Crypto Money Laundering to Exceed $82B by 2025, Driven by Chinese Services

VADODARA, January 27, 2026 — On-chain money laundering is projected to surge from $10 billion in 2020 to over $82 billion by 2025, according to a forecast by blockchain data analytics firm Chainalysis. The report, which analyzes illicit fund flows across major blockchains, attributes this exponential growth to increased market liquidity and the professionalization of laundering networks with Chinese roots. This latest crypto news highlights a critical vulnerability in the global financial system as digital assets mature.

Investigation: The Scale and Drivers of Illicit Flows

Chainalysis data indicates the scale of cryptocurrency money laundering expanded rapidly over the past five years. The firm's forensic tools track transactions from identified illicit addresses to off-ramps like exchanges. Consequently, they identified a trend largely driven by services with Chinese roots. The Chinese-language money laundering network (CMLN) now accounts for approximately 20% of all known illicit activities. These networks operate openly across messaging platforms and various blockchains, leveraging cross-chain bridges and privacy tools.

Chainalysis attributed the rapid growth to two primary factors. First, increased liquidity in the cryptocurrency market provides larger pools of capital to obscure. Second, the professionalization of laundering services has created efficient, scalable operations. These services often use structured transaction patterns to bypass basic compliance checks at centralized exchanges. Market structure suggests this professionalization mirrors the maturation of legitimate DeFi protocols, but applied to illicit ends.

Market Context & Historical Precedent

Historically, illicit activity has correlated with bull market cycles. The 2017 cycle saw a spike in ransomware payments denominated in Bitcoin. In contrast, the 2021 cycle involved more sophisticated DeFi exploits and NFT wash trading. Underlying this trend is the fundamental tension between blockchain transparency and pseudonymity. While all transactions are public, linking addresses to real-world identities remains a challenge for law enforcement without sophisticated chain analysis.

This report emerges amid a broader regulatory clampdown. For instance, recent actions by the U.S. Treasury's Financial Crimes Enforcement Network (FinCEN) have targeted mixers like Tornado Cash. You can review related regulatory perspectives in the ASIC 2026 outlook on crypto risks. , the growth of Layer-2 ecosystems, detailed in our coverage of the Citrea mainnet launch, presents new challenges for monitoring cross-chain flows.

Technical Architecture & Forensic Analysis

On-chain forensic data confirms that laundering networks exploit specific technical vulnerabilities. They frequently use cross-chain bridges to move funds between Ethereum, Binance Smart Chain, and emerging networks. This creates complex transaction graphs that obscure the origin of funds. Analysts often identify laundering patterns by clustering addresses based on behavioral heuristics and common input ownership.

A critical technical detail not in the source is the use of "UTXO fragmentation" on Bitcoin. Launderers split large illicit outputs into thousands of smaller UTXOs to avoid detection algorithms that flag large, sudden movements. Consequently, blockchain analysts must deploy advanced clustering techniques that consider transaction graph topology and timing patterns. The professionalization noted by Chainalysis likely involves custom smart contracts that automate this fragmentation across multiple blockchains.

By The Numbers

Why It Matters

This surge in illicit flows directly impacts market integrity and regulatory perception. High volumes of money laundering can deter institutional adoption, as compliance teams flag jurisdictional risks. , it pressures regulators to implement stricter KYC/AML rules for all crypto services, potentially increasing operational costs. For retail investors, this reinforces the importance of using regulated exchanges that employ chain analysis tools.

Institutional liquidity cycles may face headwinds if regulatory responses are overly broad. For example, harsh measures could limit access to decentralized protocols, affecting legitimate yield farming strategies. The report's timing is significant, as it precedes potential policy announcements from bodies like the Financial Action Task Force (FATF). You can explore how market fear impacts funding in related sectors, such as the $7M raise for tokenized gold by Tenbin Labs.

Expert Commentary

"The projection of $82 billion in laundering by 2025 isn't just a number—it's a signal of market maturation gone awry. It reflects how illicit actors have institutionalized their operations, mirroring the professionalization we see in legitimate crypto ventures. This will force a reckoning in regulatory circles, likely accelerating the adoption of real-time transaction monitoring mandates for VASPs globally."

Market Outlook & Price Scenarios

Market structure suggests two primary scenarios based on regulatory response to this data.

• Bullish Invalidation Level: A break above key regulatory resistance, such as the implementation of clear, non-punitive global standards from bodies like the International Organization of Securities Commissions (IOSCO). This would reduce uncertainty and potentially unlock institutional capital, supporting prices.
• Bearish Invalidation Level: A failure to hold current regulatory support, indicated by a wave of punitive, fragmented regulations across major economies (e.g., the U.S., EU, and Asia). This could trigger a liquidity grab as institutions pause deployments, testing lower price supports.

The 12-month institutional outlook hinges on whether regulators target specific bad actors or impose broad restrictions. A surgical approach that dismantles networks like the CMLN while preserving innovation could foster a healthier market. Over a 5-year horizon, the integration of advanced analytics into blockchain protocols themselves—through zero-knowledge proofs for compliant privacy—may offer a technical solution to this systemic challenge.