Crypto crime, caveats & clarity: How crypto forensics has evolved in 5 years

2026-03-02 · Source: Thomson Reuters Institute · Field: Technology & Digital — Blockchain & Distributed Ledger Technology, Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy · Depth: Intermediate, medium

Summary

An analysis of crypto crime statistics reveals that official figures, which indicate illicit activity represents a negligible portion of all cryptocurrency transactions, significantly underestimate the true scale of the problem. Blockchain forensics firms, such as Chainalysis and TRM Labs, adhere to a stringent 99%-plus accuracy standard for law enforcement, leading to very low false positive rates but substantial false negatives, missing up to 75% of known criminal addresses in some datasets. This reporting gap means that while identified illicit crypto flows reached $158 billion in 2025, actual losses could exceed $110 billion annually when accounting for the 85% of fraud victims who do not report crimes, as suggested by FBI data and academic research. The industry is improving at identifying criminal activity, with reported illicit activity increasing to over 1% of all crypto activity for the first time since 2019.

Key takeaway

For law enforcement agencies and financial institutions assessing crypto-related risks, you should recognize that official blockchain forensics reports represent a floor, not a ceiling, for illicit activity. Integrate FBI IC3 reports and academic research on unreported fraud to form a more comprehensive estimate of actual financial losses, which could be substantially higher than on-chain figures suggest. This holistic view will better inform your risk models and investigative priorities.

Key insights

Official crypto crime statistics significantly underreport the true scale of illicit activity due to strict reporting standards and unreported crimes.

Principles

• High accuracy standards increase false negatives.
• Unreported crimes skew financial loss estimates.

Method

Blockchain forensics firms use data models with >99% accuracy to identify illicit on-chain activity, primarily for law enforcement, which prioritizes verifiable evidence over broad estimates.

In practice

• Cross-reference forensic reports with FBI data.
• Consider unreported victim data for true loss estimates.

Topics

• Crypto Crime
• Blockchain Forensics
• Financial Crime
• Law Enforcement
• Data Accuracy

Best for: CTO, VP of Engineering/Data, Executive, Legal Professional, Policy Maker, Data Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Thomson Reuters Institute.