AI in Finance and Banking, November 17, 2024

This semi-monthly column highlights news, government documents, NGO/IGO papers ad conferences, industry white papers and reports, academic papers and speeches, and central bank actions on the subject of AI’s fast paced impact on the banking and finance sectors. The chronological links provided are to the primary sources, and as available, indicate links to alternate free versions.

NEWS:

Republicans Won The House and Senate. Here’s What A GOP Congress Could Mean for Tech Policy. Tech Policy Press, November 15, 2024. Sen. Mike Rounds (R-SD) unveiled a set of five AI bills on Aug. 27, 2024, including the Consumers LEARN AI Act (S.4838), the GUIDE AI Act (S.4638), the Increasing AI Transparency in Financial Services Act (S.4638), the Unleashing AI Innovation in Financial Services Act (S.4951 / HR.9309), and an unnamed bill (S.4758) requiring the Secretary of Defense to carry out a pilot program on using artificial intelligence-enabled software.

What an AI-powered finance function of the future looks like, McKinsey, November 4, 2024 | Podcast. Tech veteran and OpenAI CFO Sarah Friar discusses the positive potential of gen AI to change work, society, and democracy; how she is transforming the finance function; and the power of women founders.On this episode of the At the Edge podcast, OpenAI CFO Sarah Friar joins McKinsey senior partner Lareina Yee to talk about how to lead through this era of intense technological adaptation and what it means for the future of the finance function and business leadership.

How banks can supercharge technology speed and productivity, MKinsey, November 6, 2024. Financial institutions can unlock the productivity of their software engineering teams to significantly boost tech innovation without increasing IT budgets. Technology has reshaped banking. Traditional financial institutions have grown their technology teams and are demanding more from them than ever before. Technology teams build innovative new products such as AI-enabled personalized customer experiences, digital payments, and analytics-driven cross-selling. They integrate acquisitions, automate back-office processes, and securely manage vast amounts of data. A look through a bank’s strategy reveals that most of the initiatives require extensive technology delivery.

PAPERS:

Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence, Anton Korinek & Jai Vipra. Working Paper 33139. DOI 10.3386/w33139. Issue Date This paper examines the evolving structure and competition dynamics of the rapidly growing market for foundation models, with a focus on large language models (LLMs). We describe the technological characteristics that shape the AI industry and have given rise to fierce competition among the leading players. The paper analyzes the cost structure of foundation models, emphasizing the importance of key inputs such as computational resources, data, and talent, and identifies significant economies of scale and scope that may create a tendency towards greater market concentration in the future. We explore two concerns for competition, the risk of market tipping and the implications of vertical integration, and we evaluate policy remedies that aim to maintain a competitive landscape. Looking ahead to increasingly transformative AI systems, we discuss how market concentration could translate into unprecedented accumulation of power, highlighting the broader societal stakes of competition policy.

Is Distance from Innovation a Barrier to the Adoption of Artificial Intelligence? Jennifer Hunt, Iain M. Cockburn & James Bessen. Working Paper 33022. DOI 10.3386/w33022. Issue Date Using our own data on Artificial Intelligence publications merged with Burning Glass vacancy data for 2007-2019, we investigate whether online vacancies for jobs requiring AI skills grow more slowly in U.S. locations farther from pre-2007 AI innovation hotspots. We find that a commuting zone which is an additional 200km (125 miles) from the closest AI hotspot has 17% lower growth in AI jobs’ share of vacancies. This is driven by distance from AI papers rather than AI patents. Distance reduces growth in AI research jobs as well as in jobs adapting AI to new industries, as evidenced by strong effects for computer and mathematical researchers, developers of software applications, and the finance and insurance industry. 20% of the effect is explained by the presence of state borders between some commuting zones and their closest hotspot. This could reflect state borders impeding migration and thus flows of tacit knowledge. Distance does not capture difficulty of in-person or remote collaboration nor knowledge and personnel flows within multi-establishment firms hiring in computer occupations.

