Harness the power of AI to tackle financial crime

The writer is the Chairman and Chief Executive Officer of Nasdaq

Recent breakthroughs in artificial intelligence are being seen as a step-change in our technology economy. For the world of finance, much of the reaction to this rapid change has focused on the risks.

Concerns have been raised about the ability of regulators to oversee AI operations, market concentration risks from a small number of service providers, and digital herding where computers all perform the same functions, reinforcing market swings.

While calls for caution and proactive regulation are appropriate, so are calls for urgency and optimism as we empower industries to begin harnessing the potential of AI advances.

It starts with recognizing that not all AI is created equal. Yes, the power of Generative AI, which allows images and text to be created from prompts, has captured the imagination of the world. But AI has been deployed in our markets for many years.

Nasdaq uses AI for predictive market maintenance – preventing disruptions before they happen – and we are embedding AI at various stages in our operations. This is especially important for our Anti-Financial Crime Software Division. Within the world of finance, AI’s ability to help detect, deter, and prevent financial crime is perhaps the technology’s most compelling use case.

Financial crime is a major — and thriving — global industry. LexisNexis estimates that banks spend about $275 billion annually dealing with financial crime. Yet UN studies show that less than 1 percent of the approximately $4 trillion in illicit money circulating in the financial system is currently being intercepted by law enforcement.

One contributor to this disconnect is the restrictive effect of regulations that limit banks’ access to data and advanced technology.

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

Therefore, on the crime-fighting side, the quality and depth of our data sets, coupled with the use of the latest analytics technologies, are the most important determinants of success in preventing crime.

At Nasdaq’s Anti-Financial Crimes Division, we have built data lakes that bring together denormalized and anonymized transaction data from over 2,400 banks. This consortium data approach, combined with advanced AI algorithms, has enhanced our ability to detect suspicious transaction patterns.

Still, banks are expected to provide an end-to-end explanation of any model, including fighting crime, which greatly inhibits effectiveness.

After years of fighting market manipulation and financial crime, two truths stand out: criminals don’t follow laws or regulations and they take advantage of technological innovation on a massive scale to stay several steps ahead of detection. Therefore, it is critical that we find common ground with regulators to find solutions to address this insidious problem.

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

The second imperative is for regulators to allow the industry to take advantage of the latest capabilities in cloud, AI and machine learning so that we can better respond to new threats, increase effectiveness and improve efficiency.

And finally, there is an opportunity to enhance cooperation. Criminal enterprises are deeply entwined and the financial system needs to reflect this by strengthening cooperation between the private sector, government and law enforcement. One key change will be the deployment of “feedback loops”: communications from law enforcement to banks to confirm whether reported activity was found to be criminal. This requires little investment but allows banks to refine their algorithms based on real-world results.

The fight against financial crime is quite complex. I strongly urge regulators to reduce complexity, not add. Leverage the next wave of innovation to strengthen the integrity of the financial system, together with technology.