Author: Thejaswini M A
Compiled by: Deep Tide TechFlow
Deep Tide Introduction: Six mainstream Wall Street institutions, including Fidelity, Euronext, and Tradeweb, have begun publishing market data directly onto the blockchain through Pyth, allowing any developer to access it for free. This breaks the 44-year monopoly model of data intermediaries like Bloomberg—no more two-year contracts, no more annual fees of $27,000, and no more dedicated keyboards. More importantly, this is a prerequisite for the true scaling of RWA (Real World Assets) in DeFi: data must be on-chain before assets.
In 1981, Michael Bloomberg was fired from Salomon Brothers. He was 39 years old at the time, had worked there for 15 years, and left with a $10 million severance package, deeply dissatisfied with how Wall Street handled information. His reaction to being fired, by any reasonable standard, was insane: he started showing up at Merrill Lynch's office every morning with coffee, wandering the halls, handing coffee to strangers, and explaining that he was going to build them a computer that knew everything. The traders took the coffee but were less certain about the computer.
Forty-four years later, each of these computers costs $27,000 per year. There are 350,000 of them globally, and Bloomberg earns approximately $10 billion annually from this business. Its entire structural genius lies in this: it inserted itself between the institutions that own the data and the people who need it, charging a toll for everything that passes through. The data was never Bloomberg's—Merrill Lynch had the data, Goldman Sachs had the data, every trading firm on Wall Street had the data. Bloomberg just built a tollbooth, convinced everyone that the tollbooth was the destination, and then raised prices every year because what could you do, go back to calling your broker?
This model withstood every technological change over four decades because no one could figure out a better distribution mechanism. Until last Wednesday.
On April 9, six institutions that had been feeding data into the tollbooth began publishing elsewhere: Euronext, Fidelity, Tradeweb, OTC Markets Group, Singapore Exchange's foreign exchange division, and Exchange Data International started publishing directly on-chain through Pyth's new data marketplace, accessible to any developer on 100 blockchains. You don't need a contract, a two-year minimum commitment, or a dedicated keyboard with yellow-green buttons.
Remember this: the funny thing about building a monopoly on other people's data is that those other people eventually notice.
The financial data industry is worth about $30 billion annually, one of the least discussed monopolies in the world, probably because the only people who care about it are the ones already paying for it.
Bloomberg controls about 33% of the global financial data market, with terminal business alone generating over $10 billion in annual revenue. Refinitiv, now acquired by the London Stock Exchange Group for $27 billion, holds about 20%. ICE Data Services reports market data revenue of $2.8 billion. Then there's FactSet, S&P Global, Morningstar, and some regional players serving niche markets. The top four suppliers combined control the vast majority of how financial data flows from generating institutions to demanding companies.
All these companies follow the same model. Institutions like exchanges, trading firms, banks, and asset managers generate pricing data as a byproduct of their work. They sell or license this data to suppliers. The suppliers package, standardize the data, add analytical tools on top, and then sell it to everyone else at a significant markup, with long-term contracts and proprietary access methods that make switching painful. Bloomberg subscriptions lock you in for two years. Canceling early costs 50% of the remaining contract value. And everything about the Bloomberg experience is designed to make leaving feel harder than staying. The keyboard is different. The data format is different. Even the messaging system that half of Wall Street uses to communicate with each other runs on Bloomberg, meaning switching terminals also means abandoning your contact list.
This has lasted forty years because suppliers solved a genuinely difficult problem: getting data from hundreds of sources, cleaning and standardizing it, and delivering it with low latency through global infrastructure. Bloomberg earned its place.
But blockchain is a better distribution mechanism. Maybe not for everything, and not yet at full scale. But for the specific problem of connecting institutions that have data with developers who want to build with it, a programmable, publicly accessible on-chain infrastructure is structurally superior to a proprietary terminal with a two-year contract. By turning data into an API without switching costs, you provide permissionless, self-service access to any developer on any chain. This is what Pyth is doing.
Euronext, Exchange Data International, Fidelity Investments, OTC Markets Group, Singapore Exchange's foreign exchange division, and Tradeweb are starting to publish their proprietary market data directly on-chain through Pyth's new data marketplace.
Euronext FX: Spot currencies and precious metals. Foreign exchange rates used for actual trading in global markets.
Fidelity: ETF valuations and fixed income data. Data used by institutions daily to mark their portfolios to market.
Tradeweb: Intraday ETF pricing. Real-time valuations from one of the largest electronic trading platforms.
OTC Markets Group: Over-the-counter securities. A market almost absent in today's DeFi data.
Singapore Exchange FX: Asian currency pairs. The largest but least on-chain covered foreign exchange market by trading volume.
Together, these six institutions cover a significant portion of asset classes that DeFi has never been able to reliably build because the data feeding these assets wasn't institutional-grade.
Why Data Must Precede Assets
Everyone in crypto has been talking about the tokenization wave for two years now: tokenized treasuries, tokenized bonds, tokenized stocks. The entire discussion assumes the hard part is putting the assets on-chain.
