The game of cat-and-mouse is now akin to a chess match played in the dark, with both sides needing to re-write the rules and anticipate the next move against a backdrop of hidden tactics. It’s coming at a great cost too as the growth of global criminal networks, powered by cyber-fraud, money laundering and human trafficking, has been found to drain between 10-15% of global GDP.
This rapid escalation carries very real human impact. Bad actors now deploy digital tools at scale, whether that’s social media, instant messaging, fake eCommerce platforms or AI and automation to attract money mules, move money without detection, and exploit unwitting account holders. Victims are reachable around the clock and from all corners of the world, and that drives the moral imperative for why banks and financial institutions must do more.
This is an issue that lives in security and compliance, yet has much wider ramifications that traverse revenues, reputation, regulatory penalties and confidence in the financial system. Criminal networks cannot be allowed to operate unimpeded, and this means staying two steps ahead with the right digital infrastructure.
Cybercrime as the engine of modern illicit economies
Many will be familiar with the template financial scam; the unsolicited email or text message, bogus attachments or the random enticement on social media. In the past, these were manageable and often small-scale threats, but the move to industrialised criminal operations poses a real issue for all of us.
Not only do financial institutions need to contend with greater numbers of customers falling victim to these tactics, and demanding support, but the rise of real-time payments and digital financial services means that transactions are now instantaneous. Intervention has become much harder, while the growing use of crypto and alternative assets adds further complexity to the situation. Funds are quickly moved through complex networks, become difficult to trace, especially when filtered across borders, and are then laundered and reused.
In the UK, up to 80% of fraud cases now involve a cyber element. But cybercrime is no longer just an entry point, it’s driving modern global money laundering. Financial institutions must understand how to detect and stop suspicious activity in real time, before harm can escalate.
Human trafficking as a financial system
Like cybercrime, the threat of human trafficking is a growing consequence of the borderless criminal economy. It is already widely recognised as a humanitarian crisis, but bad actors see it as a mere tool of income generation. It relies on financial systems to move and legitimise its profits, often using the same techniques seen in other forms of crime.
Crypto-assets, for example, are now being used across illicit networks, including those linked to human trafficking. Their speed, transferability, and in some cases, limited transparency means they are an ideal tool to move and obscure funds tied to exploitation.
But the risk doesn’t sit with crypto alone. Trafficking often flows through a mix of traditional and digital financial channels – payments that, in isolation, can appear routine but together signal something far more serious. This is where many institutions are falling short by failing to connect fragmented signals across accounts, financial channels and regions, missing the broader patterns of activity.
This is where the challenge, and in turn, the responsibility, for banks becomes clear. Identifying and preventing human trafficking is not just about flagging individual suspicious transactions, but recognising the behaviours and networks behind them. That means moving beyond siloed monitoring and static rules, towards a more holistic, intelligence-led approach that can surface those hidden connections and risks in real time.
The AI arms race
Artificial intelligence is undoubtedly reshaping both sides of financial crime – accelerating the threat from criminals but also offering a way to fight back.
Across cyber-enabled fraud and crime, AI is lowering the barriers to entry while increasing both speed and precision. Scams can now be deployed at scale, while AI means that tactics never stand still – always evolving to blur the lines between what could be legitimate and what isn’t. In one widely reported case, an employee was tricked into transferring approximately $20 million after interacting with what she believed was a trusted colleague but was in fact an AI-generated deepfake. That level of sophistication is no longer the exception but the standard.
What is most striking is that while financial institutions recognise that this is a fast-evolving issue, many are not ready to respond effectively. There is no shortage of investment or intent, but there is a clear gap between ambition and execution. Our recent report found that just 59% believe they have ‘mature’ AI programmes, with many struggling as a result of the technology being layered onto fragmented and legacy systems that are not fit for purpose.
To keep up, AI needs to be ‘by-design’, built into the very core of risk detection and management. We found that almost all firms (99%) know that they have issues detecting financial crime, with siloed data (22%) and a lack of real-time visibility (21%) as key problem areas. While many are still taking minutes, not seconds, to clear low-risk AML or sanctions alerts. In that time, illicit funds can already be on the move.
This state of affairs needs to change, and the issue is not simply more technology adoption, but a reimagination of how it can be deployed – connecting data across customers, transactions and networks to build a clearer, more complete picture of risk as it unfolds. AI cannot be bolted on, it must be the foundation of all future financial crime prevention.
The role banks must now play
Financial crime is undoubtedly evolving with digital tools making it easier for criminal networks to grow and operate across borders – compounding global issues like cybercrime and human trafficking. What we are seeing though is not just growth, but a fundamental shift.
For banks and financial institutions, the responsibility is clear. With visibility into the movement of money and the tools to detect risk, they are well positioned to disrupt criminal networks and protect vulnerable individuals.
But they need to act with urgency, adopt an AI-by design mindset and take a more proactive, forensic approach to stopping bad actors from using their networks. In doing so, they will not only keep pace with an increasingly complex and digital threat landscape, but make the financial system safer for everyone.
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