cryptocurrencies, alongside a shift in how laundering exercise is carried out and who’s facilitating it.

The agency famous that laundering providers have turn into extra refined, industrialized and more and more embedded in world legal networks.

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

Chainalysis discovered that Chinese-language money laundering networks (CMLNs) have elevated their share of attributed illicit laundering exercise to round 20% in 2025.

These networks have additionally turn into a key endpoint for rip-off proceeds. Chainalysis famous that CMLNs now constantly launder greater than 10% of funds stolen in pig butchering scams, as criminals shift away from centralized exchanges, which might freeze property.

Since 2020, inflows to recognized CMLNs have grown 7,325 instances quicker than these to centralized exchanges, far outpacing progress in DeFi-related laundering and intra-illicit transfers.

Chainalysis stated Telegram-based providers working in Chinese-language channels now account for a disproportionate share of the worldwide laundering panorama.

CMLN Ecosystem Processed $16.1B Through 1,799 Wallets

Chainalysis recognized six main service varieties throughout the CMLN ecosystem, which collectively processed $16.1 billion in inflows throughout 2025. The variety of lively entities has risen sharply reaching greater than 1,799 lively on-chain wallets final 12 months.

The report highlights the velocity at which these operations scale. “Black U” providers reached $1 billion in processing quantity in simply 236 days, whereas different typologies corresponding to OTC desks and cash mule networks scaled over longer intervals.

Chainalysis estimates the ecosystem is processing practically $44 million per day exhibiting the commercial capability of those networks.

Guarantee Platforms Anchor a Sophisticated Underground Market

At the middle of the ecosystem are “assure platforms,” which operate as advertising and escrow hubs connecting laundering distributors with patrons. Chainalysis stated providers corresponding to Huione and Xinbi have dominated this market, at the same time as enforcement actions disrupt particular person accounts.

Vendors supply a variety of laundering methods, together with operating level brokers, cash mule “motorcades,” casual OTC providers, Black U discounted illicit crypto gross sales, gambling-linked laundering, and mixing and swapping-as-a-service.

Chainalysis famous that these networks display resilience, usually migrating throughout platforms when challenged, whereas sustaining operational continuity.

Enforcement Actions Highlight Growing National Security Threat

Recent sanctions and advisories have drawn consideration to the nationwide safety dangers posed by laundering facilitation networks. Chainalysis pointed to actions together with OFAC’s designation of the Prince Group, FinCEN’s rule concentrating on Huione Group, and advisories on Chinese cash laundering networks.

Experts cited in the report warned that crypto has allowed fast cross-border motion of illicit funds. Chainalysis concluded that disrupting these networks would require coordinated public-private collaboration, combining blockchain analytics, intelligence sharing, and proactive concentrating on of underlying operators relatively than particular person platforms alone.

Chainalysis emphasised that on-chain transparency presents unprecedented visibility—however provided that matched with world enforcement capability and systemic cooperation.

The publish Chinese-Language Money Laundering Networks Processed $16.1B in Illicit Crypto: Chainalysis appeared first on Cryptonews.

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