Despite high expectations: AI is not being used in the fight against financial crime

Over the past year, I've asked two key questions of financial crime professionals across Nordic banks. The contrast in the answers has been striking. When I ask whether generative AI (Gen-AI) has the potential to revolutionise the fight against financial crime, about 95% of experts enthusiastically answer "yes." However, when I ask whether they've seen concrete examples of Gen-AI being implemented and used, only about 5% can confirm this.

So, is Gen-AI just hype, or is it the way forward? Gen-AI undoubtedly has the potential to change how we prevent and detect financial crime. But the adoption of the technology requires three key barriers to be overcome and they are currently curbing its potential.

Despite decades of investment, many financial institutions still struggle with poor data management and fragmented system architectures. Gen-AI is only as good as the data it is fed; without reliable and comprehensive data, its insights are useless. Unfortunately, many organisations suffer from inconsistent data collection and management practices, resulting in data breakdowns over time. Furthermore, risk controls are often spread across separate systems, making it nearly impossible to get a unified view of customers.

These challenges are not merely technical; they are fundamental barriers preventing companies from harnessing the full potential of AI. The solution? Financial institutions must prioritise improved data management and integrated system architectures.

The role of humans: The overlooked piece in AI adoption

Despite technological advances, humans remain the most important defence in the fight against financial crime. Ironically, this aspect receives the least attention and the lowest level of investment when it comes to AI adoption.

Successful implementation of Gen-AI requires trust and understanding among employees. Without this, resistance to the technology will be high. To bridge the gap between people and technology, companies should focus on:

• AI training: Integrate AI modules into existing financial crime training programmes with a focus on responsible use and practical applications.
• Shifting attitudes: Build trust and understanding of AI’s possibilities and limitations.
• Job security and collaboration: Reassure employees that AI is a help, not a threat – a technology that frees them from routine tasks and creates space for strategic, value-adding work.

Investing in employees is not optional – it is essential.

The way forward: Bold steps with caution

Although the potential of Gen-AI is enormous, many companies are hesitating about taking the leap due to uncertainty around regulation.

The global regulatory landscape is evolving rapidly. The EU’s AI law, which comes into effect in 2026, marks an important step, but differences in approaches between regions create uncertainty. In the US, changes in AI regulation have further complicated the picture.

Many leaders acknowledge that the risks of being the first movers in AI are not worth it without clearer guidance from authorities. At the same time, existing regulation prioritises compliance over innovation, which hinders progress.

To harness Gen-AI's full potential in the fight against financial crime, companies must balance caution with courage. This requires investing in strong data foundations, employee skills, and an agile approach to regulatory changes.

Gen-AI is not just hype – it is the way forward. But to unlock its transformative power, we must overcome the barriers holding us back.

Read the article in Danish here.