This semi-monthly column highlights news, government documents, NGO/IGO papers, 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:
As artificial intelligence (AI) continues to shape industries worldwide, its role in banking has quietly evolved behind the scenes. Forbes, January 30, 2025. While much of the attention around AI in banking has focused on chatbots or fraud detection, there is an equally significant shift happening within lending. AI-powered tools are enabling banks to refine credit policies, improve risk assessments, and, most importantly, enhance the customer experience. Banks are leveraging AI to transform lending, not through flashy, customer-facing technologies, but through tools designed to work behind the scenes. These innovations enable banks to deliver more personalized loan offerings, adapt to changing markets, and say “yes” to more customers than ever before.
Banks increasing tech spend overall in 2025: Research, American Banker, January 30, 2025.
Goldman Sachs hires Amazon exec in senior AI engineering role, Reuters, January 29, 2025. Goldman Sachs has hired Daniel Marcu from Amazon.com as its global head of artificial intelligence engineering and science to help develop and refine artificial intelligence platforms and products, according to a memo seen by Reuters. Before joining Goldman, Marcu was vice president of Web and Knowledge Services in Alexa Information and then Amazon Artificial General Intelligence, the memo said. He joins a roster of technology experts at Goldman that includes Chief Information Officer Marco Argenti, who also worked at Amazon Web Services. Goldman Sachs CEO David Solomon said during the bank’s fourth-quarter earnings call earlier this month that Goldman is leveraging AI solutions to scale and transform its engineering capabilities, simplify and modernize its technology, and drive productivity.
AI will have a major impact on labor markets. Here’s how the US can prepare. FedScoop, December 30, 2024. The nation can do better at forecasting AI-driven job and skill changes, including with a data-focused nonprofit that examines the technology’s impact. Brent Orrell, Suzette Kent and Jason Owen-Smith.
PAPERS:
Artificial Intelligence and Bank Supervision, John Mullin. August 20, 2024 Federal Reserve Research, Richmond. Artificial intelligence has come a long way since English mathematician, logician, and cryptographer Alan Turing’s seminal 1950 essay, “Computing Machinery and Intelligence,” which explored the idea of building computers capable of imitating human thought. In 1997, almost 50 years after Turing’s essay, AI posted a historic breakthrough when the IBM supercomputer Deep Blue won a chess match against reigning world champion Garry Kasparov. Since then, AI’s capabilities have improved rapidly, largely through advances in machine learning (ML), especially in ML models that use digital neural networks to classify text, images, or other data. (See “Machine Learning,” Econ Focus, Third Quarter 2018.) ML is now commonly used in industrial applications, and it underpins a vast number of consumer services, from Google searches to Netflix movie recommendations. Of more recent note, ML technology is the basis of the new generative AI programs, such as ChatGPT, designed to, among other things, conduct useful conversations with human beings. Financial institutions in the U.S. have hardly sat idle amid these developments. On the contrary, they have developed and implemented AI-based applications for a wide variety of purposes.
AI and Work: How to Build New Data Foundations, American Enterprise Institute. Jason Owen-Smith, October 2024.
Key Points
- Actionable evidence about the economic and jobs effects of critical and emerging technologies such as AI requires trusted consensus measures of technology capabilities and current and emerging skill needs.
- Partnerships connecting states, higher education, and businesses can precisely craft measures fit to regional economies and industry contexts to support programs that make states the laboratories of democracy and opportunity.
- Scaling local innovations to address national concerns will help sustain the skilled, agile workforce needed to ensure US competitiveness and security.
- The necessary data exist. Key measures are possible and immensely valuable. The US needs a mechanism to develop consensus, facilitate innovation, and streamline production and dissemination of results.
- A new type of data-driven, nonpartisan institute to serve these needs is within our reach.
Research: How Gen AI Is Already Impacting the Labor Market, Harvard Business Review – AI and machine learning, In new research, forthcoming in Management Science, we explore the impact gen AI has already had on the labor market by examining trends in demand for online freelancers. Our findings show significant short-term job replacement after these tools were introduced, and that jobs prone to automation, like writing and coding, were the most affected by ChatGPT. Our research also examines how competition, job requirements, and employer willingness-to-pay have changed to better understand how the online job market is evolving with the rise of gen AI. Although still in its early stages, gen AI’s impact on online labor markets is already becoming discernible, suggesting potential shifts in long-term labor market dynamics that could bring both challenges and opportunities.
NGO/IGOs:
Governance of AI adoption in central banks. Report by the Consultative Group on Risk Management (CGRM) established at the BIS Representative Office for the Americas, 29 January 2025. Artificial intelligence (AI) presents huge opportunities for central banks. At the same time, its adoption entails complex risk management challenges. The use cases for AI span a broad range of critical functions of a central bank including data analysis, research, economic forecasting, payments, supervision and banknote production. The adoption of AI presents new risks and can amplify existing ones. The potential risks are wide-ranging and include those around data security and confidentiality, risks inherent to AI models (eg “hallucinations”) and, importantly, reputational risks. The potential risk exposure for central banks can be significant, owing to the criticality and sensitivity of the data they handle as well as their central role in financial markets. This report on the governance of AI adoption in central banks provides guidance on the implementation of AI at central banks and proposes a governance and risk management framework. A comprehensive risk management strategy can leverage existing risk management models and processes, in particular the well established three lines of defence model. In incorporating the specific issues around AI and its use cases, risk managers at central banks can make use of the frameworks proposed by a number of international bodies. A good governance framework is key for adopting AI. The report proposes an adaptive governance framework and recommends ten practical actions that central banks may want to undertake as part of their journey in adopting AI. The report is the outcome of work conducted by Bank for International Settlements (BIS) member central banks in the Americas within the Consultative Group on Risk Management (CGRM), which brings together representatives of the central banks of Brazil, Canada, Chile, Colombia, Mexico, Peru and the United States. The Artificial Intelligence Task Force that prepared this report was co-led by Alejandro de los Santos.
How Artificial Intelligence Will Affect Asia’s Economies. IMF, January 5, 2025. IMF, AI may widen inequality, but policymakers can counteract this with more effective social safety nets, reskilling programs, and regulations to promote ethical use of the technology. Asia-Pacific’s economies are likely to experience labor market shifts because of artificial intelligence, with advanced economies being affected more. About half of all jobs in the region’s advanced economies are exposed to AI, compared to only about a quarter in emerging market and developing economies. However, as we show in our latest Asia-Pacific Regional Economic Outlook, there are also more jobs in the region’s advanced economies that can be complemented by AI, meaning that the technology will likely enhance productivity rather than replace these roles altogether. The concentration of such jobs in Asia’s advanced economies could worsen inequality between countries over time. While about 40 percent of jobs in Singapore are rated as highly complementary to AI, the share is just 3 percent in Laos. AI could also increase inequality within countries. Most workers at risk of displacement in the Asia-Pacific region work in service, sales, and clerical support roles. Meanwhile, workers who are more likely to benefit from AI typically work in managerial, professional, and technician roles that already tend to be among the better paid professions. As the Chart of the Week shows, we also find that women are more likely to be at risk of disruption from AI because they are more often in service, sales, and clerical roles. Men, by contrast, are more represented in occupations that are unlikely to be impacted by AI at this stage, like farm workers, machine operators, and low-skill elementary workers.