BIPA Chairman calls for professionalising blockchain intelligence at INTERPOL Virtual Asset Summit in Lyon
Lyon, France — March 2025. Bogdan Vacusta, Chairman of the Blockchain Intelligence Professionals Association (BIPA) and strategy consultant on crypto-assets and digital currencies with the National Bank of Romania, took part in the Virtual Asset Summit 2025, held on 27 March 2025 at INTERPOL Headquarters in Lyon and convened by the Digital Asset Task Force (DATF) of the Global Coalition to Fight Financial Crime.
The invite-only, full-day session brought together members and external experts from across the public sector and the digital asset industry for an intensive exchange on the most pressing challenges in financial crime involving virtual assets — from privacy-coin investigations and the misuse of virtual assets by illicit actors, to the interoperability of blockchain analytics providers and the question of what regulatory standards such providers should meet.
Vacusta joined the panel “The Future of Intelligence Sharing — Blockchain Analytics and Attribution Techniques,” which assembled practitioners and policy voices from both the public and private sectors to debate how investigators, supervisors and the industry can work together more effectively as the on-chain economy grows.
Professionalising a domain that is still taking shape
Throughout his intervention, Vacusta made the case that blockchain intelligence has matured into a discipline in its own right — and now needs to be treated as one. Today, he argued, the work of tracing, analysing and attributing on-chain activity is performed by professionals drawn from very different backgrounds, working to inconsistent expectations and without a shared professional reference point. That fragmentation, he warned, is a risk in itself.
His central message was that the field should be professionalised through the development of a dedicated profession, underpinned by:
- Clear ethical and governance standards, so that analysts operate to a recognised code of conduct and their findings can withstand scrutiny;
- Common training standards, so that competence is defined, demonstrable and comparable across organisations and borders; and
- Prioritised data-exchange standards, so that intelligence can move reliably between the institutions that need it.
Data-exchange standards as the foundation for cooperation
Vacusta placed particular emphasis on the importance of standardising how blockchain intelligence is captured and shared. Without agreed formats and protocols, he noted, valuable analysis remains locked inside individual tools, teams and jurisdictions.
Robust data-exchange standards, by contrast, would allow regulators, supervisors, financial intelligence units (FIUs) and law enforcement agencies to cooperate far more effectively — both nationally and across jurisdictions internationally. This, he stressed, is precisely where cross-border financial crime investigations most often stall today.
The point resonated directly with the summit’s own agenda, which addressed interoperability among blockchain analytics providers and the features that blockchain analytics software should be expected to deliver.
Avoiding the fragmentation of blockchain data analysis
For Vacusta, professional standards, training and interoperable data exchange are not three separate ambitions but a single coherent way forward. Building a recognised profession with shared ethical, governance and training foundations — and connecting practitioners through common data-exchange standards — is, in his view, the most effective way to avoid the fragmentation of blockchain data analysis.
A fragmented landscape, where each institution analyses on-chain activity in isolation and to its own standard, ultimately weakens everyone’s ability to follow illicit flows. A professionalised, standardised and interoperable one strengthens collective capacity against financial crime.
Such standards are especially important for central banks and financial supervisory authorities, enabling them to develop independent, in-house data analysis capabilities rather than relying solely on external providers.