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:
The Finance Sector Is Hitting an Inflection Point With AI, March 17, 2025, Newsweek. If you are among the majority of Americans who use mobile banking services, you’re probably familiar with the facial or fingerprint recognition tools that let you access your accounts with a single look or touch of the screen. A national survey conducted last year by Morning Consult and the American Bankers Association found digital banking to be the most popular method among U.S. consumers, with only 8 percent of Americans visiting in-person branch locations. MSU Federal Credit Union, which of course offers online banking, also has an AI feature on its app that tells members if there is a better way to shop at their favorite grocery store, offering a guide on which cards to use with which vendors. The credit union is hoping to ramp up those capabilities in the near future. For example, members may soon be able to avoid going to branch locations to facilitate large wire transactions or verify your identity with a wet signature altogether. Or at least, that’s what Benjamin Maxim, the chief digital strategy and innovation officer at MSUFCU, is hoping members of the credit union will be able to do thanks to artificial intelligence. “If we’re calling to verify who this person is, we could have them simply do a biometric face scan that matches up with what we’d have,” Maxim told Newsweek. “It would be way more efficient and effective than asking 20 questions about your account.”
Jamie Dimon On AI impact: It Will Replace Jobs In Banking And Financial Services. Business Today, March 15, 2025. Artificial Intelligence is as transformative as the steam engine and the internet — says JPMorgan Chase CEO Jamie Dimon in this candid conversation at the Stanford Graduate School of Business. AI is already revolutionizing banking, fraud detection, and trading, but its biggest impact? Jobs. Dimon warns that AI will replace jobs across industries, just as tractors and automation did in agriculture and manufacturing. While some roles will evolve with AI assistance, others will disappear entirely. With JPMorgan investing $2 billion in AI and deploying 450+ use cases, from risk management to customer service automation, Dimon stresses the need for businesses to prepare for workforce disruptions through attrition, reskilling, and redeployment. The discussion also covers open banking and data privacy, with Dimon taking a strong stance against unchecked data sharing. Should financial institutions be required to share consumer data? How should AI be regulated to balance innovation with ethical concerns? With AI changing the global workforce and financial markets, this is a must-watch conversation on the future of work, banking, and regulation
China’s central bank vows to promote applications of AI large language models, Global Times, March 13, 2025. The People’s Bank of China (PBC), the central bank, held a meeting to reinforce its technological work in 2025, vowing to promote the applications of artificial intelligence (AI) large language models and related technologies in the financial sector to accelerate the process of financial digitalization. The meeting emphasized plans to vigorously strengthen the construction of the science and technology talent team, and propel the high-quality development of technological work to a new level, the PBC said in a statement on its website on Monday. The central bank pledged to strengthen the integration of business and technology, deepen data governance, promote the application of new technologies, and enhance information technology support for the central bank’s mission. It also vowed to advance the construction of an independent, controllable, secure, and efficient financial infrastructure system, and safeguard cybersecurity and data security. The financial sector generates massive data volumes, and technological tools can process data efficiently to enhance the operational efficiency and security of financial activities, Xi Junyang, a professor at the Shanghai University of Finance and Economics, told the Global Times on Monday.
PAPERS:
NBER – A Quest for AI Knowledge .Working Paper 33566. DOI 10.3386/w33566. Issue Date This paper examines how the introduction of artificial intelligence (AI), particularly generative and large language models capable of interpolating precisely between known data points, reshapes scientists’ incentives for pursuing novel versus incremental research. Extending the theoretical framework of Carnehl and Schneider (2025), we analyse how decision-makers leverage AI to improve precision within well-defined knowledge domains. We identify conditions under which the availability of AI tools encourages scientists to choose more socially valuable, highly novel research projects, contrasting sharply with traditional patterns of incremental knowledge growth. Our model demonstrates a critical complementarity: scientists strategically align their research novelty choices to maximise the domain where AI can reliably inform decision-making. This dynamic fundamentally transforms the evolution of scientific knowledge, leading either to systematic “stepping stone” expansions or endogenous research cycles of strategic knowledge deepening. We discuss the broader implications for science policy, highlighting how sufficiently capable AI tools could mitigate traditional inefficiencies in scientific innovation, aligning private research incentives closely with the social optimum.
NBER – AI and the Extended Workday: Productivity, Contracting Efficiency, and Distribution of Rents. Working Paper 33536. DOI 10.3386/w33536. Issue Date MarchThis study investigates how occupational AI exposure impacts employment at the intensive margin, i.e., the length of workdays and the allocation of time between work and leisure. Drawing on individual-level time diary data from 2004–2023, we find that higher AI exposure—whether stemming from the ChatGPT shock or broader AI evolution—is associated with longer work hours and reduced leisure time, primarily due to AI complementing human labor rather than replacing it. This effect is particularly pronounced in contexts where AI significantly enhances marginal productivity and monitoring efficiency. It is further amplified in competitive labor and product markets, where workers have limited bargaining power to retain the benefits of productivity gains, which are often captured by consumers or firms instead. The findings question the expectation that technological advancements alleviate human labor burdens, revealing instead a paradox where such progresses compromise work-life balance.
Artificial Intelligence and the Labor Market. Working Paper 33509. DOI 10.3386/w33509. Issue Date We leverage recent advances in NLP to construct measures of workers’ task exposure to AI and machine learning technologies over the 2010 to 2023 period that vary across firms and time. Using a theoretical framework that allows for a labor-saving technology to affect worker productivity both directly and indirectly, we show that the impact on wage earnings and employment can be summarized by two statistics. First, labor demand decreases in the average exposure of workers’ tasks to AI technologies; second, holding the average exposure constant, labor demand increases in the dispersion of task exposures to AI, as workers shift effort to tasks that are not displaced by AI. Exploiting exogenous variation in our measures based on pre-existing hiring practices across firms, we find empirical support for these predictions, together with a lower demand for skills affected by AI. Overall, we find muted effects of AI on employment due to offsetting effects: highly-exposed occupations experience relatively lower demand compared to less exposed occupations, but the resulting increase in firm productivity increases overall employment across all occupations.
GOVERNMENT DOCUMENTS:
NGO/IGO:
The AI supply chain. BIS Papers | No 154 | 18 March 2025. by Leonardo Gambacorta and Vatsala Shreeti. PDF full text – The rapid advancement of artificial intelligence (AI) relies on a complex supply chain comprising five key layers: hardware, cloud infrastructure, training data, foundation models and AI applications. This paper examines the market structure of each layer and highlights the economic forces shaping them: rapid technological change, high fixed costs, economies of scale, network effects and, in some cases, strategic behaviour by dominant firms. We also highlight the expanding influence of big tech companies across the AI supply chain. We discuss the challenges for consumer choice, innovation, operational resilience, cyber security and financial stability.
Putting AI agents through their paces on general tasks. BIS Working Papers | No 1245 | 21 February 2025 by Fernando Perez-Cruz and Hyun Song Shin. Artificial intelligence (AI) “agents” that have recently been rolled out can use computers by taking control of the keyboard and mouse. These AI agents can use a computer just like a person would and can receive instructions in English. By end-2025, these AI agents are expected to become commonplace and to change how we work and use the internet. We assessed these AI agents on the general skills needed to play games such as Wordle – recognising when tiles change colour, using feedback to arrive at informed guesses and inputting those guesses using the computer keyboard and mouse.