On June 4, the U.S. Under Secretary for Domestic Finance, Nellie Liang, delivered a speech at the OECD-FSB Roundtable on Artificial Intelligence (AI) in Paris. Liang noted that while AI has been around for many years, the recent advances of generative AI will be evolving and will have the potential to transform the financial sector even more. The latest advancements in AI models can process vast amounts of data, generate content, and automate decision-making, welcoming new opportunities and challenges for financial institutions and regulators. The biggest takeaway was that AI holds transformative potential for the financial sector by enhancing efficiency and innovation, yet it also posed challenges such as model risk and privacy issues, necessitating vigilant evolution of regulatory frameworks to ensure safety and fairness.

On AI uses, Liang highlighted that financial institutions have explored AI applications to reduce costs, increase productivity, and develop new products. For instance, AI can be used to automate back-office functions, enhance customer service through chatbots, and inform trading strategies. AI’s expertise will be its abilities to process large volumes and types of information that would be otherwise impractical or impossible to analyze. Concerning risks, Liang pinpointed model risk as a prime issue, contending that robust data governance and careful design can counteract potential pitfalls. AI may also introduce or amplify interconnections among financial firms, leading to potential financial stability risks. Furthermore, Liang focused on the increased use of AI in financial services and the concerns it raised about data privacy, surveillance, and potential biases in AI-driven decision-making.

Liang noted how addressing these AI risks through existing regulatory frameworks, such as principles of model risk management, third-party risk management, and consumer protection laws would be possible. However, she noted, regulators need to assess whether AI will introduce new risks that require adjustments to the regulatory framework. Additionally, policymakers will be exploring the use of AI for identifying data anomalies, countering illicit finance and fraud, and improving fraud detection through comprehensive databases.