AI could stop $113bn of dirty money passing through the UK | Napier AI

Finding the balance between meeting evolving needs of the regulator, while balancing the adoption of innovative technologies to bring down financial crime, such as AI is not an easy feat. Some markets have clearer guidance than others on the best way of implementing AI, and many lack specific guidance for the use case of financial crime compliance. Implementing AI controls for the sake of it will lead to ineffective solutions, end up costing billions of pounds in fines, but also impact the institution’s reputation and the economy it operates in.  

It is important to understand what, if any, guidance there is from an AI point of view in the market that you operate in. Assessing the goals of any AI implementation and the readiness of your business is also important, as well as the scale of financial crime to best inform a risk-based approach. The Napier AI / AML Index 2024-2025 found that global economies could save $3.13 trillion annually using AI to detect and prevent money laundering and terrorist financing. 

In this article, we will examine the impact of AI on anti-money laundering strategies, estimating how much could be prevented from passing through the UK illegally, with data from the Napier AI / AML Index. 

As a large financial hub, the UK has a higher risk exposure to financial crime, nevertheless it successfully protects a large amount of GDP from flowing into the black market. The low cost of financial crime compliance coupled with its high compliance scores illustrate the benefits of a regulatory environment that balances risk with innovation. The UK should focus next on AI implementations across the industry, beyond just traditional banks.

The UK generally takes a pro-innovation stance to AI in contrast to its EU and US counterparts who adopt more prescriptive legislative measures. Having hosted the world’s first AI Safety Summit in Bletchley Park in 2023, the UK government followed up with a consultation response on regulating AI in February 2024. The response aims to balance innovation and safety but delays legislative action in favour of better understanding risks and challenges, with no tangible requirements yet.

Despite the pro-innovation approach from the UK government, regulator and enforcement bodies, financial institutions are only just starting to use AI and there is some hesitancy around implementation and best practices. Additionally, there has been a bigger focus in recent years on banks over other financial firms and fintechs. In the next 12 months, we may see a more legislative approach towards AI from the UK, following in the footsteps of the EU’s AI Act. More explicit guidance on AI’s usage could encourage more adoption in the financial services sector. The new government has shown a greater willingness to intervene to facilitate the technology’s development.  

The market’s financial services regulator, the Financial Conduct Authority (FCA) takes a similar stance to AI. In its AI Update published in April 202414, the FCA emphasised the importance of transparency and explainability. It also sees potential in synthetic data’s possibilities to benefit innovation in fighting financial crime, and so has set up the Synthetic Data Expert Group to explore its opportunities and challenges.

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