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.
AI Startup Raises $25 Million After Beating Human Forecasters in Online Competition
Mantic is pitching hedge funds a system that forecasts earnings, economic data and other market-moving events.
A lot of AI financial tools I see focus on improving the research that informs investors’ forecasts.
But what about using AI to improve forecasts directly?
That’s the idea behind Mantic, which last week raised $25 million in a seed round led by Radical Ventures, with backing from Microsoft’s M12, Thinking Machines and trading firm DRW.
The company was co-founded by former DeepMind researcher Toby Shevlane and Ben Day, who previously led research at Foresight Data Machines. Its system finished ahead of all 676 human entrants, including professional forecasters, in the Metaculus Cup, an online competition where participants assigned probabilities to roughly 60 questions about political, economic, technological and cultural events.
Questions ranged from the price of Brent crude and Colombia's presidential election to Spider-Man box-office revenue and whether Shakira's "Dai Dai" would overtake "Waka Waka" on the Billboard Hot 100.
Mantic finished second overall behind a bot called laertes built by an independent developer. It was the first time AI systems had beaten every human in the tournament.
“The models are getting way smarter,” Toby told me in an interview. “Their potential performance ceiling of how good at forecasting they can be is getting higher and higher.”
NOTE FROM OUR SPONSOR
Join the data industry’s biggest conversation.
On 29 October, join 300+ data-forward funds—ranging from emerging and established hedge funds, private markets funds, AI players and corporates—at the San Francisco Data and AI Summit.
Meet data buyers, innovative providers and hear from experts at OpenAI, Perplexity, IBM, Salesforce Ventures and many more! See the full agenda.
Mantic describes its product as a generalist forecasting engine. It starts with frontier language models, then builds what Shevlane called a “layer on top” that supplies them with forecasting-specific research, data and scaffolding. The company puts more of its research effort into those surrounding harnesses than into fine-tuning.
In one published experiment, its researchers used reinforcement learning to fine-tune gpt-oss-120b on roughly 10,000 yes-or-no questions, rewarding the model for putting more probability on the correct real-world outcome.
The highest-volume markets on Kalshi and Polymarket are already highly accurate, Shevlane said, but Mantic can forecast questions that prediction markets don't list.
“As a human forecaster, it’s hard to make so many forecasts per day, but we can massively scale up the number of forecasts that Mantic’s making.”
TL;DR
Mantic raised $25 million to scale an AI forecasting system that beat humans in an online tournament and can tackle questions prediction markets don't cover.
Meta’s Muse Spooks Wealth Stocks
In February, an AI tax tool from Altruist triggered billions of dollars in market-cap losses across wealth-management stocks.
This week, it happened again.
Meta’s new Muse agent contributed to a selloff that pushed Charles Schwab and LPL Financial down more than 6%.
Muse is a personal AI agent that operates through its own browser and connects to other apps. A user can ask it to send emails, book travel, fill out forms, negotiate a bill or make a purchase.
These moves always surprise me because while technology moves fast, regulation just doesn’t. And financial services is among the most regulated industries. I would think that would favor incumbents with scale and the necessary regulatory infrastructure rather than an outsider who would need to jump through all those regulatory hoops.
TL;DR
Muse could quickly change how people access financial services, but the licenses, infrastructure and regulatory permissions will take longer.
AI Is Polluting the Data Hedge Funds Rely On
Here’s a smart story from Business Insider on how AI is corrupting data hedge funds rely on. We know that AI companies trained their models on data from the internet, but that was a web written by humans. That is no longer the case as anyone who’s perused LinkedIn lately can tell you AI writing is everywhere. (I can no longer finish reading a sentence that starts: “It’s not x, it’s Y.” 🤮)
From BI:
AI is affecting data quality in two ways: Providers are using AI to generate or map the data they’re selling, or they’re using AI as a justification to cut or reassign people focused on data quality, said Daniel Entrup, cofounder of AggKnowledge, a data product business that works with sellers and buyers.
…
Entrup has noticed an uptick in basic data hygiene issues in recent months as industry priorities have shifted to finding new use cases for AI. His business does data "revision" work that cleans up errors in datasets clients use, and he said this type of work has increased significantly.
TL;DR
As we’ve previously discussed, bots now generate more traffic on the web than humans. And I don’t see how there won’t be more agents a year from now than there are today. So I suspect the quality of internet data is likely to go down as bots proliferate.
