Vincent Danjean, Head of INTERPOL’s Cyberspace and New Technologies Laboratory, spends much of his time working on ways to help law enforcement keep up with evolving cyber threats. Among these: the use of crypto for organised crime and money laundering.

This Q&A gives an insight into the challenges and solutions from a law enforcement perspective. Vincent is a driving force behind efforts to enhance the quality of blockchain intelligence, an issue that is the focus of the upcoming Blockchain Intelligence Forum in Bucharest, Romania.

1. What are the biggest challenges law enforcement faces when investigating crimes involving crypto?

One of the biggest challenges in investigating crypto-related crimes is the pseudonymous nature of blockchain transactions. This makes it difficult to link wallet addresses to real-world identities. Criminals exploit mixers, privacy coins and decentralised finance (DeFi) tools to obscure illicit funds.

Additionally, cross-border issues slow down investigations, as different countries have varying regulations and cooperation mechanisms. The rapid evolution of criminal tactics, including the use of AI-driven fraud, smart contract exploits and cross-chain laundering, further complicates enforcement efforts.

Law enforcement is addressing these challenges by enhancing blockchain intelligence capabilities and strengthening international collaboration to harmonise both forensic methods and procedures, as well as wallet address attribution techniques.

2. How does law enforcement collaborate with blockchain analytics firms and cryptoasset service providers to track illicit activities?

Law enforcement agencies work closely with blockchain intelligence firms and cryptoasset service providers to trace illicit transactions and identify perpetrators. Investigators leverage advanced tools to analyse blockchain transactions. This typically involves following the money from a suspect wallet to a known cryptoasset service provider (such as an exchange), which may hold identifying information.

Traditionally, this has been a manual and time-consuming process, relying on public blockchain data and cooperation from compliant exchanges. While this method has yielded positive results, it does not scale with the rapidly growing volume and complexity of crypto-asset-related crimes.

To stay ahead, law enforcement must continue to work closely with the private sector. Through public-private partnerships, they can jointly develop methods for analysing, evaluating and attributing crypto-asset transaction activity that are based on scientific principles and are empirically tested.

3. What methods could make law enforcement more effective in combating crypto-related crimes?

One major inefficiency in investigations today is the duplication of efforts – multiple law enforcement agencies unknowingly working on the same cases. This happens because cybercriminals operate globally while victims report felonies locally. It leads to fragmented investigations into what is often a single, large-scale crime.

A key strategy to improve effectiveness is proactively identifying connections between related cases before launching separate investigations. This can be achieved by creating better procedures for information-sharing and by enabling blockchain data interoperability. There is also a need to jointly analyse common cryptoasset addresses, overlapping transaction patterns and shared cybercriminal tactics.

Rather than working in isolation, international collaboration and real-time intelligence sharing must be promoted by providing secure platforms built on common standards that facilitate blockchain data interoperability.

By pooling resources, leveraging automated data-matching tools and integrating blockchain intelligence across jurisdictions, law enforcement can significantly enhance efficiency and improve the success rate of cryptoasset criminal investigations.

4. What role does AI and automation play in modern blockchain investigations?

With crypto-related crimes increasing exponentially, it is evident that manual tracing methods alone will not scale. Cybercriminals already leverage automated techniques to launder illicit funds and increase transaction complexity, making traditional “follow-the-money” approaches ineffective. To keep pace, law enforcement must integrate automation into blockchain investigations.

Automation can accelerate transaction tracing, detect suspicious patterns in real time and streamline large-scale investigations. However, it is crucial that investigators retain the ability to manually verify and validate results to preserve the evidential integrity of blockchain investigations.

AI offers promising opportunities, but law enforcement must apply it cautiously as it is a high-risk domain. One of the biggest challenges is the relatively limited volume of blockchain transaction data. Also, the low signal-to-noise ratio due to wash trading and other manipulation obfuscates the economic intent of transactions.

Law enforcement needs to ensure that technology is judiciously applied to cryptoasset tracing. Methodologies and technologies must stand up to independent validation, verification and reproduction.

In addition, ensuring reproducibility, explainability and maintenance of the chain of custody is essential for court-admissible evidence. While AI can enhance efficiency, it must be transparently designed and rigorously tested using established standards for forensic science. This is necessary to uphold legal and ethical standards and ensure admissibility.

5. What are some key strategic takeaways?

To summarise:

First, a networked approach to investigations is essential. Cybercriminals operate globally, yet investigations often remain local. By connecting related cases across jurisdictions, law enforcement can improve efficiency and uncover larger criminal networks. Strengthening cross-border collaboration and intelligence sharing while ensuring blockchain data exchange and interoperability will be key to combating crypto-related crimes effectively.

Second, law enforcement needs to embrace automation to keep pace with criminals using automated laundering techniques and DeFi exploits. Manual tracing alone is no longer scalable. Law enforcement must integrate automation into blockchain intelligence while ensuring human oversight to validate evidence for court proceedings.

Third, a data-centric approach is crucial. Instead of relying solely on intelligence tools, law enforcement should focus on structured, shareable and interoperable blockchain data to enhance investigations. Shifting from “thinking in tools” to “thinking in data” will enable better case-linking, pattern detection and real-time monitoring. This will also support automation.

Last, establishing empirically tested standards of analysing and interpreting blockchain data, while ensuring interoperability, will be key to extracting value from blockchain intelligence.

Learn more

• Read a related Q&A: Unlocking blockchain intelligence to tackle illicit crypto use.
• Learn more about the Blockchain Intelligence Forum on 10 April 2025 in Bucharest, Romania.