Ladies and Gentlemen:
The Bank Policy Institute[1] is writing to respond to the Office of Science and Technology Policy’s Request for Information; Regulatory Reform on Artificial Intelligence.[2] We support and welcome the opportunity to contribute to OSTP’s efforts, consistent with the recommendations of the July 23, 2025 AI Action Plan released by the White House,[3] to identify priorities for federal regulatory reform and other agency action necessary to promote AI innovation and adoption in the United States.[4]
BPI and its member banks are committed to using AI responsibly in their businesses and operations. As the Government Accountability Office recently noted, “[f]inancial institutions are using AI for many activities … includ[ing] automated trading, countering threats and illicit finance, credit decisions, customer service, investment decisions, and risk management.”[5]
The adoption of AI tools in the financial sector is at a critical inflection point. Although banks have been using traditional AI and machine learning tools for decades,[6] the emergence of generative AI, including large language models (collectively, “GenAI”), has opened the door to transformational benefits for financial institutions. Federal Reserve Board Vice Chair for Supervision Michelle Bowman recently stated that AI technologies “have the potential to transform how business is conducted [for banks], including the way we detect and prevent fraud, manage risk, and provide customer service.”[7] We agree.
These opportunities are emerging amidst a regulatory and supervisory environment that often discourages, rather than incentivizes, responsible AI innovation by financial institutions. Specifically, some BPI members have experienced difficulty engaging with supervisors and examiners who may not appreciate the benefits and risk profiles of AI use cases. This can lead to hesitation, if not risk-aversion, across organizations when it comes to AI adoption.
Further, banking organizations face threats from bad actors who themselves use cutting-edge AI technology to attack financial institutions, threatening the safety and stability of banks and their customers. In the face of these threats, banking regulators should adjust their expectations in order to provide banks with the flexibility needed to deploy AI-based defenses quickly and safely. To date, one of the most widely adopted AI use cases in the U.S. banking system has been to harness AI-powered technologies to counter the efforts of malicious foreign and domestic actors.[8] As the technologies used by these bad actors become more advanced, it will be important for banks to be able to embed AI into their defensive toolkits to most effectively combat these threats.
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[1] The Bank Policy Institute is a nonpartisan public policy, research and advocacy group that represents universal banks, regional banks, and the major foreign banks doing business in the United States. The Institute produces academic research and analysis on regulatory and monetary policy topics, analyzes and comments on proposed regulations, and represents the financial services industry with respect to cybersecurity, fraud, and other information security issues.
[2] Notice of Request for Information; Regulatory Reform on Artificial Intelligence, 90 Fed. Reg. 46,422 (Sept. 26, 2025), https://www.govinfo.gov/content/pkg/FR-2025-09-26/pdf/2025-18737.pdf (Office of Science and Technology Policy).
[3] Winning the Race: America’s AI Action Plan, THE WHITE HOUSE (July 2025), https://www.whitehouse.gov/wp-content/uploads/2025/07/Americas-AI-Action-Plan.pdf (the “AI Action Plan”).
[4] This document is approved for public dissemination. The document contains no business-proprietary or confidential information. Document contents may be reused by the government in developing the AI Action Plan and associated documents without attribution.
[5] Artificial Intelligence: Use and Oversight in Financial Services, UNITED STATES GOVERNMENT ACCOUNTABILITY OFFICE REPORT TO CONGRESSIONAL COMMITTEES (May 19, 2025), https://www.gao.gov/assets/gao-25-107197.pdf (“GAO AI Report”).
[6] The integration of AI in the form of machine learning within the financial sector traces its origins to the 1980s, when it was employed primarily to identify and counteract fraudulent activities. K. W. Kindle, R. S. Cann, M. R. Craig, and T. J. Martin, PFPS – Personal Financial Planning System – AAAI, in Proceedings of the Eleventh National Conference on Artificial Intelligence, pp. 344-349, 1989.
[7] Vice Chair Michelle Bowman, Embracing Innovation, Remarks at the Wyoming Blockchain Symposium 2025, FEDERAL RESERVE (Aug. 19, 2025), https://www.federalreserve.gov/newsevents/speech/bowman20250819a.htm.
[8] See, e.g., GAO AI Report, supra note 5 at 11 (“AI could improve the security of institutions and markets through better detection of cyber threats and illicit finance … For example, AI can help combat synthetic identity fraud by identifying cases that human analysts cannot easily detect.”); Report on Artificial Intelligence, BIPARTISAN H. TASK FORCE ON ARTIFICIAL INTELLIGENCE, 118th Cong., at 235 (Dec. 2024), https://republicans-science.house.gov/_cache/files/a/a/aa2ee12f-8f0c-46a3-8ff8-8e4215d6a72b/6676530F7A30F243A24E254F6858233A.ai-task-force-report-final.pdf (discussing how financial institutions are using AI for customer identity verification and detecting suspicious activity); AI Innovation Explored: Insights into AI Applications in Financial Services and Housing, Staff Report, BIPARTISAN WORKING GROUP ON ARTIFICIAL INTELLIGENCE, H. COMM. ON FIN. SERVS., 118th Cong., at 15 (July 18, 2024), https://financialservices.house.gov/uploadedfiles/bipartisan_working_group_on_ai_staff_report.pdf (noting that fraud detection has been a leading AI use case in the banking industry).
