AI in Finance and Banking, April 30, 2024

This semi-monthly column highlights news, government reports, 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 versions.

American Banker, April 28, 2024. Banks don’t talk about the energy AI guzzles. Here’s why they should. [unpaywalled] Artificial intelligence uses more energy than other forms of computing. Training a single model consumes more electricity than about 130 U.S. homes use in an entire year, according to some researchers’ estimates. “These large language models are so power hungry, and there’s just not enough energy right now,” Amazon CEO Andy Jassy said at the World Economic Forum in Davos, Switzerland, in January. “So we’re going to have the dual challenge as a group to find a lot more energy to satisfy what people want to do and what we can get done for society with generative AI. But we’ve got to do it in a renewable way, in a carbon-neutral or zero way. It can’t be going back to coal.”

MIT Technology Review, April 25, 2024. Chatbot answers are all made up. This new tool helps you figure out which ones to trust. “This new tool helps you figure out which ones to trust. In many high-stakes situations, large language models are not worth the risk. Knowing which outputs to throw out might fix that. Large language models are famous for their ability to make things up—in fact, it’s what they’re best at. But their inability to tell fact from fiction has left many businesses wondering if using them is worth the risk. A new tool created by Cleanlab, an AI startup spun out of a quantum computing lab at MIT, is designed to give high-stakes users a clearer sense of how trustworthy these models really are. Called the Trustworthy Language Model, it gives any output generated by a large language model a score between 0 and 1, according to its reliability. This lets people choose which responses to trust and which to throw out. In other words: a BS-o-meter for chatbots tests. With hopes and fears about the technology running wild, it’s time to agree on what it can and can’t do. Cleanlab hopes that its tool will make large language models more attractive to businesses worried about how much stuff they invent. “I think people know LLMs will change the world, but they’ve just got hung up on the damn hallucinations,” says Cleanlab CEO Curtis Northcutt. Chatbots are quickly becoming the dominant way people look up information on a computer. Search engines are being redesigned around the technology. Office software used by billions of people every day to create everything from school assignments to marketing copy to financial reports now comes with chatbots built in. And yet a study put out in November by Vectara, a startup founded by former Google employees, found that chatbots invent information at least 3% of the time. It might not sound like much, but it’s a potential for error most businesses won’t stomach…In another test, Cleanlab worked with a large bank (Northcutt would not name it but says it is a competitor to Goldman Sachs). Similar to Berkeley Research Group, the bank needed to search for references to insurance claims in around 100,000 documents. Again, the Trustworthy Language Model reduced the number of documents that needed to be hand-checked by more than half…”

Axios, April 22, 2024 – How to make AI “pro worker – “A top economics researcher is making the case that generative AI could be good for workers, as long as there’s a course correction in how businesses plan to use the technology. Why it matters: The economic consequences of AI are a big unknown. But if this outlook is correct, the economy could see the upsides of the rapid economic changes AI might bring while avoiding the pitfalls of uneven labor market outcomes, like those seen during the automation boom of the 1970s. What they’re saying: “The right way to think about generative AI is to view it as a flexible tool that’s usable by human workers,” MIT professor Daron Acemoglu said at an event hosted by the Group of 30 at the International Monetary Fund on Friday.
  • “If we can do that — not just for managers and the top-level workers, but for electricians, plumbers, nurses, educators — I think there is a chance of turning this into a ‘pro-worker’ phenomenon,” Acemoglu told the group of elite current and former global officials.
  • “But, unfortunately, that’s not where we’re heading.”

Quartz, April 21, 2024. AI is becoming a big deal for big banks. What the CEOs of JPMorgan, Goldman Sachs and more are saying. AI could be as “transformational as some of the major technological inventions of the past several hundred years,” Jamie Dimon said.

Reuters, April 17, 2024. Banks told to anticipate risks from using AI, machine learning. Banks must anticipate risks from using artificial intelligence (AI) and machine learning (ML) in their operations as part of their day-to-day governance, a top global banking regulator said on Wednesday. There are unanswered questions on whether the use of AI or ML in banking is a net positive or negative to global financial stability, said Bank of Spain Governor Pablo Hernandez de Cos, who chairs the international Basel Committee on Banking Supervision. “My main message is that the use of AI in banking raises important prudential and financial stability challenges,” de Cos said in a speech in Washington.

American Banker, April 15, 2024. 9 ways AI is transforming the payments industry. From the freshest entry-level employee all the way up to the C-suite, AI is changing the way people in the payments industry approach their jobs. Generative AI is helping people communicate internally and speeding up product development. It’s crunching large amounts of data to improve the supply chain. It’s also helping retailers cut shrinkage and pitch the right products.  But AI also has the potential to eliminate certain roles, depriving companies of a crucial part of their talent pipeline. Here’s how several payment companies and retailers are adopting AI to transform the way they do business.

Li, Yueqi and Goel, Sanjay, Artificial Intelligence Auditability and Auditor Readiness for Auditing Artificial Intelligence Systems (April 8, 2024). Li, Y., and S. Goel. (in press). AI auditability and auditor readiness for auditing AI systems. Accepted at International Journal of Accounting Information Systems: Advanced Technologies and Decision Support for Audit (Special Issue). Available at SSRN:

World Bank – Digital Progress and Trends Report 2023 – “…The diffusion and adoption of digital technologies are just as critical as their invention. Digital uptake has accelerated since the COVID-19 pandemic, with 1.5 billion new internet users added from 2018 to 2022. The share of firms investing in digital solutions around the world has more than doubled from 2020 to 2022…”

Posted in: AI in Banking and Finance, Climate Change, Economy, Energy, Financial System, Legal Research