AI in Banking and Finance, March 17, 2024

This semi-monthly column highlights news, government documents, NGO/IGO papers, industry white papers, academic papers 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 [unpaywalled] versions.


Cryptonews, March 15, 2024. How Artificial Intelligence Could Start To Boost Crypto Crime: Chainalysis. Artificial intelligence (AI) could breed a dangerous new category of crypto-based crime in the coming years, according to blockchain intelligence platform Chainalysis. Crypto Criminals Adopting Artificial Intelligence. During a private video webinar viewed by Cryptonews on Thursday, Chainalysis Cybercrimes Research Lead Eric Jardine summarized growing and shrinking trends in illicit blockchain activity in 2023, and predicted what sorts of tactics criminals will adopt next.

Reuters, March 13, 2024. EU lawmakers endorse political deal on artificial intelligence rules. EU lawmakers on Wednesday endorsed a provisional agreement on artificial intelligence(AI) rules, the world’s first legislation to set guardrails on a technology used in banking, internet-connected devices, smart homes and cars. The European Parliament and EU countries had clinched a preliminary deal in December after nearly 40 hours of negotiations on thorny issues such as governments’ use of biometric surveillance and how to regulate foundation models of generative AI such as ChatGPT.

JD Supra, March 14, 2024. EU AI Act – Landmark Law on Artificial Intelligence Approved by the European Parliament. The highly anticipated EU Artificial Intelligence Act is finally here! With extra-territorial reach and wide-reaching ramifications for providers, deployers, and users of Artificial Intelligence (“AI”), the Artificial Intelligence Act (“AI Act”) was finally approved by the European Parliament (“EP”) on March 13, 2024. The text of the approved version is based on the political agreement that the EP reached with the Council of the European Union in December 2023. Members of the EP passed the law with 523 votes in favor, 46 against, and 49 abstentions. The Act aims to safeguard the use of AI systems within the EU as well as prohibiting certain AI outright., February 22, 2024. How fatalistic should we be on AI? [unpaywalled] The godfather of artificial intelligence has issued a stark warning about the technology.

Forbes, February 23,2024. How AI is reshaping banking. Artificial intelligence is transforming the banking industry, with far-reaching implications for traditional banks and neobanks alike. This transition from classic, data-driven AI to advanced, generative AI provides increased efficiency and client engagement never seen before in the banking sector. According to McKinsey’s 2023 banking report, generative AI could enhance productivity in the banking sector by up to 5% and reduce global expenditures by up to $300 billion. But that’s not even half of the picture.

The Economist, March 4, 2024. Does generative artificial intelligence infringe copyright? Several lawsuits, one brought by the New York Times, could soon answer the question. ENERATIVE ARTIFICIAL INTELLIGENCE (AI) will transform the workplace. The International Monetary Fund reckons that AI tools, which includes ones that produce text or images from written prompts, will eventually affect 40% of jobs. Goldman Sachs, a bank, says that the technology could replace 300m jobs worldwide. Sceptics say those estimates exaggerate. But some industries seem to be feeling the effects already. A paper published in August 2023 on SSRN, a repository for research which has yet to undergo formal peer review, suggests that the income of self-employed “creatives”—writers, illustrators and the like—has fallen since November 2022, when ChatGPT, a popular AI tool, was released.

The Economist, January 7, 2024. What happened to the artificial-intelligence investment boom? Perhaps AI is a busted flush. Perhaps the revolution will just take time.

Business Insider, February 28, 2024. In Private Equity Revival In 2024, Those Who Understand AI Will Win. Gone — at least for the medium term — is the era of low interest rates and the days of highly leveraged deals. Funds must now refocus on value creation in their portfolios. These were the findings at a conference for the private equity industry in June 2023 and are likely to remain the PE investment themes of 2024, according to Beringer Capital, a PE firm based in Toronto, Canada. The industry set a record-breaking pace in the post-financial crisis decade, but the surge in demand for goods during the Covid pandemic resulted in supply chain bottlenecks that quickly fanned the flames for inflation. The global central banks’ collective response to rising prices? Higher interest rates. As rates moved higher, access to cheap funding to finance PE deals was more scarce, which caused activity in the mergers and acquisitions market to fall sharply. “The combination of credit tightening and valuation mismatches made 2023 an interesting year that rippled across M&A activity, fundraising, exits, and restructurings,” said MorganFranklin Consulting in its Private Equity Review of 2023.

