This semi-monthly column highlights news, government documents, NGO/IGO papers, industry white papers and reports, academic papers, conferences and speeches 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.
CONFERENCES:
Business Wire, – Money20/20, the world’s leading fintech show and the place where money does business, brings the largest gathering of leading AI brands together with major players in banking and fintech at its upcoming USA show in Las Vegas on Oct. 27-30, 2024. This year’s groundbreaking agenda features an unprecedented convergence of AI pioneers and financial powerhouses, setting the stage for fintech’s next revolution under the theme “Human X Machine.” Leading AI disruptors like Daniela Amodei, President of Anthropic, Malcolm deMayo, Global VP Financial Services Industry of NVIDIA, and Sarah Friar, Chief Financial Officer of OpenAI will be joined by executives from leading US financial services powerhouses such as JPMorgan Chase, Mastercard, and Wells Fargo for four days of important AI announcements and conversations. Money20/20 will bring all key AI stakeholders and providers together under one roof to connect and dive deep into the industry’s hottest topics and biggest questions, leaving attendees with real, actionable takeaways. Human X Machine will celebrate the synergy between human and artificial intelligence, exploring how this dynamic relationship is revolutionizing business models and transforming customer experiences across finance. This includes Aiana, Money20/20’s very own AI-powered fintech host of the Sentient Stage.
NEWS:
National Community Reinvestment Coalition, September 30, 2024. NCRC and Fintechs Urge Regulators to Use AI to Detect and Eliminate Lending Discrimination. Government should act to harness AI’s power to detect and eliminate discrimination in lending, leading fintechs and economic equity advocates argued in a letter to regulators “One of AI/[machine learning]’s beneficial applications is to make it possible, even using traditional credit history data, to score previously excluded or unscorable consumers,” the letter states. “In some cases, AI models are enabling access and inclusivity.” AI systems have advanced more rapidly than the government’s ability to effectively regulate them. Agencies have struggled to implement an approach that can be applied uniformly to the financial services industry. That lag increases the risk that corporate decisions powered by machines may introduce new forms of discrimination, inequity and bias into life-altering decisions for things such as mortgages, business loans and employment and startup investments for small businesses, especially for low- and moderate-income (LMI) people.
International Banker, . Is AI the Cornerstone for Financial Inclusion? – Can artificial intelligence (AI) be the disruptor that finally makes financial services more accessible? In this article, we will explore AI’s transformative potential for improving access to credit by drawing on insights from top journals and taking a historical perspective. We will also examine whether AI is likely to level the playing field in financial inclusion and discuss how historical technology disruptions have shaped access to credit. We will wrap up this article by exploring AI’s challenges and opportunities. AI’s role in financial inclusion can be better understood by focusing on the key technological disruptions that have transformed loan assessments. If we focus on the primary methods of making loan decisions, three distinct historical periods become apparent.
Bloomberg, September 23, 2024 – HSBC Looking to Join AI Infrastructure Finance Boom, Keefe Says – HSBC Holdings Plc wants to join in the rush to finance the infrastructure needed to roll out artificial intelligence, according to one of the lender’s most senior investment bankers.
The European Union’s biggest banks have spent years quietly creating a new way to pay that could finally allow customers to ditch their Visa and Mastercard cards—the latest sign that the region is looking to dislodge two of the most valuable financial firms on the planet. Wero, as the project is known, is now rolling out across much of western Europe. Backed by 16 major banks and payment processors including BNP Paribas, Deutsche Bank and Worldline, the platform will eventually allow a German customer to instantly settle up with, say, a hotel in France using their own bank account instead of a Visa or Mastercard.
CSO, September 19, 2024. Deepfakes break through as business threat. Deepfakes targeting financial data are no longer hypothetical, with many executives saying their companies have been targeted with deepfake scams in the past year.
Markets Insider via MSN, September 21, 2024. AI will nearly double demand for copper, which is already facing a global shortage
- The AI boom will nearly double demand for copper, mining firm BHP told the Financial Times.
- BHP predicts demand will reach 52.5 million tons a year, 72% higher from 2021 levels.