But the hard part is the data. Before you can trade tokenized treasuries in a DeFi protocol, you need to know what they are worth right now, down to the second, with the same accuracy that a Goldman Sachs trading desk uses to price this instrument. Before you can build lending protocols around real-world assets, you need continuously running price feeds from institutions that actually market-make, not scraped from a website and updated every few minutes.
DeFi protocols need accurate, real-time traditional financial data for derivatives, loans, and structured products, but have historically relied on limited or slower data sources. This is why DeFi has been mostly crypto-to-crypto since its inception. The data feeding these products wasn't reliable enough, fast enough, or from institutions with enough credibility in compliance conversations.
Pyth Pro, an institutional subscription tier launched by Pyth in September 2025, offers price feeds with 1-millisecond latency on over 2,200 instruments. Polymarket integrated Pyth Pro in April 2026 to settle new markets for traditional assets including major stock indices, commodities, and U.S. stocks, replacing manual or exchange-specific data sources with standardized data aggregated from over 125 trading firms. Hyperliquid now uses Pyth's price feeds to run perpetual contracts for oil and gold. Data quality is reaching a level where serious financial products can be built on top without apology.
The tokenization wave needs this layer to operate at scale. Without reliable fixed income price feeds, you cannot build reliable fixed income products on-chain.
The Oracle War
The original oracle problem in cryptocurrency was simple: smart contracts live on-chain, prices live off-chain. Something needed to connect the two. Chainlink was the dominant oracle for most of DeFi's history, solving this by running a large network of independent nodes that fetch prices from third-party sources (exchanges, aggregators, data APIs) and submit them on-chain. Many independent sources, many independent nodes, reasonable decentralization, acceptable latency.
Pyth took a different approach from the start, going directly to the institutions that are actually trading. Now over 120 institutions publish data through Pyth, including global exchanges, trading firms, and market makers. Jane Street doesn't secondhand describe the Bitcoin price to Pyth; it becomes a publisher. Data comes from the source, not from someone describing the source.
This is faster, more accurate, and more directly tied to real market activity than aggregated price feeds. In a structural sense, it's also more centralized: a smaller club of publishers who mostly know each other and validate their own data. Pyth has staking and slashing mechanisms designed to create economic incentives around accuracy. But a better way to put it is that Pyth chose speed and data quality over maximizing decentralization. For institutional finance, this might be the right trade-off.
The Cost of Centralization
Pyth was created with significant involvement from Jump Crypto, an organization that played a major role in the events of 2022, which most people in crypto prefer not to revisit. The publisher network is a small club, institutions mostly know each other and validate data amongst themselves. Staking and slashing mechanisms create economic incentives for accuracy, but Pyth is both faster and higher quality than what came before, and also more centralized than the marketing suggests. You are not replacing a monopoly with a commons. You are replacing one centralized system with another that happens to run on a blockchain.
The PYTH token hit an all-time high of $1.20 in March 2024 and is currently trading around $0.046, down about 96% from its peak. The obvious reason: using Pyth's data does not require holding or buying PYTH. The network can grow significantly while the token remains range-bound, a known problem that Pyth's reserve plan is attempting to address, allocating a portion of protocol revenue for open market buybacks of PYTH.
The End of the Tollbooth
Getting data from the generating institution to the desk of the person who needs it requires hardware, proprietary networks, sales relationships, and ongoing support. Bloomberg solved all of this and charged accordingly. Data producers had no alternative distribution mechanism, so they sold their data to middlemen, who kept the profits. Blockchain eliminates that specific friction. Not the analysis, not the workflow, not the keyboard. Just the part where someone had to move data from one place to another and charge for the privilege.
But Bloomberg sells workflow. The terminal, the keyboard, the messaging system, the analysis, the support team. Traders build entire careers around it. Pyth sells none of that. It's the data layer that protocols plug into. The only overlapping part is the underlying data itself, and that part just moved.
This matters because if Fidelity publishes its ETF valuations on-chain, any developer anywhere can read that data without negotiating a license agreement, without paying $32,000 a year, without waiting for a supplier to standardize the format. Data becomes programmable infrastructure rather than a proprietary product. Institutions retain control over what they publish and keep the attribution. The middleman's job—moving data from source to user—becomes unnecessary.
These six institutions are choosing Pyth as a primary distribution channel, which is a different category of commitment than a pilot. Pilots get turned off when the advocate changes jobs. Primary distribution channels become operational dependencies.
Tokenized bonds, tokenized stocks, tokenized everything. Most of these are months or years away from meaningful scale. But the raw material that makes real-world asset products possible in DeFi is now available without contracts, without terminals, without two-year minimum commitments.
Michael Bloomberg spent months handing out free coffee in the halls of Merrill Lynch because the data he needed was locked inside institutions that had no reason to give it to him. He built an entire business on that friction.
The tollbooths won't disappear overnight. Every monopoly in data distribution ends the same way. Not with a fight, not with laws, not with a revolution. Mostly, someone somewhere asks why they are paying for something they already have.