CFTC Starts Forum on AI & Finance
The derivatives regulator is hosting a series of roundtables on how emerging technology is impacting markets.
The first session, which aims to bring together “builders and leaders” in the space, focuses on AI and agentic finance and will take place on Oct. 28. You can send speaker nominations to Innovation@CFTC.gov.
AI Is Becoming a Credit Rating Issue
I often have to remind myself that it hasn’t even been four years since OpenAI released ChatGPT in November 2022. And the technology is already so crucial that S&P will consider a bank’s AI strategy as part of its credit evaluation. From Bloomberg:
Here’s the S&P report.
ROUNDUP
What Else I’m Reading
OpenAI, Anthropic Costs Push More Startups to Build Off Cheaper Open Models | BBG
Fed, BoE probe banks’ exposure to trading firms after Jane Street loss | Reuters
What It’s Like to Work in One of America’s Data Centers | WSJ
OpenAI Discloses Six New Incidents of ‘Concerning’ A.I. Behavior | NYTimes
Old School Voice Brokers Face Automation in $4 Trillion FX Market | BBG
Banks warn AI shopping agents outpace fraud protections | Yahoo
Workday Billionaire Duffield Mints His Third Billion-Dollar Firm Ridgeline | BBG
This Week in AI Street
Jump Trading’s Lucas Baker on AI Agents
The technical divide between quant firms and frontier AI labs has all but vanished, according to Lucas Baker, head of LLM R&D at Jump Trading.
Both work with the same basic ingredients: models, compute, data and infrastructure. Both recruit similar talent from the same pool of computer science, mathematics and physics majors. You’ll often see them sponsoring the same major machine learning conferences, like OpenAI and Jane Street did for ICML 2026.
Lucas has worked in both worlds. Prior to Jump, he spent time at Google DeepMind as a software engineer, helping build the evaluation framework for AlphaGo Zero, the system that learned the game without using data from human games.
SPONSORSHIPS
Reach Wall Street’s AI Decision-Makers
AI Street reaches institutional investors, C-suite executives and Big Law attorneys at firms including JPMorgan, Citadel, BlackRock, Skadden, McKinsey, and more. Sponsorships are reserved for companies in AI, markets, and finance. Email sponsors@ai-street.co for more details.
CALENDAR
*new events added since last newsletter
Upcoming AI + Finance Conferences
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.
*Speed, Trust & AI in Investment Data Workflows — October 1 • Online
Kadoa and Norges Bank Investment Management host a webinar on sourcing and analyzing data with AI.22nd Quantitative Finance Conference — September 30–October 2 • Malta
Practitioner and academic conference with tracks on AI, LLMs and machine learning, alongside volatility, derivatives, risk modeling and systematic trading.AI Agents for Alpha Generation — From Prompt to P&L — October 7 • London
Finteda and Zerve event at Deutsche Bank examining how AI agents move from prompts into production investment workflows and measurable alpha generation.ALGODEFI 26 — October 8–9 • Milan
Politecnico di Milano workshop exploring algorithmic trading, decentralized finance and artificial intelligence in capital markets.World Financial Information Conference — October 11–14 • Copenhagen
Market-data conference examining AI adoption, data licensing and governance, alternative data, cloud trading infrastructure and the changing financial-information industry.AI Engineer New York 2026 — October 12–14 • New York
Three-day conference for engineers and technical leaders building production AI across banking, hedge funds, fintech, insurance and asset management.AI in Finance Summit Fall — October 21–22 • Hoboken, NJ
Financial-services AI summit covering agentic systems, governance, fraud, forecasting, trading, data infrastructure and the challenges of scaling AI into production.Evident AI Symposium — October 22 • New York
Curated gathering of senior banking executives, AI leaders and policymakers focused on turning financial institutions into AI-first organizations.Open Source in Finance Forum New York — November 4–5 • New York
FINOS conference for financial-services technologists featuring keynotes, panels and technical sessions on open-source infrastructure and collaboration.FinTech Founder & Investor Evening — November 4 • Frankfurt
Invitation-only evening hosted by Finteda, Schalast and Fincite, bringing together founders and investors to discuss capital, regulation and scaling fintech companies in Europe.
Manage how often you receive AI Street
If you read this far down
Do me a favor and hit reply with the number of your favorite topic from today:
AI Forecaster Mantic
Meta’s Muse Spooks Wealth Stocks
AI Is Polluting Internet Data
CFTC Starts AI & Finance Series
AI Is Becoming a Credit Rating Issue