The world of cryptocurrency is increasingly shadowed by sophisticated money laundering operations, and a new report reveals the scale of the problem. Chinese-based money laundering networks (CMLNs) have rapidly emerged as a dominant force in moving illicit funds globally, fundamentally altering how criminal proceeds are concealed and transferred.
$16.1 Billion in Laundering by 2025: The Industry’s Largest Channel
Table of Contents
- $16.1 Billion in Laundering by 2025: The Industry’s Largest Channel
- How These Networks Operate: Six Key Service Types
- A Familiar Pattern: Echoes of Traditional Money Laundering
- Assurance Platforms: The Hub of the Ecosystem
- Regulatory Response and Ongoing Challenges
- Expert Insights
- The Need for Collaboration
According to a report released January 27, CMLNs now account for approximately 20% of all known cryptocurrency money laundering activity. These networks are projected to process $16.1 billion in 2025—that’s roughly $44 million every single day—facilitated through over 1,799 active wallets. Since 2020, the growth of inflows into CMLNs has dramatically outpaced other methods, increasing 7,325 times faster than centralized exchanges, 1,810 times faster than decentralized finance (DeFi), and 2,190 times faster than overall illegal on-chain inflows.
How These Networks Operate: Six Key Service Types
Researchers have identified six distinct service types that comprise the CMLN ecosystem, each playing a specific role in the laundering process. These include running point brokers, money mule convoys, unofficial over-the-counter (OTC) services, “black U” services, gambling services, and money movement services.
Running Point Brokers: The Initial Entry
These brokers serve as the first point of contact for illicit funds, recruiting individuals to lease their bank accounts, digital wallets, or exchange deposit addresses to receive or deliver criminal proceeds.
Money Mule Convoys: Layering the Funds
Responsible for the “layering” phase of money laundering, these convoys create networks of multiple accounts and wallets to obscure the original source of the funds. Some operators have even expanded their reach into five African countries.
Unofficial OTC Services: ‘Clean Funds’ Without Scrutiny
Advertising “Clean Fund” or “White U,” these services process fund transfers without the typical “Know Your Customer” (KYC) verification procedures. However, on-chain analysis has revealed strong connections between these services and illicit platforms like Hui One.
Black U Services: Discounted ‘Tainted’ Crypto
Specializing in cryptocurrencies obtained through hacking, exploits, and fraud, “Black U” services sell these “tainted” funds at a 10-20% discount. This service has experienced the fastest growth, reaching $1 billion in cumulative inflows in just 236 days. In the fourth quarter of 2025, large transactions settled in an average of only 1.6 minutes.
Gambling Services: Obscuring Funds Through High Volume
Leveraging the high cash flow and frequent transactions inherent in online gambling, these services are used to launder funds. Some Telegram-based sellers have even been found to manipulate results.
Money Movement Services: Mixing and Exchange
Providing mixing and exchange capabilities, these services operate in Southeast Asia, China, and North Korea, and are actively utilized by illicit actors.
A Familiar Pattern: Echoes of Traditional Money Laundering
On-chain data reveals that the flow of funds within CMLNs closely mirrors the traditional stages of money laundering: placement, layering, and consolidation. The “Black U” service, in particular, exhibits aggressive “smurfing” behavior—breaking up large sums into smaller transactions—with outflows under $100 increasing 467% compared to inflows. Medium transactions ($100 to $1,000) rose by 180%, and for remittances exceeding $10,000, there were 51% more receiving wallets than sending wallets.
Gambling insiders, running point brokers, and OTC services act as central hubs, pooling funds from various channels and creating a wholesale foundation for re-entry into the legitimate financial system.
Assurance Platforms: The Hub of the Ecosystem
At the core of the CMLN ecosystem are assurance platforms like Hui One and Sinbi. These platforms provide marketing and escrow infrastructure for money laundering sellers, but do not directly control the laundering activities themselves.
Even after Telegram removed some Hui One accounts, sellers quickly migrated to other platforms, demonstrating the need to focus on the operators themselves, rather than simply targeting the platforms they use.
Regulatory Response and Ongoing Challenges
Recent enforcement actions include the US Treasury’s Office of Foreign Assets Control (OFAC) and the UK’s Office of Financial Sanctions Implementation (OFSI) designating Prince Group as a target of sanctions. FinCEN issued a final rule designating Huiwen Group as a major money laundering concern and released an advisory regarding Chinese money laundering networks.
Despite these measures, the core network persists and adapts, finding alternative routes when pressured.
Expert Insights
Tom Keating, Director of the Center for Finance and Security at the UK’s Institute for Defense and Security Strategy, noted that these networks have rapidly grown into multibillion-dollar cross-border businesses. “China’s capital controls have fueled rapid growth, while wealthy individuals seeking to evade them provide liquidity and incentive for criminal organizations operating between Europe and North America,” Keating explained.
Chris Urban, Executive Director at Nardello & Co., highlighted the rapid shift from traditional informal money transfer systems to cryptocurrency in recent years. “Cryptocurrencies have less stringent KYC procedures than banks, and are very efficient as billions of dollars can be moved across borders with just a cold wallet stored on a hard disk,” Urban said.
The Need for Collaboration
Chainalysis emphasizes that effectively combating these cryptocurrency-linked money laundering networks requires proactive measures to disrupt the underlying network, rather than simply cracking down on individual platforms after the fact.
Urban advises combining open-source and human intelligence with blockchain analytics to detect these networks. “Only when these tools work together and develop leads that connect information to each other can we uncover networks by connecting players and money flows,” he says.
