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.
I’ve previously written about the early uptake of AI trading agents, the broader shift from trading algorithms to trading agents, and how AI could push more trading into less-liquid securities.
More evidence of this trend came this week: German broker Scalable Capital opened its investment platform to ChatGPT, Claude and other AI assistants. Clients can use an AI agent to analyze their portfolios and prepare trades, which must be approved before execution.
Scalable has more than 1 million clients and more than €60 billion in assets on its platform. Co-CEO Erik Podzuweit called the service a “first step” and told Reuters that mass adoption was more likely once Scalable puts the capability directly inside its own app.
By my count, about a dozen brokerages let customers connect third-party AI assistants directly to their accounts, with permissions ranging from read-only portfolio access to autonomous trading.
Alpaca: Executes paper and live trades
Tradier: Constructs and submits trades
TradeStation: Analyzes accounts and places trades after customer confirmation
eToro: Trades autonomously within a dedicated portfolio
moomoo: Backtests strategies and supports paper and live trading
Public: Executes trades autonomously
IG Australia: Provides read-only account access and cannot trade
Robinhood: Trades autonomously through a dedicated account
Interactive Brokers: Drafts orders for customers to review and submit
Webull: Places and manages trades with an order preview
Scalable Capital: Prepares trades for customer approval
Vanguard Bets $4 Billion on AI for Financial Advice
I think we’ll look back at the pre-AI era sort of like the way we look at the days of card catalogues now. For those of you too young to remember the smell of tens of thousands of aging index cards held in wooden cabinets, this is how you had to look up books before the internet.
This seems incredibly inefficient today—having to go to the library trying to find a book—but this was the best system available at the time.
As I’ve argued, AI cuts the tedium in our jobs by completing low-level administrative tasks. A 2019 Kitces.com survey of more than 1,000 advisers found that a typical lead adviser spent less than 20% of their time meeting existing clients and another 42% on back-office client work and administration.
Altruist tries to automate these processes. In February, the company unveiled an AI tool it said could analyze client tax documents and generate personalized strategies in minutes, helping trigger a selloff in wealth-management shares.
This week, Vanguard agreed to buy the startup for a reported $4 billion. The second-largest asset manager described its takeover of Altruist as an expansion of its financial-advice business through the acquisition of the “AI-forward wealth technology and custody platform.”
This is not solely driven by AI. Vanguard first invested in Altruist in 2020, and the acquisition also gives it a custody platform and closer ties to independent advisers.
TL;DR
AI should help lower the cost of financial advice by automating more manual tasks. Advisers could offset lower fees by serving more clients. I suspect other incumbents will follow Vanguard’s lead, using M&A to quickly boost AI adoption.
What Else I’m Reading
Young British investors trust AI more than TV or celebs | Finextra
DBS moves AI-generated credit memos from a 150-person pilot to 1,500 bankers | DBS
OpenBB Winds Down as a Company, Releases Entire Financial Technology Stack to Open Source | Rebellion Research
Citi, HSBC, StanChart adopt Ant International’s forex AI tool | Reuters
Harvard Is Selling a $699 Course Taught by A.I. Clones of Its Faculty | NYT
Itoflow raises $2.5m for investment research AI agents | Finextra
The GenAI premium: How alternative data is being repriced | Neudata
ADIB appoints first chief AI officer | Finextra
Stanley Druckenmiller’s AI writing has split Wall Street down the middle | BI
PE Is Deploying an Army of AI Wonks to Embed in the Firms They Back | WSJ
Revolut launches dedicated AI research lab built on its own foundation model | Finextra
This startup sold Wall Street on AI. Its existential challenge is doing it again. | BI
New Coinbase General Counsel Charts AI-Engineered Legal Path | Bloomberg Law
WorldQuant Says AI Is Boosting Solo Quant Research
AI makes it cheaper and faster to test ideas. This is a point I’ve heard often from folks building in the space. (I also discussed this in my interview with Tal Fishman at Lord Abbett.)
Here’s more evidence: WorldQuant, the quantitative asset manager founded and run by Igor Tulchinsky, holds an annual competition where students build and test predictive trading signals. This year, more than 150,000 people registered to compete individually in the contest, about double the 2025 figure. Multi-person teams increased much less, from over 4,000 to more than 5,300.
WorldQuant believes AI is helping explain the gap. Competitors used LLMs to brainstorm signals, generate variations on an idea, find overlooked data fields, test hypotheses and automate parts of the research process.
Fudan University finalist Ziming Xu used an AI-agent workflow to organize his research and avoid “brute-force testing,” according to comments provided by a WorldQuant spokesperson.
The 13 finalist teams will compete in Singapore on Oct. 6–7, developing and presenting new alphas to WorldQuant executives. The competition has a $100,000 prize pool.
This Week in AI Street
Earlier this week, I wrote about how funds are trying to transfer institutional knowledge into AI models:
D. E. Shaw, Point72 and Ares Hire to Put Investment Know-How Into AI
Firms are hiring AI specialists to codify how their investors work while retaining control of the data, workflows and feedback loops used to teach the AI. The firms still rely on frontier labs for broader use cases, as many of the partnerships we’ve covered show. But this goes beyond giving engineers access to coding tools.
Alex Gannes, founder of the investment management focused search firm, Banyak Group, described outside models and internal customization as complementary.
“A hedge fund is always positioning itself for an edge,” Gannes said. “Leveraging frontier labs and customizing AI solutions should ultimately support that edge.”
Business Insider published a related story:
Goldman’s engineers have a new challenge: turning AI agents into firm insiders
“The transfer of the institutional knowledge into the AI is the biggest question… How does an experienced GS AI look versus a naive AI?”
Marco Argenti, Goldman’s chief information officer
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