- Copper is a necessary material for electrification, and AI data centers will require power capacity to expand.
- A rising copper shortage is set to intensify as artificial intelligence boosts demand for the red metal by as much as 72% in the coming decades, according to mining giant BHP.
Chief Financial Officer Vandita Pant told the Financial Times that AI data centers will account for 6% to 7% of copper demand by 2050. These centers currently make up less than 1%, she noted, but there increasing buildout requires more of the red metal. By another measure, BHP expects global demand for copper to rise 52.5 million tons a year by the mid-century, compared to 30.4 million tons in 2021. In recent years, a shortfall in the red metal has sparked concern among industries that depend on it, and commodity experts have forecast the demand-supply imbalance to hike prices through the years to come. Copper is a key material in various economic sectors, used in everything from construction to machinery.
PAPERS:
NBER. Economic Policy Challenges for the Age of AI. . Working Paper 32980. DOI 10.3386/w32980. Issue Date This paper examines the profound challenges that transformative advances in AI towards Artificial General Intelligence (AGI) will pose for economists and economic policymakers. I examine how the Age of AI will revolutionize the basic structure of our economies by diminishing the role of labor, leading to unprecedented productivity gains but raising concerns about job disruption, income distribution, and the value of education and human capital. I explore what roles may remain for labor post-AGI, and which production factors will grow in importance. The paper then identifies eight key challenges for economic policy in the Age of AI: (1) inequality and income distribution, (2) education and skill development, (3) social and political stability, (4) macroeconomic policy, (5) antitrust and market regulation, (6) intellectual property, (7) environmental implications, and (8) global AI governance. It concludes by emphasizing how economists can contribute to a better understanding of these challenges.
NBER. The Rapid Adoption of Generative AI. . Working Paper 32966. DOI 10.3386/w32966. Issue Date Generative Artificial Intelligence (AI) is a potentially important new technology, but its impact on the economy depends on the speed and intensity of adoption. This paper reports results from the first nationally representative U.S. survey of generative AI adoption at work and at home. In August 2024, 39 percent of the U.S. population age 18-64 used generative AI. More than 24 percent of workers used it at least once in the week prior to being surveyed, and nearly one in nine used it every workday. Historical data on usage and mass-market product launches suggest that U.S. adoption of generative AI has been faster than adoption of the personal computer and the internet. Generative AI is a general purpose technology, in the sense that it is used in a wide range of occupations and job tasks at work and at home.
This paper explores the role of artificial intelligence (AI) in improving value creation within multinational enterprises (MNEs) by transcending the limitations of bounded rationality. Businesses and managers are increasingly using AI, particularly in decision-making processes, which are especially pertinent within MNEs due to the complexity that they face in operating across diverse institutional, cultural, and market environments. We argue that AI’s computational rationality—rooted in its ability to process vast amounts of data and provide optimized decisions—can complement traditional heuristic approaches that are constrained by humans’ bounded rationality. Through an exploratory analysis that draws on case studies, workshops, and expert interviews, we examine how AI rationality assists in adapting products and services to foreign contexts, thereby optimizing value creation. The findings suggest that, while AI offers substantial potential to improve decision-making outcomes, it also introduces new challenges due to the proprietary nature of its algorithms and the dynamic and diverse conditions of international markets. We contribute to the IB literature by presenting a nuanced understanding of how AI and bounded rationality intersect, ultimately proposing that AI-enabled decision-making can reduce the cognitive boundaries managers traditionally face, leading to more effective value-creation strategies within global contexts for MNEs.
Ozili, Peterson K, Digital Innovations for Increasing Financial Inclusion: CBDC, Cryptocurrency, Embedded finance, Artificial Intelligence, WaaS, Fintech, Bigtech, and DeFi (August 28, 2024). Impact of Artificial Intelligence on Society, Forthcoming, Available at SSRN: https://ssrn.com/abstract=4939348 or http://dx.doi.org/10.2139/ssrn.4939348 Central Bank of Nigeria.
