Dramatic illustration of Chinese Telegram-based crypto laundering networks handling $16.1 billion in illicit funds, per Chainalysis report.
Dramatic illustration of Chinese Telegram-based crypto laundering networks handling $16.1 billion in illicit funds, per Chainalysis report.
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Chinese-language networks laundered $16.1 billion in crypto in 2025

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A new report from blockchain analytics firm Chainalysis reveals that Chinese-language money laundering networks processed $16.1 billion in illicit cryptocurrency funds last year, accounting for about 20% of all known crypto laundering activity. These Telegram-based operations have grown dramatically since 2020, outpacing other laundering channels by thousands of times. The findings highlight the networks' role in facilitating global crime while evading enforcement efforts.

Chainalysis released its 2026 Crypto Crime Report on January 27, detailing the rise of Chinese-language money laundering networks (CMLNs). In 2025, these networks handled $16.1 billion in inflows—roughly $44 million per day—across more than 1,799 active wallets. This represents a surge from $10 billion in total on-chain laundering in 2020 to $82 billion in 2025, with CMLNs capturing 20% of the activity.

The report identifies six key service types within the CMLN ecosystem: running point brokers, which recruit individuals to rent bank accounts for initial fund placement; money mule motorcades for layering funds through networks of accounts; informal OTC services offering KYC-free transfers; Black U services selling tainted crypto at 10-20% discounts; gambling platforms for high-volume transactions; and money movement services providing mixing and swapping. Guarantee platforms like Huione and Xinbi act as central hubs, offering escrow and marketing, though they do not control the laundering itself.

Growth has been explosive: inflows to CMLNs expanded 7,325 times faster than to centralized exchanges since 2020. On-chain patterns mirror traditional laundering phases—placement, layering, and integration—with Black U services fragmenting large sums to evade detection, clearing very large transactions in just 1.6 minutes on average in Q4 2025.

Experts attribute this to China's capital controls, which drive wealthy individuals to seek evasion routes, fueling transnational crime. Tom Keatinge, director at the Centre for Finance & Security at RUSI, said, “Very rapidly, these networks have developed into multi-billion dollar cross-border operations offering efficient, value-for-money laundering services.” Chris Urben of Nardello & Co noted crypto's efficiency over traditional systems, allowing billions to be moved via cold wallets.

Regulatory actions include U.S. Treasury sanctions on the Prince Group and FinCEN's designation of Huione as a primary money laundering concern. However, vendors migrate to alternative platforms, underscoring the need for public-private collaboration to target operators directly.

Was die Leute sagen

X discussions focus on Chainalysis' 2026 Crypto Crime Report preview, noting Chinese-language networks laundered $16.1 billion in illicit crypto in 2025, equating to $44 million daily across nearly 1,800 wallets and 20% of global activity. Sentiments include alarm at the scale of organized crime, concerns over reputational damage to crypto and calls for regulation, defenses citing growth in adoption outpacing crime stats, and praise for analytics aiding enforcement and victims.

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Illustration of crypto crime surge: hackers using AI to steal $17B in scams per Chainalysis report, with charts, bitcoins, and law enforcement seizures.
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Chainalysis 2026 Report: $17 Billion in 2025 Crypto Scams Amid Surging AI Fraud and Hacks

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Experts from blockchain intelligence firm NOMINIS.io have revealed how Iran's regime employs cryptocurrencies to evade Western sanctions, funding proxy groups in the region. By selling oil to Russia and China for digital payments, Iran maintains economic flows despite restrictions. This network also facilitates activities like espionage, as seen in a recent Israeli indictment.

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