InvestIndependently confirmed2 publishers3 min readPublished Updated
Scalable Capital puts ChatGPT, Claude and Grok inside the European order ticket
A Munich broker has connected mainstream AI assistants to a regulated execution rail. The one independent test cited alongside it says the models pick well and size badly.
The Investor · Invest desk

What happened
- Scalable Capital's new Agentic Investing service connects customer accounts to supported AI agents through the Model Context Protocol.
- Through ChatGPT, Claude or Grok, European customers can analyse portfolios, set up savings plans and place trades by prompt.
- The Munich bank told Reuters it is the first in Europe to open its platform to major AI assistants.
- An Elm Wealth study in June found Claude beat human players in 76% of about 200 market-prediction sessions, ChatGPT 63%, Grok 51% and Gemini 43%.
- The same researchers found the models chose what to buy reasonably well but sized positions badly, taking too much risk for the context.
Why it matters
- capability Advice has been available from these models for two years; what is new in Europe is a supervised execution rail behind the chat window, reachable without opening the broker's own app.
- contradiction Scalable's three connected assistants sit 25 points apart on the only cited measure of skill, so the quality of the counsel now depends on which vendor the customer happened to subscribe to.
- exposure With the four model makers silent on trading use, the confirmation tap is the point where responsibility for a badly sized order attaches, and it attaches to the retail customer.
- precedent Because MCP is a generic connector rather than a bespoke build, rival European brokers can expose the same surface cheaply, and the live question becomes which ones decline and why.
Alexander Siepp's own description of the design is the part to read closely: the client journey starts inside an AI assistant and finishes inside Scalable's regulated banking infrastructure [3]. That splits a trade across two custodians of responsibility. The analysis, the screening and the wording of the instruction happen in a chat product the bank does not run. The order lands on a rail that European supervision actually reaches. The seam between them is one tap.
Scalable's guardrails are real as far as they go: the customer approves each trade and savings plan, assistants cannot make payments or pull money out, and the connection uses the same authentication as the existing apps [5]. But approval is a weak instrument when the thing being approved is already written. Siepp's example has the assistant find stocks that have fallen for consecutive months, watch them, then prepare the order from the user's instructions [8]. What the human contributes at that point is the absence of an objection, not an independent calculation of size.
Size is exactly where the Elm Wealth work says the models fail. Bell, Haghani and White found the systems relatively good at deciding what to invest in and poor at deciding how much, comfortable with the Kelly criterion and the Merton share as concepts and unable to apply them under simulated pressure [11]. Their measured average position sizing was 7x to 12x, against a US market that has moved more than 9 percent on seven days since 2000 [12]. Run that arithmetic: a 9 percent adverse move at 7x exposure costs 63 percent of capital, and at 12x it costs 108 percent [15]. The strong headline number and the dangerous one come from the same study.
Scale matters for who absorbs that. More than 60 billion euros of client assets spread across more than a million customers, mostly in Germany and Austria [6], implies an average account of roughly 60,000 euros [14]. These are not desks with independent risk limits reviewing the ticket. Siepp concedes the rollout will not reach all client segments at the same speed [9].
Two things Fortune's account leaves open. Scalable said in July it would offer more than 1.8 million derivatives from seven issuers [7], and the piece does not establish whether those instruments are reachable through the assistant connection, which is the difference between a prompt that buys an index fund and one that buys leverage. And OpenAI, Anthropic, Google and xAI did not respond to questions about their assistants being used to trade [13], which leaves the bank as the only party on the record for the workflow. Siepp calls the result a level playing field, with information, compute and intelligence available in your pocket around the clock [4]. What is being distributed at that scale is a capability the only cited test rates strong on selection and unreliable on the sizing decision that determines whether an account survives a bad week.
What to watch
- Whether the assistant connection reaches Scalable's derivatives catalogue, or stays limited to cash instruments and savings plans.
- Whether BaFin or ESMA takes a position on suitability and record-keeping when the order is drafted by a third-party model.
- Whether OpenAI, Anthropic, Google or xAI set terms on brokerage execution through their assistants, having so far not commented.
