For years, I have worked at the intersection of crime, technology and financial investigation. My background did not start with blockchain. It started with people. Early in my career, I worked with young people involved in criminal behaviour. Later, my work shifted towards organised crime, online crime and financial crime, working alongside professionals from law enforcement, government and other organisations involved in preventing and investigating criminal activity. One lesson has remained remarkably consistent throughout that journey: crime starts with human behaviour. People make decisions. They interact with other people. They move through social and financial networks. And those decisions create patterns.
The technology changes. The behaviour often does not. That became particularly interesting when cryptocurrencies and other digital assets entered the financial system. Blockchain created new opportunities for consumers, investors and businesses. But it also created a challenge for the traditional financial and compliance world: How do you establish where digital wealth actually came from?
The source of wealth problem
Financial institutions and other regulated professionals have long been required to understand their clients. Know your customer, customer due diligence and anti-money laundering processes are designed to answer fundamental questions: Who is this person? What is the purpose of the relationship? Where does the money come from? And does the financial behaviour make sense? In traditional finance, answering these questions usually involves documentation. Payslips. Bank statements. Company accounts. Tax returns. Contracts.
Transaction records: crypto complicates that process
Imagine a client tells an accountant, lawyer, notary or financial institution that €500,000 of their wealth originated from cryptocurrency investments. Knowing the current value of a wallet is not enough. The real questions are much more difficult: When were the assets acquired? How were they acquired? Which exchanges or wallets were involved? What happened between the original purchase and the current balance? Were assets transferred between wallets? Were they swapped into other tokens? Did funds interact with services or addresses presenting elevated risk? And, ultimately, does the blockchain activity support the story the client is telling? Suddenly, a ‘source of wealth’ investigation becomes partly a blockchain investigation. And that presents a problem. Most compliance professionals are not blockchain investigators - nor should we expect them to be.
Blockchain as an evidence layer
This is where blockchain technology offers something unusual. Traditional financial investigations often depend heavily on information supplied by institutions or clients. Public blockchains introduce an additional source of information: a transaction history that can, in many cases, be independently examined. Transactions can contain timestamps, wallet addresses, transaction hashes, amounts and movements between addresses. That does not automatically tell us who owns a wallet or why a transaction took place. But it does provide something extremely valuable: an independently observable trail of activity. This changes the nature of source of wealth and source of funds investigations. Instead of asking only: “What documents has the client provided?” We can also ask: “Does the activity visible on chain support the explanation being provided?” That distinction is important. A blockchain should not be treated as a magical source of truth. But it can function as an additional evidence layer.
The advantages - and the limitations
There are several important advantages to using blockchain technology in financial investigations. The first is transparency. On public blockchains, transaction activity can often be independently examined without relying entirely on a client’s own records. The second is traceability. Digital assets can sometimes be followed across multiple transactions, creating a timeline that helps investigators understand how assets moved. The third is verifiability. Transaction hashes and blockchain records provide evidence that can be independently checked. And the fourth is automation. Machines are much better than humans at processing thousands of transactions, calculating balances, identifying timestamps and detecting recurring patterns. That means technology can significantly reduce the amount of manual investigative work required.
But blockchain technology also has serious limitations
A wallet address is not an identity. Seeing that funds moved from wallet A to wallet B does not automatically tell us who controlled either wallet. Blockchain data can show what happened, but not necessarily why it happened. Off-chain activity creates another challenge. Funds may move through centralised exchanges, banks or other services where important information exists outside the blockchain. There are also privacy-enhancing technologies, cross-chain activity, bridges and increasingly complex decentralised financial structures. And perhaps most importantly, data without context can create false confidence. A transaction may be technically visible while its economic meaning remains unclear. That is why I believe the future of financial investigation is not just using blockchain technology instead of traditional compliance. It is the deployment of blockchain-powered solutions combined with traditional evidence, professional judgement and contextual information.
