Artificial Intelligence is transforming every sector, and financial crime is no exception. Financial institutions are increasingly turning to AI to strengthen their ability to detect and prevent illicit activity, but the technology is also changing the nature of the threats they face.
The result is a paradox. The same technology that enables better detection, faster analysis and more sophisticated monitoring is also being adopted by criminals to carry out more complex and scalable attacks. For organisations responsible for protecting the financial system, the challenge is no longer simply about adopting new technology. It is about building the capability to stay ahead of how that technology is being used.
AI has become a powerful tool in the fight against financial crime, enabling institutions to analyse vast datasets, identify unusual patterns and detect suspicious activity far more quickly than traditional approaches. However, as financial crime becomes more sophisticated, organisations must ensure that the systems designed to protect them are supported by the right expertise, governance and operational frameworks.
The evolving threat landscape
One area where this shift is particularly visible is in the evolution of spear phishing. Unlike traditional phishing attacks, spear phishing is highly targeted, focusing on specific individuals or organisations. These attacks use detailed research and social engineering to craft convincing messages that encourage victims to disclose sensitive information, transfer funds or install malicious software.
Large language models and other AI tools are rapidly changing this landscape. They enable attackers to generate highly personalised messages at scale, making fraudulent communications more convincing and significantly harder to detect. What was once a relatively labour-intensive activity for criminals can now be automated and deployed across large target groups with far greater efficiency.
This creates a new level of complexity for financial institutions. The threat environment is evolving quickly, and the tools used to combat financial crime must evolve just as rapidly.
Technology alone is not the solution
While AI and advanced analytics are powerful tools, they are not a standalone solution. Financial crime prevention still relies heavily on human expertise to interpret patterns, understand context and identify emerging risks.
Industry bodies have emphasised this point. Research from organisations such as UK Finance highlights the role AI can play in strengthening detection capabilities, but also stresses the importance of human oversight to interpret results and respond to evolving threats. At the same time, major consulting firms have warned that AI may also increase the scale and sophistication of fraud and scams, reinforcing the need for skilled professionals who can manage these risks effectively.
Building the right capability
For financial institutions, this means the challenge is not simply technological. It is organisational.
The next generation of financial crime programmes requires professionals who understand traditional compliance and fraud detection, but who also have the skills to work with data analytics, machine learning and cybersecurity frameworks. These capabilities are increasingly essential in modern financial crime teams.
Just as importantly, organisations must ensure that the governance and delivery structures around these programmes are robust. AI tools must be implemented within well-designed control environments, supported by clear reporting structures and programme oversight.
A new phase for financial crime programmes
The role of AI in financial crime is only going to grow. Detection capabilities will become more sophisticated, but so too will the threats that financial institutions face.
For organisations navigating this environment, success will depend on a balanced approach. Technology must be paired with experienced programme leadership, strong governance, and specialist expertise to interpret signals, anticipate emerging risks, and adapt quickly as the threat landscape evolves.
AI may be changing the tools used in the fight against financial crime, but ultimately, it is still people, structure and expertise that determine how effective those tools will be.