Harness the power of artificial intelligence to fight financial crime

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The writer is chairman and chief executive officer of the Nasdaq

Recent breakthroughs in artificial intelligence are rightly seen as a radical shift in our technological economy. For the world of finance, much of the reaction has focused on the risks posed by this rapid change.

The concerns were rightly so lifted up on the ability of regulators to oversee AI operations, market concentration risks arising from the limited number of service providers, and digital breeding where all computers act alike, reinforcing market swings.

While calls for caution and proactive regulation are appropriate, so are calls for urgency and optimism as we give industries a chance to start tapping into the potential of TO THE advance.

This starts with recognizing that not all AI is created equal. Yes, the power of generative AI, which allows you to create images and text from prompts, has captured the world’s imagination. But AI has been implemented in our markets for many years.

Nasdaq uses AI for market predictive maintenance, preventing outages before they happen, and we’re incorporating AI into several stages of our operations. It is especially important for our financial crime software division. In the world of finance, AI’s ability to help detect, deter and stop financial crime is perhaps the technology’s most compelling use case.

Financial crime is an important and thriving global industry. LexisNexis estimates show that banks spend nearly $275 billion each year fighting financial crime. Yet United Nations studies suggest that less than 1 percent of the roughly $4 trillion in illicit funds circulating in the financial system is currently intercepted by law enforcement.

Contributing to this disconnect is the restrictive impact of regulations that limit banks’ use of data and advanced technology.

Simply put, financial crime is a data problem. Criminals don’t bank with just one bank. They leverage the entire financial ecosystem to avoid detection. The growing interconnectivity of the financial system and the emergence of new payment systems are all helping criminals become more effective.

Therefore, from a crime-fighting perspective, the quality and depth of our datasets, combined with the use of the latest analytics technologies, are the most critical determinants of success in stopping crime.

In Nasdaq’s Financial Crime Division, we built data lakes that collect normalized and anonymised transaction data from more than 2,400 banks. This consortium data approach, combined with advanced AI algorithms, has enhanced our ability to detect suspicious transaction patterns.

However, banks are expected to provide end-to-end explanations for any model they use, even for crime-fighting, which greatly inhibits their impact.

After years of fighting market manipulation and financial crime, two truths emerge: Criminals do not follow laws or regulations and exploit technological innovation at scale and speed to stay ahead of detection. It is therefore crucial to find common ground with regulators on solutions to address this insidious problem.

It all starts with responsible data sharing. In the US, banks can share information for the purpose of fighting crime. Enabling financial institutions in Europe, Canada and other regions to share data both inside and outside their networks would greatly improve our ability to identify criminal activity. There are proven models that allow for data sharing while protecting the privacy rights of individuals. These can – and should – be replicated on a large scale.

The second imperative is that regulators enable the industry to leverage the latest capabilities in the cloud, artificial intelligence, and machine learning so they can better respond to new threats, increase effectiveness, and improve efficiency.

And finally, there’s an opportunity to increase collaboration. Criminal enterprises are deeply connected, and the financial system needs to reflect this by strengthening collaboration between the private sector, government and law enforcement agencies. A key change would be the implementation of “feedback loops”: communication from law enforcement agencies to banks to confirm whether or not the reported activity was deemed criminal. This requires little investment but allows banks to refine their algorithms based on real results.

The fight against financial crime is already complex enough. I strongly urge regulators to reduce, not increase, complexity. Let’s harness the next wave of innovation to strengthen the integrity of the financial system, with technology on our side.