Clarity's read
What the record supports and how the coverage leans. The claims behind it follow.
Reality
- Evidence58
- Adoption22
- Hype gap+34
- Incentives74
- Confidence64
Claim ledger
Ranked by verification strength, evidence, and original report placement.
- [1]
Scalable Capital is opening its investment platform to AI assistants including ChatGPT, Claude and Grok, giving European investors the ability to analyze portfolios, set up savings plans and place trades through prompts.
- [2]
The new service is called Agentic Investing and allows customers to connect their Scalable accounts to supported AI agents through the Model Context Protocol (MCP).
- [3]
Scalable Capital Chief Product Officer Alexander Siepp told Fortune the company sees the integration as a way for investors to begin their financial client journey inside an AI assistant and complete it through Scalable's regulated banking infrastructure.
ReportedSupportedSource: Alexander Siepp, Scalable Capital, to Fortune2 sources— create a free account to open themView cited source - [4]
Siepp said the integration "certainly creates a level-playing field" and that access to information, compute and intelligence is now available literally in your pocket, 24/7.
ReportedSupportedSource: Alexander Siepp, Scalable Capital2 sources— create a free account to open themView cited source - [5]
Scalable said users must approve trades and savings plans before they are executed, its current system does not allow AI assistants to make payments or withdraw money from Scalable accounts, and the AI connection follows the same core security protocols as existing applications, including strong customer authentication.
- [6]
Scalable Capital, founded in 2014, told Reuters it has more than 60 billion euros in client assets and more than 1 million customers, primarily in Germany and Austria, with operations also expanding across Italy, Spain, France and the Netherlands.
- [7]
Scalable said in July that it would offer more than 1.8 million derivatives from seven major issuers.
- [8]
Siepp said a customer could ask an AI assistant to identify stocks that have fallen for consecutive months and monitor them, and the assistant could then prepare an order based on the user's instructions: "It's just a few prompts."
ReportedSupportedSource: Alexander Siepp, Scalable Capital2 sources— create a free account to open themView cited source - [9]
Siepp said it may take time for the service to become fully integrated with Scalable's client base: "Maybe not for all client segments at the same speed."
ReportedSupportedSource: Alexander Siepp, Scalable Capital2 sources— create a free account to open themView cited source - [10]
A June Elm Wealth report by Jerry Bell, Victor Haghani and James White tested Claude, ChatGPT, Gemini and Grok in a Crystal Ball Challenge using historical Wall Street Journal front pages with market outcomes withheld; across roughly 200 sessions Claude beat human players in 76% of sessions, ChatGPT in 63%, Grok in 51% and Gemini in 43%.
- [11]
Elm found the AI systems generally took too much risk relative to the trade context, performing relatively well on what to invest in and poorly on how much to invest, and found the models understood the Kelly criterion and Merton share in theory but struggled to apply appropriate risk management in actual simulated trading decisions.
- [12]
The Elm study noted the US stock market has moved by over 5% on 23 days and by over 9% on seven days since the year 2000, and that given average position sizing in stocks of 7x to 12x across the AIs the researchers judged the models were taking too much risk of a catastrophic loss of capital given their hit ratios.
- [13]
OpenAI, Anthropic, Google and xAI did not immediately respond to a request for comment from Fortune about using AI assistants for financial trading.
- [14]
More than 60 billion euros of client assets across more than 1 million customers implies an average account of roughly 60,000 euros; both reported figures are floors, so the average is approximate.
- [15]
At the 7x to 12x average position sizing Elm measured, a 9% adverse market move implies a loss of 63% to 108% of capital.
- [16]
Across the three assistants Scalable named, the Elm win rates against human players spread 25 percentage points, from Grok at 51% to Claude at 76%.
- [17]
The Munich-based bank told Reuters it is the first bank in Europe to open its platform to major AI assistants.
ReportedInsufficientSource: Scalable Capital, via Reuters2 sources— create a free account to open themView cited source
Sources
2 independent publishers whose own reporting we read for this story.
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