NGOs/IGOs:

FSB – The Financial Stability Implications of Artificial Intelligence 14 November 2024 | PDF full text – The rapid adoption of AI in finance means that authorities should address information gaps for monitoring, assess the adequacy of current policy frameworks and enhance supervisory and regulatory capabilities. This report revisits the 2017 FSB report on AI and machine learning in financial services by taking stock of recent advancements, exploring use cases in the financial sector and drivers of adoption, as well as new potential benefits and AI-related financial sector vulnerabilities. In the past few years, technological advancements and increased computational power have led to an uptake in AI adoption by financial firms and supervisors. AI offers benefits such as increased operational efficiency, regulatory compliance, financial product customisation and advanced analytics. With the advent of generative AI (GenAI) and large language models, the range of use cases has become more diverse. While AI offers benefits like improved operational efficiency, regulatory compliance, personalised financial products, and advanced data analytics, it may also potentially amplify certain financial sector vulnerabilities. AI-related vulnerabilities that stand out for their potential to increase systemic risk include: (i) third-party dependencies and service provider concentration; (ii) market correlations; (iii) cyber risks; and (iv) model risk, data quality and governance. GenAI also increases the potential for financial fraud and disinformation in financial markets. Misaligned AI systems that are not calibrated to operate within legal, regulatory, and ethical boundaries can also engage in behaviour that harms financial stability. And from a longer-term perspective, AI uptake could also drive changes in market structure, macroeconomic conditions and energy use that could have implications for financial markets and institutions. While existing regulatory and supervisory frameworks address many of the vulnerabilities associated with AI adoption, more work may be needed to ensure that these frameworks are sufficient. The report calls for national financial authorities and international bodies to enhance monitoring of AI developments, assess whether financial policy frameworks are adequate, and enhance their regulatory and supervisory capabilities including by using AI-powered tools.

FSB – OECD – FSB Roundtable on Artificial Intelligence (AI) in Finance: Summary of key findings 30 September 2024 | PDF full text

The adoption of artificial intelligence in the financial sector presents significant opportunities for efficiency and value creation, but it also introduces potential risks that must be addressed. On 22 May 2024, the Organisation for Economic Co-operation and Development (OECD) and the Financial Stability Board (FSB) held a roundtable with experts from the public and private sectors and with academics to analyse trends and use cases of artificial intelligence (AI) in finance. Roundtable participants discussed opportunities and risks and shared emerging best practices regarding policy frameworks. The growing adoption of AI technologies by banks, insurers, and asset managers is resulting in efficiency gains in areas such as risk modelling, trading, claims handling, fraud detection, and financial crime prevention. Generative AI use in finance does not seem transformational at present, at least for regulated financial institutions, as it focuses on operational efficiency improvements and is largely exploratory. Supervisors are also benefiting from AI, with an enhanced capacity to manage large volumes of data. Notwithstanding these benefits, the use of AI also raises concerns in terms of model risk, data protection, governance, privacy, and ethics. It may also create financial stability risks given its potential to amplify interconnections among financial firms as well as complexity and opacity concerns around models and data. Policymakers should strive to promote the safe use of AI in financial services, particularly through global cooperation on standards and best practices.

CALL FOR PAPERS & CONFERENCES:

ECB – The transformative power of AI: economic implications and challenges – Call for papers. Tuesday, 1 and Wednesday, 2 April 2025 Frankfurt am Main– hybrid event – Recent advances in the field of Artificial Intelligence (AI) have the potential to transform our economies, from providing workers with new productivity-enhancing tools to enabling businesses to optimise their pricing strategies in new ways. However, at the same time, AI-powered technologies raise ethical and regulatory concerns. Given this ambivalence, a better understanding is needed of the economic implications and challenges associated with AI. To this end, the European Central Bank is organising a high-level conference entitled “The Transformative Power of AI: Economic Implications and Challenges”, which will take place in Frankfurt am Main on 1-2 April 2025. This conference will bring together leading researchers, practitioners and policymakers to discuss the transformative power of AI. The conference will include keynote speeches by Kristina McElheran (University of Toronto), Jonathan Haskel (Imperial College London, TBC), and Claire Monteleoni (University of Colorado, Boulder). It will also feature a panel discussion on fostering the creation and diffusion of AI while addressing its risks with Jesús Fernández Villaverde (University of Pennsylvania), Valérie Pisano (Mila, CEO), Lucilla Sioli (European Commission, TBC), Philippe Aghion (INSEAD, London School of Economics and College de France, TBC) and Karine Perset (OECD, TBC). ECB Executive Board member Philip R. Lane  will give an introductory address. The conference will be web-streamed, but we expect physical presence of participants presenting or discussing the papers.

Artificial Intelligence, Big Data, and the Path Ahead for Productivity, Remarks by Lisa D. Cook Member Board of Governors of the Federal Reserve Systemat “Technology-Enabled Disruption: Implications of AI, Big Data, and Remote Work,” a conference organized by the Federal Reserve Banks of Atlanta, Boston, and Richmond Atlanta, Georgia October 1, 2024.

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Posted in: AI in Banking and Finance, Big Data, Financial System, Legal Research
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