Financial Times, February 27, 2024 [unpaywalled]. Large Apple shareholders seek AI disclosures. Norway’s wealth fund and LGIM back resolution asking iPhone maker to outline risks associated with artificial intelligence. Two large Apple investors are seeking more information about the company’s artificial intelligence risks as tech companies’ ambitions in the fast-growing sector face mounting investor scrutiny. Norges Bank Investment Management and Legal & General, Apple’s eighth and 10th-largest shareholders respectively, have said they will support a resolution at the iPhone maker’s annual shareholder meeting on Wednesday that asks the company to report about AI in its business operations. The shareholder proposal asks the company to “disclose any ethical guidelines that the company has adopted regarding [its] use of AI technology”. US technology giants have faced a growing number of questions about their AI development as they spend billions of dollars to compete in the emerging sector. In January, the US Federal Trade Commission issued information demands to Alphabet, Amazon and Microsoft for details about their partnerships with generative AI companies. Last year, the US and UK unveiled efforts to scrutinise AI development. Some Big Tech investors have expressed concerns. At Microsoft’s annual meeting in December, 21 per cent of the company’s shareholders supported a resolution demanding more information about risks posed by misinformation generated and disseminated throug


NBER – The Puzzling Persistence of Financial Crises. Charles W. Calomiris & Matthew S. Jaremski. Working Paper 32213. DOI 10.3386/w32213. Issue Date March 2024. The high social costs of financial crises imply that economists, policymakers, businesses, and households have a tremendous incentive to understand, and try to prevent them. And yet, so far we have failed to learn how to avoid them. In this article, we take a novel approach to studying financial crises. We first build ten case studies of financial crises that stretch over two millennia, and then consider their salient points of differences and commonalities. We see this as the beginning of developing a useful taxonomy of crises – an understanding of the most important factors that reappear across the many examples, which also allows (as in any taxonomy) some examples to be more similar to each other than others. From the perspective of our review of the ten crises, we consider the question of why it has proven so difficult to learn from past crises to avoid future ones.

NBER – ChatGPT and Corporate Policies. Manish Jha, Jialin Qian, Michael Weber & Baozhong Yang. Working Paper 32161. DOI 10.3386/w32161. Issue Date February 2024. We create a firm-level ChatGPT investment score, based on conference calls, that measures managers’ anticipated changes in capital expenditures. We validate the score with interpretable textual content and its strong correlation with CFO survey responses. The investment score predicts future capital expenditure for up to nine quarters, controlling for Tobin’s q and other determinants, implying the investment score provides incremental information about firms’ future investment opportunities. The investment score also separately forecasts future total, intangible, and R&D investments. High-investment-score firms experience significant negative future abnormal returns. We demonstrate ChatGPT’s applicability to measure other policies, such as dividends and employment.

NBER – Applying AI to Rebuild Middle Class Jobs. David Autor. Working Paper 32140. DOI 10.3386/w32140. Issue Date February 2024. While the utopian vision of the current Information Age was that computerization would flatten economic hierarchies by democratizing information, the opposite has occurred. Information, it turns out, is merely an input into a more consequential economic function, decision-making, which is the province of elite experts. The unique opportunity that AI offers to the labor market is to extend the relevance, reach, and value of human expertise. Because of AI’s capacity to weave information and rules with acquired experience to support decision-making, it can be applied to enable a larger set of workers possessing complementary knowledge to perform some of the higher-stakes decision-making tasks that are currently arrogated to elite experts, e.g., medical care to doctors, document production to lawyers, software coding to computer engineers, and undergraduate education to professors. My thesis is not a forecast but an argument about what is possible: AI, if used well, can assist with restoring the middle-skill, middle-class heart of the US labor market that has been hollowed out by automation and globalization.

NBER – The Unreasonable Effectiveness of Algorithms. February 2024 – Working Paper 32125. Jens Ludwig, Sendhil Mullainathan & Ashesh Rambachan. We calculate the social return on algorithmic interventions (specifically their Marginal Value of Public Funds) across multiple domains of interest to economists—regulation, criminal justice, medicine, and education. Though these algorithms are different, the results are similar and striking. Each one has an MVPF of infinity: not only does it produce large benefits, it provides a “free lunch.” We do not take these numbers to mean these interventions ought to be necessarily scaled, but rather that much more R&D should be devoted to developing and carefully evaluating algorithmic solutions to policy problems.

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