Compliance teams, regulators, and investigators rely on blockchain analytics to uncover illicit activity and support enforcement actions, but every outcome depends on the quality of the underlying data. A single incorrect attribution can discredit related insights, derail investigations, and trigger wrongful customer terminations. Evaluating a provider requires scrutiny of the methodology, evidence, and safeguards behind every conclusion.
- Providers should explain whether common ownership is established deterministically or inferred probabilistically, and demonstrate how techniques adapt to distinct blockchain architectures.
- A label backed by law enforcement-seized data is fundamentally different from one based on an anonymous tip, and grouping logic should hold up even if a label is removed.
- Robust attribution requires differentiating between who interacts with an address and who ultimately controls it, particularly for exchange deposit addresses and nested custodial entities.
- Providers should be transparent about whether their methods have satisfied legal standards like Daubert and how they distinguish machine learning outputs from evidence-based conclusions.
- A reliable provider can walk you through exactly how any specific cluster was constructed and what evidence supports it.
Read our full analysis here.