Digital innovations are emerging to solve known problems using new digital tools or technologies. Digital innovations also have wide application for financial inclusion. Private sector agents are using digital innovations to increase financial inclusion in remarkable ways. This chapter explores the recent digital innovations that are changing the financial inclusion landscape toward digital financial inclusion. The study used the discourse analysis methodology. It was found that digital innovations, such as central bank digital currency (CBDC), cryptocurrency, embedded finance, artificial intelligence, wallet as a service (WaaS), Fintech, Bigtech, and decentralized finance (DeFi), are helping to accelerate digital financial inclusion in many parts of the world. Each of these digital innovations serve a specific purpose, and they contribute to accelerating digital financial inclusion in unique ways, even though they all pose some risks that can be mitigated with careful and purposeful regulation.
Huang, Yueling, The Labor Market Impact of Artificial Intelligence: Evidence from US Regions. IMF Working Paper No. 2024/199, 10.5089/9798400288555.001 [10.5089/9798400288555.001], Available at SSRN: https://ssrn.com/abstract=4967346 or http://dx.doi.org/10.5089/9798400288944.001 This paper empirically investigates the impact of Artificial Intelligence (AI) on employment. Exploiting variation in AI adoption across US commuting zones using a shift-share approach, I find that during 2010-2021, commuting zones with higher AI adoption have experienced a stronger decline in the employment-to-population ratio. Moreover, this negative employment effect is primarily borne by the manufacturing and lowskill services sectors, middle-skill workers, non-STEM occupations, and individuals at the two ends of the age distribution. The adverse impact is also more pronounced on men than women.
The rise of generative AI: modelling exposure, substitution and inequality effects on the US labour market. BIS Working Papers | No 1207 | 02 September 2024 by Raphael Auer, David Köpfer and Josef Švéd
The data set provides comprehensive information on the AISA indices (AISA, AISA-core, AISA-side) for individual AI capabilities (kappa_AI) on a scale of 1 to 6 at the occupational level. It also includes data on shares of the time spent with i) computer interaction, ii) social interaction, and iii) physical labour, along with shares of skills within given AI capabilitiesAdditionally, the data set is enriched with additional valuable characteristics for each occupation, such as industry and occupational classification, employment numbers, annual mean wage, and overall wage decile. Our paper utilises data from O*NET database version 27.2 and the 2022 Occupational Employment and Wage Statistics (OEWS) Survey from the US Bureau of Labor Statistics.
Purpose-Generative artificial intelligence (GenAI) has progressed in its ability and has seen explosive growth in adoption. However, the consumer’s perspective on its use, particularly in specific scenarios such as financial advice, is unclear. This research develops a model of how to build trust in the advice given by GenAI when answering financial questions. Design/methodology/approach-The model is tested with survey data using structural equation modelling (SEM) and multi-group analysis (MGA). The MGA compares two scenarios, one where the consumer makes a specific question and one where a vague question is made. Findings-This research identifies that building trust for consumers is different when they ask a specific financial question in comparison to a vague one. Humanness has a different effect in the two scenarios. When a financial question is specific, human-like interaction does not strengthen trust, while (1) when a question is vague, humanness builds trust. The four ways to build trust in both scenarios are (2) human oversight and being in the loop, (3) transparency and control, (4) accuracy and usefulness and finally (5) ease of use and support. Originality/value-This research contributes to a better understanding of the consumer’s perspective when using GenAI for financial questions and highlights the importance of understanding GenAI in specific contexts from specific stakeholders.
Intelligent financial system: how AI is transforming finance. BIS Working Papers | No 1194 | 13 June 2024 by Iñaki Aldasoro, Leonardo Gambacorta, Anton Korinek, Vatsala Shreeti and Merlin Stein – Focus – Like the brain of a complex organism, the financial system processes vast amounts of dispersed information to guide the allocation of resources in the economy. The capacity of the financial system to perform this function has been shaped in large part by the computation and information-processing technology available. After examining how progressive generations of artificial intelligence (AI), from rule-based systems to machine learning to generative AI, have transformed the financial sector, we evaluate how to prepare for the coming arrival of AI agents and the possibility of artificial general intelligence (AGI).