Advanced Investigative Analytics to Reveal Fentanyl-Related Financial Crime Networks

Applying DataWalk to Fentanyl-Related Financial Crime

The hallmarks of fentanyl money laundering, including high-risk chemical purchases, shell companies, Chinese Money Laundering Organizations (CMLOs), and crypto layering, can only be seen when investigators can correlate data across banking systems, trade documents, blockchain ledgers, open-source intelligence, and other data sources. DataWalk transforms this complex process into actionable intelligence by providing a unified platform for analysis.

1. Linking Narcotics Proceeds to Precursor Purchases

Investigators can ingest transaction data, shipping manifests, and letters of credit directly into DataWalk’s central knowledge graph . From there, powerful visual queries uncover hidden connections between narcotics proceeds and payments to chemical suppliers. Patterns that once hid in spreadsheets become instantly visible, such as repeated small payments to high-risk jurisdictions labeled “industrial supplies” or front companies receiving large transfers without corresponding business activity. By mapping entities and relationships in one unified graph, analysts can finally see how the same funds thread through multiple accounts to finance precursor purchases, the financial lifeblood of synthetic drug production.

2. Tracing Virtual-Asset Flows

The same integrated approach applies to the crypto dimension of fentanyl financing. By integrating blockchain analytics and transaction-monitoring feeds, DataWalk enables multi-hop tracing of virtual-asset flows. Pattern-detection tools highlight sudden spikes in cryptocurrency activity or clustered deposits into exchanges that correlate with known shipment dates. Where traditional systems see isolated transactions, DataWalk connects them into a single, dynamic financial network, revealing structure instead of chaos.

3. Spotting CMLO Typologies

Chinese Money Laundering Organizations (CMLOs) have become key facilitators for Mexican cartels and global financial crime networks. Their agility and speed make them particularly dangerous, as cash collected in North America is swapped for funds in China through mirror transfers and informal value systems, leaving little trace in standard reporting channels. DataWalk helps investigators recognize these typologies by correlating high-velocity cashier’s checks, suspicious account activity (e.g, indicating money muling), and currency conversions that lack a clear business rationale. Without coding, you can automatically detect clusters of newly opened accounts tied to counterfeit documents or thin-credit profiles, while link analysis exposes shared beneficiaries across accounts, a hallmark of a CMLO network.

4. Testing New Hypotheses – Fast

Fentanyl networks evolve weekly. When new typologies emerge, such as prepaid cards funding chemical purchases or fintech wallets used for layering, investigators need the ability to test and deploy new scenarios immediately. In DataWalk, analysts can drag and drop new data sources, build rules visually, and test them against the entire graph in minutes. There is no waiting for SQL development or data preparation, and every investigative step is tracked, reversible, and auditable. This means investigative hypotheses can evolve as fast as the threat itself, turning data agility into operational intelligence.