Some industry experts consider data as the new oil. Just as it does for the finance industry, the rapid digitalisation of the economy comes with opportunities and challenges for financial regulators. On the positive side, new information is available, with vital insights into financial risks that regulators spend considerable time trying to understand. The abundance of data provides details on global money patterns, economic trends, onboarding decisions, noncompliance with regulations and many more critical subjects. More importantly, the data provides answers to regulators’ questions about the challenges of new technology. 

Thanks to digitalisation, regulators have the opportunity to collect and examine much more data and see more of it in real-time. The possibility for issues develops from the concern that regulators existing technology cannot harness the data. Ironically, this rise of new data is overwhelming for many companies. Without applying digital technology, the stream of new data financial regulators need to manage systems cannot be used appropriately. This challenge of managing the abundance of new data is where artificial intelligence can play an important role.

In 2019, Mark Carney, the Gov of the Bank of England, emphasised that financial regulators needed to integrate AI to maintain pace with the rising amount of data flowing into businesses. Carney highlighted that the bank received 65 billion pieces of data every year from companies it is responsible for, and examining all of this information would be overwhelming without supportive technology. In today’s world, the volume of data has only continued to increase, especially if you factor in other data sources generated from public records, news and social media channels.

AI emerged over 70 years ago, and for years AI experts predicted that it would change our lives significantly, but it has taken a long time before we have seen the impact of AI on our daily lives. It was only until recently that we discovered the signs of AI and how it could solve real-world problems. This discovery is down to having enough data available in a digitised format to justify using AI. Today, we have so much data available we can use AI, but in sectors such as finance, AI is becoming necessary to maintain pace. Financial regulators are beginning to explore how AI and similar technologies can improve their work. Businesses continue to test the potential of new technologies to monitor performance. This work is happening in the finance industry, particularly to enhance compliance systems.

Financial regulators worldwide have become more active in monitoring the use of AI rather than adopting it for their benefit. How can AI be used to improve areas of poor regulatory performance? One example has emerged from the war in Ukraine. The Russian invasion has triggered a new level of sanctions against Russian oligarchs attempting to hide their money. Financial institutions are obliged to monitor accounts and identify transactions by these sanctioned groups. If law enforcement agencies had applied AI-powered analytics to examine data from global transactions, they would be able to detect particular patterns within sanctioned groups. For the time being, however, most financial groups lack these resources. 

Another example relates to the millions of refugees and the issue of human trafficking. Banks are required to maintain anti-money laundering systems to detect and report the movement of money that could indicate human trafficking and other crimes, but many of these systems fail to be very effective. 

AI-powered compliance systems would be far more efficient at detecting these issues and significantly impact many challenges our planet faces.