By Nilabh Ohol, VP of Product, FiVerity
Financial institutions have never had more sophisticated tools to detect fraud and money laundering. Transaction monitoring, behavioral analytics, and risk models work remarkably well when threats live inside an institution’s four walls. But today’s most dangerous criminal networks don’t live there anymore.
Recent findings from the U.S. Treasury’s Financial Crimes Enforcement Network (FinCEN) show how far these threats have spread beyond institutional visibility. Between 2020 and 2024, banks filed over 137,000 suspicious activity reports tied to Chinese money laundering networks (CMLNs), representing more than $312 billion in suspect flows.
These networks quietly launder cartel funds through “mirror transactions” and mule accounts, often held by unsuspecting students or retirees, using legitimate payment rails like Debit Cards, Crypto Wallets, P2p methods (Zelle, etc), and many other mobile apps.
A recent investigation by The Epoch Times described this as the “Student Mule Economy”: thousands of legitimate accounts, each appearing normal in isolation, collectively moving billions through U.S. banks. To any one institution, the activity looks benign. Only when viewed across multiple institutions do the linkages become clear.
These are precisely the kinds of threats today’s siloed defenses can’t see, and the ones that secure, AI-enabled collaboration was built to uncover.
The Institutional View: Effective, but Limited
Most financial institutions operate from what can be called an institutional view of financial crime.
They’ve mastered what’s visible within their own perimeter:
- Traditional fraud detection systems catch known typologies such as account takeover or card fraud.
- Behavioral analytics detect anomalies using internal customer data.
- Vendor consortiums provide some external context but limited reach.
These tools are vital for detecting familiar fraud patterns, but they all share one constraint: they only see what happens within a single institution or vendor ecosystem. That’s why sophisticated identity fraud (SIF), scams, and mule networks thrive and each institution sees only its own fragment, while the larger choreography goes unnoticed.
The Connected Lens: How Financial Crime Actually Operates
The latest FinCEN analysis shows how these laundering schemes really work. CMLNs connect Mexican cartels holding U.S. cash with Chinese citizens seeking U.S. dollars beyond China’s foreign exchange limits. The result is a “mirror economy,” where value moves across borders without money ever crossing the system.
Today’s version uses payment apps, small-dollar transfers, and legitimate consumer banking channels.
Each transaction looks normal. But taken together, they reveal a sprawling network that moves cartel profits, bypasses currency controls, and undermines trust in financial systems designed for transparency.
Every dashboard in the sector answers one question: What’s happening in my data? But the question that now matters most is: What’s happening outside my data that affects me?
That’s the blind spot. The institutional view can’t detect hidden links, such as shared devices, mule accounts, or cross-institution flows, that define today’s financial crime networks. A connected shared intelligence lens is what reveals them to investigators.
The Structural Problem: Fragmented Defenses
This isn’t a failure of technology; it’s a failure of perspective. Financial institutions and vendors operate within closed systems. Fraud, AML, and compliance teams rarely share intelligence in real time, even inside their own organizations. Across industries, banking, fintech, and crypto, those gaps widen.
FinCEN’s report highlights accounts belonging to students, homemakers, and retirees that easily pass KYC checks but later show high turnover, linked devices, and proximity to money service businesses. These signals only emerge when viewed collectively.
Without a mechanism to connect those dots across systems and sectors, institutions are left detecting symptoms rather than dismantling the networks behind them.
Why Collaboration Has Finally Become Possible
For decades, efforts to connect fraud and AML defenses have been blocked by three hard realities:
- Data privacy and regulatory risk made information sharing nearly impossible.
- Integration complexity made cross-institution collaboration costly and slow.
- Trust barriers kept financial institutions from sharing insights beyond consortiums or regulators.
That’s changed. Advances in privacy-preserving computation, federated data models, and lightweight secure connectors now enable real-time, compliant intelligence exchange without exposing sensitive data or requiring resource-heavy integrations. What was once theoretical — a connected, secure layer of collaboration — is now operational. For the first time, financial institutions can exchange fraud intelligence in real time, securely and compliantly, without losing control of their data.
A Shift Toward Shared Defense
With these advances, collaboration no longer requires compromise. The barriers that once made information-sharing slow, risky, or impractical are gone — and the path to a connected defense is finally open. To close this gap, the industry needs a connected lens — one that views fraud from the ecosystem’s perspective rather than the institution’s. That means correlating intelligence across systems, peers, and industries, using privacy-preserving technology that protects customer data while exposing shared risks.
The timing is critical. Instant payments, stablecoins, and embedded banking partnerships have expanded both the speed and surface area of financial crime. Meanwhile, AI-generated identities, cloned voices, and deepfakes are industrializing fraud faster than institutions can adapt.
Traditional tools, built to flag anomalies in known channels, struggle to detect synthetic identities moving seamlessly between fiat, fintech, and crypto rails.
Regulators are taking notice. The OCC’s 2023 bulletin on sponsor-bank oversight underscores the need for stronger monitoring of fintech partners. The Financial Action Task Force (FATF) has called cross-industry collaboration a “missing link” in AML enforcement.
The message is clear: defending against the next generation of financial crime requires collective visibility, not just individual vigilance and tooling.
The Way Forward
The future of fraud prevention won’t be defined by how well each institution defends itself, but by how effectively the industry defends together.
By turning fragmented data into connected intelligence, financial institutions move from compliance to collective defense — identifying linkages and repeat offenders that traditional systems can’t see.
Fraudsters already operate in complex networks. Until the financial system responds the same way, our defenses will remain one step behind.
About the Author
Nilabh Ohol is VP of Product at FiVerity, an AI-native, financial crime collaboration platform that provides the infrastructure and tooling to connect systems, partners, industry defenses, and regulators to detect and prevent complex financial crime through shared intelligence.