On Friday, the Federal Reserve Governor Michael S. Barr spoke at the Federal Reserve Bank of San Francisco in California, addressing the use of generative AI in the banking and fintech sectors. He praised the partnership between fintech companies and banks, highlighting how it has driven innovation in the banking industry.
The Governor said: “I’d like to speak about responsible innovation in the context of generative artificial intelligence (Gen AI) in banking and how bank–fintech partnerships may accelerate the integration of the technology and banking”
Emphasizing the necessity of AI in the banking sector, he added:
“Today, banks appear to be moving cautiously with their Gen AI use, which reflects the current state of the technology, as well as banks’ internal organizational structure and the highly regulated environment in which they operate. At the same time, Gen-AI offers enormous potential to significantly alter the business of banking, provided that the risks are managed appropriately. Given rapid advances in Gen AI every quarter, in the not-too-distant future, we may approach a point at which Gen AI becomes an imperative—a competitive necessity—in banking”
Commending the advancements in AI, Governor stated: “Let me begin with why Gen AI has such potential for the banking industry. The business of banking is data-driven—data underpin the decisions to set yields on deposits, underwrite and price credit products, and manage the attendant risks. While traditional forms of artificial intelligence have become essential in areas like fraud detection, Gen AI offers new possibilities for data analysis, taking into account a broader and more diverse set of data. Gen AI has benefits for document analysis, which could be applied to improve credit underwriting”
The Federal Governor also cautioned about the need to strike a balance between innovation and risk when it comes to the challenges posed by generative AI in the banking sector.
The Governer said: “Of course, one reason is that banks are being appropriately cautious in the highly regulated environment in which they operate. Beyond that, for some of these applications, the technology is not fully mature. For instance, Gen AI systems may still hallucinate, generating plausible sounding but inaccurate information. Relatedly, because Gen AI usually involves stochastic processes, answers can differ in response to the same query asked at different times or to similar queries. This is tough to square with the requirements of banking, where decisions must be well-controlled, numerically and legally precise, explainable, and replicable”
“Information security is another key concern. To the extent that a Gen AI-powered agent is accessing sensitive customer data and authorizing transactions, it becomes an attractive target for malicious actors. Further, as Gen AI models process vast amounts of data, there’s a risk that proprietary or customer information could be inadvertently included in the model’s outputs or responses, leading to legal violations and privacy breaches”
“Moreover, business processes at banks have not evolved to optimize Gen AI usage. Gen AI requires data and infrastructure to be effective. Many banks have existing tech debt, and their data storage is siloed and not optimized for firmwide analysis. Furthermore, there may be organizational practices that may make it hard to evolve existing processes to ones optimized by AI”
