This semi-monthly column by Sabrina I. Pacifici highlights news, government and regulatory documents, NGO//IGO and industry white papers as well as academic papers 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. Each entry includes the publication name, date published, article title and abstract. I blog the link to each column publication date on beSpacific, post it on my Mastodon handle, as well as publishing here on LLRX.

NEWS:

CNBC, August 15, 2023 – Hedge funds beefed up A.I. bets in the second quarter

FT.com, August 15, 2023. SoftBank/AI: strong Arm narrative exploits market’s machine longing

City Life, August 15, 2023. The Impact of AI on Job Losses and the Need for Strategic Planning. Recent headlines highlighting the threat of artificial intelligence (AI) and its potential impact on job losses have caused alarm. Reports indicate that AI has already caused disruptions and job losses at major companies like IBM and Chegg. Additionally, Goldman Sachs predicts that 300 million jobs will be lost or degraded due to AI. AI’s impact is already evident, with a report stating that nearly 4,000 jobs were eliminated in May alone. Before the pandemic, the loss of high-paying manufacturing jobs to overseas markets was a concern. The COVID-19 pandemic highlighted the vulnerabilities in our global supply chains, which were highly dependent on countries that may not share our values of democracy and human rights. This realization prompted a shift towards a more self-sufficient and secure nation.

Open Access Government, August 15, 2023. AI in the financial industry: Machine learning in banking. Digital work of Digital image transfer or nft conceptual backgrounds. Useful for technology concepts or nft concept.

Financial World, August 15, 2023. Machine Learning Boosts Profits: Banking Giant’s Deep Dive

FT.com, August 15, 2023. [read free] David Autor: ‘We have a real design choice about how we deploy AI’. The MIT economist warns that artificial intelligence will not only affect the number of available jobs, but their quality too.

FT.com, August 13, 2023 [read free]. Multinationals turn to generative AI to manage supply chains. Geopolitical tensions and new laws requiring companies to monitor environmental and human rights abuses in their supply networks drive interest.

FT.com, August 10, 2023 [read free]. US investors face uncertain future in China after tech ban. Private equity and venture capital funds targeted in Biden administration’s crackdown

American Banker, BankThink, August 10, 2023 [read free]. Banks embracing the AI future need to pay attention to its risks. The ongoing rise of artificial intelligence (AI) has profoundly impacted the banking and fintech sectors, offering the potential for increased efficiency, improved customer service and enhanced risk management. However, as we ride this wave of technological transformation, important questions arise concerning security vulnerabilities, code ownership and application copyrights associated with AI-generated code.

The New York Times, August 7, 2023 [read free]. The S.E.C.’s Chief Is Worried About A.I. Gary Gensler, who has studied the consequences of artificial intelligence for years, said that the technology could lead to future financial crises. A financial regulator issues a warning on A.I. Gary Gensler, the chairman of the S.E.C., has been studying the potential consequences of artificial intelligence for years. The recent proliferation of generative A.I. tools like ChatGPT has demonstrated that the technology is set to transform business and society. Mr. Gensler outlined some of his biggest concerns in an interview with DealBook’s Ephrat Livni.

FT.com, July 20, 2023 [read free]. AI in banking, payments and insurance. Algorithms are already being used to check payment balances, detect suspicious transactions, and optimise insurance pricing

FT.com, July 20, 2023. Artificial intelligence in business: an explainer. Training machines to carry out human tasks will bring more efficiencies, job losses and risks. Here, FT journalists explain the potential of generative and G-d-like AI and the likely impact on industry sectors, in Q&As and graphics Supported by Infosys.

CONTINUING EDUCATION:

Practical AI for Teachers and Students. Wharton School – 5 Part Course on YouTube for Students and Instructors/Teachers – Description of the Introduction: “In this introduction, Wharton Interactive’s Faculty Director Ethan Mollick and Director of Pedagogy Lilach Mollick provide an overview of how large language models (LLMs) work and explain how this latest generation of models has impacted how we work…

PAPERS:

Boussioux, Leonard and N. Lane, Jacqueline and Zhang, Miaomiao and Jacimovic, Vladimir and Lakhani, Karim R., The Crowdless Future? How Generative AI Is Shaping the Future of Human Crowdsourcing (August 7, 2023). Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005, Available at SSRN: https://ssrn.com/abstract=4533642 or http://dx.doi.org/10.2139/ssrn.4533642

Gensler, Gary and Bailey, Lily, Deep Learning and Financial Stability (November 1, 2020). Available at SSRN: https://ssrn.com/abstract=3723132 or http://dx.doi.org/10.2139/ssrn.3723132. The financial sector is entering a new era of rapidly advancing data analytics as deep learning models are adopted into its technology stack. A subset of Artificial Intelligence, deep learning represents a fundamental discontinuity from prior analytical techniques, providing previously unseen predictive powers enabling significant opportunities for efficiency, financial inclusion, and risk mitigation. Broad adoption of deep learning, though, may over time increase uniformity, interconnectedness, and regulatory gaps. This paper maps deep learning’s key characteristics across five possible transmission pathways exploring how, as it moves to a mature stage of broad adoption, it may lead to financial system fragility and economy-wide risks. Existing financial sector regulatory regimes – built in an earlier era of data analytics technology – are likely to fall short in addressing the systemic risks posed by broad adoption of deep learning in finance. The authors close by considering policy tools that might mitigate these systemic risks.

GOVERNMENT DOCUMENTS:

White House, July 21, 2023. FACT SHEET: Biden-⁠Harris Administration Secures Voluntary Commitments from Leading Artificial Intelligence Companies to Manage the Risks Posed by AI