Hey, I’m Matt. I’m a former Bloomberg News reporter, and you’re reading AI Street, where I report on how Wall Street uses AI. Every Thursday, I cover the week’s biggest AI-in-finance stories, plus original reporting and analysis.
Back in New York
I’m back in New York for a few days next week to attend Cornell’s Future of Finance & AI conference on Sept 11. It has a great agenda exploring many of the topics we’ve been covering at the vanguard of tech and markets. If you’re attending, let me know. It’d be great to meet in person!
Banks Ask Big Law to Share the AI Savings
I spent many years talking to litigators at big law firms when I covered white-collar crime for Bloomberg News. That’s where I came up close to the billable hour, which is straightforward enough, but strange when you see it in person. I saw many high-powered attorneys rushing back to the office because they were on the “clock.”
The FT reported this week that this is coming under pressure. Banks are asking law firms to cut their fees since AI is making routine work easier to complete. Top lawyers have long been paid on the backs of associates billing long hours, Morgan Stanley general counsel Eric Grossman told the newspaper. “Their compensation model is now extraordinarily unstable.”
Banks are still willing to pay top dollar for judgment, but not for rote work.
“We’re not yet seeing a formalised, firm-wide shift towards alternative fee arrangements, but it is likely to come,” said Gretta Rusanow, head of advisory services for Citi’s law firm group. She expects fixed fees for routine work, with the billable hour preserved for more complex matters.
I suspect the banks’ clients will eventually make the same argument.
If AI is making it easier to put deals together, why should the companies that hired the banks pay the same rates? With less deal friction, we’re likely to see more transactions done faster at lower fees.
Something similar happened when stock trading moved online in the 1990s. Technology made execution faster and dramatically cheaper, while the premium shifted from processing trades to providing advice and handling more complex transactions.
TL;DR
Banks want law firms to pass along their AI savings. Their own clients may soon demand the same.
The Financial Models Built Like LLMs
What I find most interesting about AI is the surprising versatility of transformers, the architecture behind large language models.
Researchers and companies have trained transformer models on weather, grocery purchases, driving behavior, Netflix viewing data and bank transactions. In several cases, the models beat established benchmarks or existing production systems.
This is a topic we’ve covered quite a few times:
In a longer article in Chicago Booth Review that includes some of my previous coverage, I looked at what these models can do, where they still fall short and whether scaling them will be enough to compete with traditional quantitative methods.
It’s free to read:
The Risks AI Agents Pose to Central Banks
I was surprised, as I think most people are, to learn that no one knows exactly how LLMs work. Anthropic CEO Dario Amodei is fond of saying that AI is grown rather than built.
This uncertainty poses new regulatory questions as AI adoption picks up.
Markus Brunnermeier, an economist at Princeton University, thinks the technology could have widespread unintended consequences. In a paper presented to central bankers at Jackson Hole, he lays out a scenario in which AI makes markets less informative and more erratic, while giving market participants new ways to game central banks and regulators
AI agents, for instance, could learn from central-bank speeches, meeting minutes and past decisions until they become very good at predicting when policymakers will act. Brunnermeier argues that central banks might respond by communicating less clearly, relying on blunter rules or intervening more directly in markets.
TL;DR
If AI agents spread through financial markets, policymakers may struggle to understand them even as the agents learn to predict policymakers’ actions, according to a Princeton University economist.
ROUNDUP
What Else I’m Reading
AI-driven cyber risk is top concern for global financial stability, watchdog says | Reuters
JPMorgan curbed lending to Jane Street as trading firm muscled into bond market | FT
NYSE Used Anthropic’s Project Glasswing to Find Cyber Flaws | Bloomberg
A Glimpse Into Agentic Treasury Future | Treasury Today
Anthropic Says New Fable 5.1 AI Model Is Cheaper, Better at Coding | Bloomberg
Deutsche Bank Helps Shape Google Cloud’s New AI Solution for Financial Services | Deutsche Bank
Building AI Systems for Capital Markets | Goldman Sachs
Citadel Securities Notches Record $7.3 Billion Trading Haul | Bloomberg
AI Futures: Terry Duffy, CME | Crain’s Chicago Business
Terminal X Brings AI Operating System to Alternative Asset Managers with OpenAI | Terminal X
XTX Markets’ top quants paid more than FTSE 100 CEOs | Financial News
Agentic retail options trading triggers $1bn PFOF feeding frenzy | Global Trading
Nvidia Agrees to Buy Hugging Face for $13 Billion | WSJ
This Week in AI Street
RESEARCH
Inside 142,000 H-1B Filings From Wall Street Firms
I downloaded 26 quarters of Labor Department data covering nearly 142,000 H-1B filings from 91 finance firms, then used OpenAI’s Codex to standardize employer names, identify duplicate case records and turn the cleaned-up data into an interactive dashboard. I used it to track how filings changed across firms, identify which companies were seeking workers for explicitly AI-related roles and compare the wages offered for those jobs with other positions.
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CALENDAR
Upcoming AI + Finance Conferences
8th Annual Artificial Intelligence in Financial Services Conference – September 8–9 • London
Senior financial-services event focused on real-world AI adoption across banking, insurance and fintech, including generative AI, risk management, fraud, compliance and governance.
Cornell Financial Engineering Manhattan 2026 Future of Finance & AI – September 11 • New York
Hedge funds, banks and quants come together to explore how AI is changing finance, share practical lessons and exchange ideas on financial engineering.
Machine Learning in Quantitative Finance – September 14–16 • New York
Quant-focused conference on how financial institutions are applying machine learning across trading, portfolio construction, risk and investment workflows.
AI for Finance Summit London – September 16 • London
Invite-only summit on agentic AI in institutional finance, focused on how multi-agent systems are reshaping research workflows, PM coverage and alpha generation across hedge funds, asset managers and global banks.
AI and Machine Learning in Quant Finance Conference – September 16 • Online
CQF Institute event focused on AI and machine-learning advances in quantitative finance, with discussions geared toward practitioners and researchers.
AI-Native Banking & Fintech Conference – September 29 • Salt Lake City
Banking and fintech conference centered on agentic AI, with speakers from banks, fintechs and regulators discussing production use cases, risk, compliance and operations.
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