According to Forbes, prediction markets are exploding, with Robinhood users completing about eight billion contracts in just Q2 and Q3. Kalshi raised a massive $1.3 billion in 2025, hitting an $11 billion valuation, and the Intercontinental Exchange made a multibillion-dollar bet on Polymarket. In December, a strategic collaboration was announced between Crypto.com, Signal Markets, and ERShares to build a Global Predictive Market Intelligence Platform. The goal isn’t just more trading, but to design systems that transform raw probabilistic data into coherent, real-time market interpretation. This shift focuses on providing context for both retail users and institutions, moving the category from pure speculation to structured intelligence.
The Real Challenge Isn’t Volume, It’s Clarity
Here’s the thing: a market where people can bet on anything is cool, but it’s also incredibly noisy. You can see the probability of a Fed rate cut jump 20%, but why did it jump? Was it a new inflation report, a geopolitical event, or just some whale placing a huge, uninformed order? Raw probabilities in isolation are basically just numbers. Without context, they’re as useful as a weather forecast that just says “60% chance” without telling you of what, or where, or when.
That’s the core problem this new alliance is trying to solve. Signal Markets brings the probabilistic forecasting and system design chops, while ERShares adds decades of traditional investment research to ground things in fundamentals. Crypto.com brings the massive, global platform to distribute it all. The bet they’re making is that the future winner in this space won’t be the platform with the most contracts, but the one that can best explain what’s happening inside them.
From Gambling To Live Market Commentary
Think about it this way. What if you could see how the market’s expectation for corporate earnings is shifting in real-time, and cross-reference that instantly with changing probabilities on interest rates and commodity prices? You’d stop looking at prediction markets as a bunch of isolated bets and start seeing them as a live, aggregated commentary on global risk sentiment. It becomes a forward-looking dashboard, powered by real money at stake, not backward-looking economic data.
But for that to work for everyone, the presentation is everything. An institutional asset manager needs rigor, transparency, and deep context. A retail user on their phone needs clarity and intuition. Building one system that serves both masters is seriously hard. It requires understanding finance, user behavior, and data communication—not just blockchain tech or exchange mechanics.
The Trust Imperative
And this all hinges on trust. Institutions won’t rely on a black box. Retail users will just get confused and leave if the numbers seem random. The platforms that win will be the ones that can build an authoritative, explainable voice. They need to be seen not as a casino, but as a source of insight. That’s a huge branding and technological lift.
So, what’s the trajectory? We’re moving past the “build it and they will bet” phase. The land grab for users is still on, but the next battle is for comprehension. The real value—and the defensible moat—will be in the intelligence engine, the software that makes sense of the chaos. It’s less about who trades the most, and more about who helps you understand the market best. That’s a much more interesting—and valuable—evolution.
