Stuart Clarke, CEO, Blackdot Solutions
Financial crime rarely happens in isolation. In 2023, transnational financial crime generated over $3.1 trillion globally, with criminals operating through layered networks spanning multiple jurisdictions.
Fraudsters and money launderers work in overlapping webs that move seamlessly between industries and digital platforms. The challenge is not just spotting individual incidents, but connecting the dots across these complex networks to uncover larger organised crime efforts and emerging threats before they mature.
Open Source Intelligence (OSINT) offers a way to strengthen defences in the face of complexity. In short, it is the targeted collection and analysis of publicly available or licensable data to produce actionable insights, surfacing connections that would otherwise remain hidden. And this enables investigators to shift from reactive to proactive financial crime investigation – turning intelligence into foresight, so they can disrupt criminal activity before it impacts their business or customers.
Shining a light on hidden relationships
Processes like AML, KYC and EDD are crucial in regulated sectors like finance, law and real estate – compliance teams need to collect and verify information such as the ultimate beneficial owner (UBO) of a company and proof of source of funds. Simultaneously, teams are also under pressure to deliver smooth onboarding so their company can secure new business opportunities.
The issue is that money launderers will often mask themselves in layers of shell companies and offshore entities to hide the real UBO of a company. So, OSINT provides a way for investigators to effectively screen higher-risk or suspicious customers by using public information to map out their corporate footprint and understand any alleged risk in media reporting. Yet manually poring over corporate, property and media records can be incredibly time consuming and inefficient, with vast amounts of data spread over various sources – investigators can even miss insights altogether.
That’s why the use of OSINT technology is becoming increasingly necessary. An OSINT platform can automatically collect and analyse information from across public data sources, whether that’s corporate registries like Companies House, adverse media or web forums, and present it clearly to investigators in one platform.
Ultimately, this means investigators can work far more efficiently. And by mapping complex networks faster and more accurately, they can build a better understanding of risk, enhance their compliance efforts to meet regulations, and onboard more customers.
Spotting new crime typologies
The arrival of new technology is not only helpful for investigators. Criminals are often at the forefront of using new tools to devise innovative methods for financial crime. Money muling, for example, has expanded through a combination of social media and cryptocurrency. Here, criminals recruit individuals, often students, through public platforms such as TikTok posts, to launder money through their bank accounts or to buy or sell crypto on their behalf. The criminals can then use these money mule networks – comprising groups of recruited individuals – to hide where their money actually comes from.
The use of AI is also making crimes like fraud harder to detect. Criminals are utilising the technology to generate increasingly realistic scam messages on a huge scale. AI-generated phishing involves bad actors using large language models to write highly personalised scam emails and SMS messages that mirror a target’s tone or corporate language – these can be scraped from LinkedIn, company press releases or social media. While the tactics remain similar to traditional fraud, AI is giving criminals more skill and variety in how they can carry out these tasks, and enables them to do this far more proficiently and at scale. Similarly, AI-generated images and video could be used by criminals to impersonate innocent individuals during KYC and customer onboarding checks
So, investigators need to work faster and more effectively themselves. OSINT can help them identify these emerging crime typologies and patterns early by monitoring trends via publicly available sources and harder-to-reach locations like the dark web. This gives them the intel to intervene earlier and act before any issues escalate into regulatory breaches or enforcement cases.
Why does this matter? By unknowingly facilitating money laundering or fraud, a firm could risk hefty fines, reputational damage and even the loss of banking relationships if misconduct surfaces publicly.
Blending tech with human skill
There is simply too much data available in public, commercial and internal sources for investigators to review and understand manually. As such, combining automation and advanced analytics with investigative experience is essential for converting data abundance into precise, actionable intelligence that drives successful disruption of crime. But it’s vital that tech acts as part of a combination and doesn’t become a replacement.
If we look at money laundering and fraud cases, the data needing to be gathered and analysed generally focuses on the same sources: corporate and ownership databases, legal records, adverse news, and sometimes publicly available social media/web forum footprints. The initial collection, filtering and refinement of this data can all be automated to quickly create a report of risk related to the entity or person in question. Human investigators can then apply their judgement to assess whether further investigation is needed.
Emerging AI advancements are accelerating this process, further enhancing the speed, scale, and quality of investigative insights. Agentic AI, for example, could intelligently automate routine KYC and EDD tasks – such as identifying company affiliations, screening against PEPs and sanctions lists, or summarising adverse media – empowering investigators to focus on higher-value analysis and uncovering emerging risks more efficiently
It remains crucial, however, that AI does not replace human decision-making. While it can carry out repetitive or time-consuming steps, investigators must retain responsibility for validating the results, making strategic judgements, and ensuring compliance with regulatory and ethical standards. Autonomous AI agents should function as assistants that enhance efficiency and insights, rather than making final decisions.
Therefore, the best investigation outcomes will emerge from a blend of technology and human judgement. If investigators have more time to assess data, they can build better actionable insights and make more informed decisions.
Keeping on the front foot
Financial crime is complex by nature; it often evolves faster than the frameworks designed to stop it.
Criminals hide themselves in intricate networks of shell companies and corporate agents and are using technology like AI to become far more sophisticated in how they launder money and commit fraud.
So, under pressure to meet regulations while also hitting onboarding and customer retention targets, investigators need the tools and strategies to perform compliance tasks efficiently and proactively manage risk. OSINT provides the means for investigators to connect the dots and uncover hidden connections before they develop into severe compliance risks, such as onboarding clients with undisclosed links to money laundering.
But with data available in abundance, the use of AI, automation and OSINT technology is necessary to effectively gather public data and turn it into actionable insights. If firms can nail the combination of OSINT, the latest technologies and human judgement, then they can get on the front foot in battling financial crime.