Hybrid Hearing - Keeping Up with the Codes – Using AI for Effective RegTech (EventID=114764)

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Connect with the House Financial Services Committee Get the latest news: https://democrats-financialservices.house.gov/ Follow us on Facebook: https://www.facebook.com/HouseFinancialCmte Follow us on Twitter: https://twitter.com/FSCDems ___________________________________ On Friday, May 13, at 9:00 a.m. (ET) Task Force on Artificial Intelligence Chairman Bill Foster and Ranking Member Anthony Gonzalez will host a hybrid hearing entitled, “Keeping Up with the Codes – Using AI for Effective RegTech." ___________________________________ Witnesses for this one-panel hearing will be: • Kevin Greenfield, Deputy Comptroller for Operational Risk Policy, Office of the Comptroller of the Currency (OCC) • Melanie Hall, Commissioner, Division of Banking and Financial Institutions, State of Montana, and Chair, Board of Directors, Conference of State Bank Supervisors (CSBS) • Kelly Lay, Director, Office of Examination and Insurance, National Credit Union Administration (NCUA) • Jessica Rusu, Chief Data Information and Intelligence Officer, Financial Conduct Authority (FCA), United Kingdom Overview The events of the 2008 global financial crisis, which included failures in regulatory compliance and supervision, spurred interest and growth in newer forms of technology in the financial industry.1 While their meanings can be relativity fluid, “RegTech” (Regulatory Technology) refers to the use of emerging technologies such as Artificial Intelligence (AI) (and a subset of AI known as Machine Learning (ML)) by financial institutions to ensure compliance with applicable laws and regulations. Additionally, “SupTech” (Supervisory Technology) refers to the use of these technologies by financial regulators to support their supervisory, rulemaking, and enforcement efforts.2 As technological developments continue to transform financial markets and institutions, RegTech and SupTech solutions are emerging as regulatory focus areas. Taken together, in the financial services space, these approaches may help both financial institutions and government regulators monitor transactions, evaluate risk, catch noncompliance, identify illicit finance, and implement regulatory changes in real-time. Application of RegTech and SupTech Technologies in the Financial Sector In the past few years, financial firms have used algorithms – precoded sets of procedures or instructions designed to perform a specific task or solve a mathematical problem – to help financial institutions meet regulatory requirements (through RegTech) as well as enable the development of new technologies by regulators to strengthen their supervisory capabilities (through SupTech). Technologies such as AI (including ML), cloud-based services, and application programming interfaces (APIs) have enabled the growth of RegTech and SupTech to improve supervisory processes while ensuring compliance with regulatory requirements. AI vendors project that the use of RegTech programs and AI will continue to grow significantly over the next few years. Globally, the RegTech market is anticipated to reach $55.28 billion by 2025, with a compound annual growth rate of 52.8%, according to some AI industry estimates. The use of AI and related emerging technologies can offer a broad range of benefits for both financial institutions and regulators. For regulated financial institutions, such as banks and credit unions, RegTech can “improve compliance outcomes, enhance risk management capabilities, and generate new insights into the business for improved decision-making.” At the same time, SupTech may provide regulators with “improved oversight, surveillance and analytical capabilities, and generate real-time indicators of risk to support judgement-based supervision and policymaking.” In both contexts, proponents of AI have pointed to the improvement in the speed of data analysis and the ability to synthesize large datasets that would otherwise be too cumbersome to effectively digest through traditional means. However, as AI programs have grown in popularity, so have concerns about potential adverse outcomes arising from their use. Algorithmic bias, explainability, and transparency are major areas of concern surrounding the potential adoption of this new technology. Some policymakers have expressed concerns that the use of AI technologies could result in financial market instability or discrimination against protected groups.9 For example, outputs from AI algorithms may exhibit algorithmic bias, wherein biases associated with the underlying data used by AI algorithms (such as in automated lending decisions or anti-money laundering screening programs) may unfairly disadvantage people of color or women.10 Together, these multiple issues have created ongoing challenges and related costs for both financial institutions and government regulators. National Security, Illicit Finance, and... Hearing page: https://democrats-financialservices.house.gov/events/eventsingle.aspx?EventID=409378