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This is the 102nd edition of The Web3 + AI Daily - your definitive guide to the intersection of blockchain and AI! An interesting trend has caught my eye today: financial giants across both traditional finance and crypto are beginning to recognize the enormous value of their proprietary data. Rather than handing it over to OpenAI and Anthropic in exchange for access to frontier models, they’re increasingly looking to build their own.
Will other businesses finally wake up to the risks of sharing their corporate secrets with these two companies and follow suit?
Thank you for being here! Let’s dive in.
Revolut Sets Out to Become Europe’s OpenAI
At a recent event, Revolut‘s CEO Nik Storonsky revealed the company’s ambitions to grow beyond finance and into a global AI leader:
“Our American dream, I mean, in this case, European dream, would be to build a global tech company similar to Meta, Google or OpenAI, but out of Europe,” Storonsky said.
In pursuit of this goal, Revolut is already training proprietary AI models and building data centers:
Bernard Marr clarified how Revolut’s approach to AI differs from what other fintechs are doing:
Revolut is taking a very different approach to AI in banking. While many financial services companies are using off-the-shelf AI tools or building separate models for fraud, credit risk and customer service, the UK-based digital bank is developing its own foundation model designed specifically for finance. The idea is not simply to apply a language model to financial data, but to teach AI to understand financial behavior itself.
As it turns out, replacing fragmented AI tools and data pipelines with a streamlined, organization-wide AI strategy pays off:
It reports impressive results. PRAGMA has delivered a 64.7 percent improvement in detecting and stopping fraud, a 16 percent increase in credit risk prediction performance, and is 41 percent more effective at recommending relevant products.
From AI Assistance to AI Agency to Full-Fledged AI Leader
Like other fintech giants such as Stripe and Robinhood, Revolut has been flirting with AI for some time. Back in April, the company began rolling out its in-app AI assistant AIR (AI by Revolut) to help users access core banking functions through a single conversational interface. Now, Revolut is looking to take things a step further: it plans to give AI real agency to advise users and shop on their behalf, but also to open its platform to third-party agents:
AI agents will be able to shop for customers using Revolut’s secure card details, he said. Revolut also plans AI advice on spending, stocks and funds. It will open its platform so third-party agents can talk to its own agents through MCP, a standard way to connect AI tools, with every action authenticated by the customer.
However, automating banking chores and letting AI agents manage users’ financial lives is not enough for Revolut. The company isn’t just looking to bring AI into banking; it wants to build the AI infrastructure and intelligence that power it. And to Storonsky, that means going beyond integrating third-party models and becoming a global AI player in its own right.
Coinbase Replaces Anthropic’s Claude with Qwen
Crypto exchange Coinbase has announced that the open weight model (Qwen 3.5-9B) it post-trained and fine-tuned on proprietary fraud data outperformed frontier models.
Coinbase previously relied on Anthropic's Claude, but has shifted to Alibaba Group's open-weight models in a bid to take greater ownership of its enterprise AI capabilities while finding a more affordable, faster, and higher-performing solution.
The crypto giant published a three-part blog series on the importance of controling their own AI stack:
For Coinbase Onramp, owning intelligence means more than owning weights: a benchmark that defines success, a training process that improves decisions, and a serving system we can operate on our terms.
Enterprise AI Quits Frontier Labs, and Web3 Can Help
CEO Brian Armstrong commented that the shift away from frontier models toward smaller, specialized alternatives is only going to accelerate:
I think we’ll see more of this pattern inside companies. The frontier models are amazing generalists. But increasingly you’ll see specialist models out perform on more narrow tasks, either working on teams, or by themselves.
The same opinion was shared by Delphi Ventures‘ Tommy Shaughnessy Jr:
Love seeing this. My thesis for a long time is companies will fine tune smaller specialized models. They will also own their entire AI stack as it’s a core business asset and drives unique outcomes vs using the model everyone else is using.
But while Coinbase can afford to fine-tune a model like Qwen3.5-9B in-house, many smaller organizations don’t have that luxury. This is where Web3 companies come to the rescue:
Venice.ai, NEAR AI, Bittensor / Opentensor Foundation subnets, Flop Labs, and many others offer affordable and private onchain inference, where you don’t have to worry about your corporate data getting leaked.
Pearl Research Labs adds AI workloads to blockchain, and thus makes AI more socially valuable.
FLock.io‘s decentralized training infrastructure makes it possible for businesses to collaboratively train domain-specific models across regions, without exposing their raw data.
Hundreds of other decentralized AI companies I write about daily, which aim to make AI fairer, more equitable, affordable, and private.
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Disclaimer: The content of this newsletter is provided for informational and educational purposes only. Nothing contained herein should be construed as financial advice or as a recommendation to buy, sell, or hold any of the companies or assets mentioned.
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