Kalshi says roughly three-quarters of its users have never deposited funds, using the platform to track prices rather than trade them. This is a pattern prediction market platforms are building their products now.
Kalshi’s new Public Companies Hub, launched this week, is the latest sign that data and probabilities can be monetissed as much as trading volumes.
A Hub Built for Users Who Do not Trade
The Public Companies Hub brings together earnings-related markets and company data in one section of Kalshi’s web and mobile apps, and through its API.
It is organised around three elements: KPI markets, which forecast individual corporate metrics; mention markets, which forecast topics likely to come up on earnings calls; and non-market data, including historical performance and links to earnings call livestreams.
“Earnings are the corporate Super Bowl,” said Cat Sullivan, product lead for the hub at Kalshi. Both Kalshi’s users and Wall Street, she added, had shown growing interest in markets built around KPIs and call mentions.
The hub follows Kalshi’s Midterms Hub, launched in July, which combined election markets with polling averages, FEC fundraising data and curated news. Kalshi called that launch one of the strongest in the company’s history.
Institutions See Value in the Data Itself
The interest extends beyond Kalshi’s retail base. A January 2026 survey of 53 US market-structure specialists by Crisil Coalition Greenwich found that nearly three-quarters expected prediction-market data to hold tangible value for institutional investors over the following one to two years, as a supplement to existing market-data feeds.
The respondents were institutional market-structure professionals, not Kalshi’s retail users. Their answers point to a narrower question: whether probability data has standalone value for institutions, regardless of who trades the underlying contracts.
The Data is Already Being Sold
Prediction market data is already being distributed commercially. In 2025, Intercontinental Exchange, owner of the New York Stock Exchange, agreed to invest up to $2 billion in Polymarket at a valuation of around $8 billion. The investment itself is financing, not revenue from data.
ICE also became a distributor of Polymarket’s output, packaging it into standardised probability feeds through ICE Consolidated Feed and ICE Consolidated History. ICE describes these products as intended for investment research, risk modelling and scenario analysis.
Kalshi has built a similar arrangement with Tradeweb. The two companies partnered in February 2026 to integrate Kalshi’s market signals into Tradeweb’s institutional products, APIs and pricing tools, then extended that integration to trading workflows in June.
Tradeweb also took a minority stake in Kalshi. This is a separate transaction from any revenue the data licensing itself generates.
Neither company discloses how much revenue these agreements produce, or what share flows back to the exchanges. That disclosure is what to watch next: it will show how far prediction markets have actually moved from trading venues toward information businesses.
Kalshi says roughly three-quarters of its users have never deposited funds, using the platform to track prices rather than trade them. This is a pattern prediction market platforms are building their products now.
Kalshi’s new Public Companies Hub, launched this week, is the latest sign that data and probabilities can be monetissed as much as trading volumes.
A Hub Built for Users Who Do not Trade
The Public Companies Hub brings together earnings-related markets and company data in one section of Kalshi’s web and mobile apps, and through its API.
It is organised around three elements: KPI markets, which forecast individual corporate metrics; mention markets, which forecast topics likely to come up on earnings calls; and non-market data, including historical performance and links to earnings call livestreams.
“Earnings are the corporate Super Bowl,” said Cat Sullivan, product lead for the hub at Kalshi. Both Kalshi’s users and Wall Street, she added, had shown growing interest in markets built around KPIs and call mentions.
The hub follows Kalshi’s Midterms Hub, launched in July, which combined election markets with polling averages, FEC fundraising data and curated news. Kalshi called that launch one of the strongest in the company’s history.
Institutions See Value in the Data Itself
The interest extends beyond Kalshi’s retail base. A January 2026 survey of 53 US market-structure specialists by Crisil Coalition Greenwich found that nearly three-quarters expected prediction-market data to hold tangible value for institutional investors over the following one to two years, as a supplement to existing market-data feeds.
The respondents were institutional market-structure professionals, not Kalshi’s retail users. Their answers point to a narrower question: whether probability data has standalone value for institutions, regardless of who trades the underlying contracts.
The Data is Already Being Sold
Prediction market data is already being distributed commercially. In 2025, Intercontinental Exchange, owner of the New York Stock Exchange, agreed to invest up to $2 billion in Polymarket at a valuation of around $8 billion. The investment itself is financing, not revenue from data.
ICE also became a distributor of Polymarket’s output, packaging it into standardised probability feeds through ICE Consolidated Feed and ICE Consolidated History. ICE describes these products as intended for investment research, risk modelling and scenario analysis.
Kalshi has built a similar arrangement with Tradeweb. The two companies partnered in February 2026 to integrate Kalshi’s market signals into Tradeweb’s institutional products, APIs and pricing tools, then extended that integration to trading workflows in June.
Tradeweb also took a minority stake in Kalshi. This is a separate transaction from any revenue the data licensing itself generates.
Neither company discloses how much revenue these agreements produce, or what share flows back to the exchanges. That disclosure is what to watch next: it will show how far prediction markets have actually moved from trading venues toward information businesses.