Where AI changes the equation
This is where artificial intelligence becomes particularly interesting. Blockchain provides enormous quantities of structured data. Compliance investigations generate enormous quantities of unstructured information. Documents, transaction histories, policies, client explanations, risk indicators and regulatory requirements all need to be interpreted together. AI can potentially become the bridge between those worlds. Instead of asking an analyst to manually review hundreds or thousands of transactions, AI-assisted systems could help identify unusual patterns, reconstruct timelines and highlight transactions that deserve human attention. It could also help translate highly technical blockchain information into language that a compliance professional can actually use. For example, an AI-supported system might identify that assets were accumulated over several years, moved through multiple self-controlled wallets and eventually transferred to an exchange before being converted into fiat currency. Rather than presenting an investigator with hundreds of blockchain transactions, the technology could structure that activity into an understandable narrative, whilst retaining the underlying evidence so that the conclusions remain auditable. This distinction is crucial. AI should not replace the investigator. It should reduce the investigative burden.
The danger of automating judgement
There is an important warning here. AI introduces the same problem that blockchain analytics can introduce false certainty. A sophisticated model can produce an extremely convincing explanation that is still wrong. In financial crime investigations, that matters. A compliance decision may affect whether a client is accepted, whether a transaction is escalated or whether suspicious activity is reported. Therefore, explainability, auditability and human oversight are essential. The question should never simply be: “What did the AI conclude?” The better questions are: “Which evidence produced that conclusion? Can we verify it? And does a qualified human agree with the interpretation?” For that reason, I see AI as an investigative assistant rather than an autonomous decision-maker. It can collect, structure, compare and prioritise information at a scale humans cannot. Humans still need to understand context, challenge assumptions and make decisions. From a compliance problem to a technology solution These challenges eventually influenced the development of BARP, the Blockchain Analysis & Reporting Platform. The idea was not to build another tool that simply visualises blockchain transactions.
The problem we wanted to solve was more practical: How can professionals who are not blockchain specialists conduct defensible source of wealth and source of funds investigations when crypto is involved? That requires bringing several components together. Blockchain activity needs to be reconstructed. Wallet ownership needs to be substantiated. Assets and balances need to be understood over time. Risk indicators need to be considered. Client explanations and supporting evidence need to be incorporated. And ultimately, the findings need to become a report that another professional, or potentially a regulator, can understand and review. In other words, the objective is not simply blockchain analytics. It is translating blockchain data into compliance evidence.
Technology does not remove the human. There is sometimes an assumption that more automation will eventually remove humans from compliance. I think the opposite may happen. Technology will remove more of the repetitive work so that humans can focus on the part machines struggle with most: judgement. The strongest future model may therefore combine three layers. Blockchain provides a verifiable record of digital activity. AI helps process, interpret and structure enormous quantities of information. Humans provide context, professional scepticism and accountability. Each layer compensates for weaknesses in the others. Blockchain without context is just data. Human investigation without technology increasingly struggles with the scale and complexity of digital finance. Together, however, they create something much more powerful.
The bigger opportunity
Crypto may be forcing us to rethink source of wealth investigations today, but the underlying question is much broader. As financial activity becomes increasingly digital, how do we create evidence that can be independently verified, efficiently analysed and clearly explained? That question applies far beyond cryptocurrency. We are moving towards a world where financial crime prevention will increasingly depend on our ability to connect data across systems whilst maintaining privacy, accountability and human oversight. The organisations that succeed will not necessarily be those that collect the most data. They will be the organisations that can turn data into understandable, verifiable and actionable evidence. And perhaps that is the most important lesson from combining traditional financial investigation with blockchain technology.
Technology does not eliminate the need to understand human behaviour. It gives us new ways to see it.
This article first appeared in Digital Bytes (22nd of September, 2026), a weekly newsletter by Jonny Fry of Team Blockchain.
How can AI turn digital-asset data into practical compliance intelligence?