Stuart Clarke, CEO, Blackdot Solutions
Economic crime in the UK has surged to record levels. At its core, most crime is economically motivated. Fraud and other financial crimes now underpin a significant proportion of organised criminal activity, from phishing scams and benefit fraud, to drug trafficking and illegal wildlife trade.
In fact, fraud now accounts for over 40% of all reported crimes – there were more than 3.3 million cases and £1.17 billion in confirmed losses in 2024 alone. From a £47 million phishing attack on 100,000 HMRC accounts to the £10 billion laundered annually through UK money mule networks, the volume and complexity of financial crime is outpacing investigative capacity.
Yet despite the scale of the threat, prosecution and conviction rates remain consistently low – most investigative systems are reactive and fragmented. Financial Intelligence Units (FIUs), law enforcement, and financial institutions are drowning in data and struggling to convert information into insight.
As criminals leverage new and evolving technologies like AI – for example, to increase the sophistication of fraud attacks – traditional investigation methods are no longer enough. What’s needed is a modern approach fit to counter the online criminal world.
OSINT: a key tool to closing the case
The structured analysis of publicly and commercially available data is essential to financial crime investigations. This data can be found in a whole range of locations such as news publications, public social media accounts, online forums, corporate registries like Companies House and even more inaccessible, but often useful, information sources like the dark web. The process of collecting this information and turning it into actionable insight is what’s known as open source intelligence (OSINT).
OSINT can provide insights of such value that sectors like law enforcement and journalism use it as a vital part of their work. For those working in financial crime, its use can provide investigators with vast access to digital intelligence and help them to draw the dots between people and companies. In turn, this can enable financial institutions to determine risk faster and improve compliance with anti-money laundering and sanctions regulations.
Yet, despite these benefits, the effective use of OSINT in financial services is mixed. In financial institutions like banks, OSINT is regularly underused – millions of pounds are dedicated to activities like transaction monitoring, but not to unmasking the identities behind financial crime. For FIUs, the issue is not so much in seeing a need for OSINT, but in how the practice is being carried out. Despite 97% of FIUs claiming to use OSINT, for example, only 31% employ dedicated platforms to do so. By implementing more effective OSINT strategies, FIUs, banks and law enforcement can transform their ability to fight financial crime.
The OSINT gap: patchy reports and manual processes
With criminals latching onto technology and innovating in how they conduct economic crime, whether by using deepfakes or creating more targeted phishing scams, those responsible for investigations must match this speed of innovation. But while banks invest heavily in understanding their own, internal data, they often neglect the external intelligence needed to gain a full picture of economic crime risk. OSINT is a means of acquiring this intelligence, but is currently neglected – in part due to lack of awareness of its value, in part due to lack of skills and resource.
Instead, many banks rely on internal data and the occasional Google search. This results in patchy suspicious activity reports (SARs), which FIUs must then try to interpret with incomplete information before passing intelligence to law enforcement. Combined with a segmented approach, where each organisation deals with different data, questions and challenges, this makes for a system that is reactive, fragmented and not fit to respond to today’s threat landscape.
Moreover, FIUs are hindered by a reliance on manual OSINT processes, limiting both the depth and speed of analysis. With endless information, both real and fake, online, being able to collate relevant data for a case and then turn it into actionable intelligence is increasingly challenging. To overcome this, FIUs need the right combination of technology, people and skills.
A modern, holistic response
By implementing OSINT platforms, FIUs, banks, and law enforcement can transform their ability to fight financial crime. These tools enable faster, deeper investigations by automatically gathering and contextualising data across the surface, deep and dark web and presenting it to investigators in a digestible format. The output could be anything from an overview of a subject’s business interests – including beneficial ownership hidden by shell companies – to a map of a person of interest’s connectivity to an organised crime gang, identified via publicly available social media.
Consequently, investigators can work with open source data far more efficiently and intuitively than manual methods permit them to, uncovering insights and connections between companies or people that otherwise might never have been made. But OSINT platforms are just one part of the OSINT puzzle – input from humans who understand the context behind the investigation is also key.
The answer to this need for both human insight and more efficient ways of working lies in better use of AI and automation. Tools that support human – machine collaboration can dramatically improve the outcomes of OSINT investigations by increasing accuracy and efficiency. Automation and AI can be combined to collect and analyse large quantities of data, removing the manual overheads that are barriers to effective OSINT implementation in many financial institutions. In turn, human investigators are then able to concentrate their time on areas where they add most value – such as contextual analysis that requires niche knowledge or human reasoning.
For example, agentic AI can automate traditionally manual tasks while also adapting to changes in data or situation. In the context of applying OSINT to economic crime, this could mean conducting ‘typical’ steps in a sanctions evasion or EDD check, including mapping corporate affiliations and conducting an adverse media check. These results could then be reviewed – and supplemented as needed – by the human investigator.
Similarly, Large Language Models (LLMs) can be used to analyse large volumes of search results and identify trends, categories or key terms. Human investigators can then spend more time interpreting this data without having to conduct time-intensive processing tasks.
Closing the case
The pace of technological innovation is allowing economic crime to prosper. Traditional investigation methods are lagging behind a world full of complex crime and information overload. In particular, there is a mismatch between how banks, FIUs and law enforcement conduct OSINT, if at all, and the tools they use to do so.
Criminals using technology must be fought by investigators using technology. If the various organisations working on financial crime can embed OSINT processes and technology into their way of working, then we can increase their ability to identify criminals, disrupt networks and truly fight economic crime. If banks use OSINT to include more useful detail in SARs, for instance, then FIUs can build on this base of information rather than attempting to fill in the gaps themselves. Using similar data sources and understanding the intelligence each other is using will increase efficiency further.
The success of this approach rests on organisations providing employees with the training, skillsets and technology to conduct effective OSINT, as well as the sector building a collaborative environment that facilitates the effective sharing of OSINT. Ultimately, the better we can combine multiple intelligence sources, the better we can get cases closed.
