Prediction markets are undergoing a quiet transformation, evolving into structured, regulated platforms that offer valuable signals about future events—from elections to economic indicators.

In a recent Nasdaq TradeTalks with Jill Malandrino, Tony Sio, Head of Regulatory Strategy & Innovation for Anti-Financial Crime at Nasdaq, joined John Phillips, Co-Founder of PredictIt, and Rob Prior, CEO of ForecastEx, to discuss how these markets are gaining traction—and credibility—across the financial and regulatory landscape.

Prediction markets, where participants trade on the outcomes of events like elections or policy decisions, have existed in some form for well over a century. But while the concept isn’t new, the infrastructure around it is changing.

As Phillips noted, “If you wanted to know who was going to win an election 150 years ago, you would go to the financial markets and look to see what the betting was on the steps of the financial markets.”

Today, platforms like PredictIt and ForecastEx are working to establish these markets within a regulated framework, creating transparent systems where data can be trusted not just by traders, but also by institutions, journalists, and researchers.

One key driver of this evolution is the push toward greater regulatory clarity. As Phillips explained, much of the recent momentum has come from legal efforts to define the boundaries of these markets under the oversight of the Commodity Futures Trading Commission (CFTC).

“The litigation has gone in favor of these markets being allowed to operate and regulated mostly by the CFTC,” he said. “It’s not at all certain what the pathway forward is going to be—except that these markets are here to stay.”

While there’s still uncertainty around the regulatory pathway, recent rulings have generally supported the continued operation of well-structured prediction markets. The focus now is on building infrastructure that can withstand scrutiny, deliver reliable data, and offer real value to participants.

That value, according to Sio, is built on three pillars: contract design, rule enforcement, and surveillance. As with traditional financial exchanges, the integrity of prediction markets depends on how contracts are written, how rules are enforced, and how closely the market is monitored for unusual or manipulative behavior.

“You’ve got to focus upon the contract and the market design,” Sio said. “Have a very clear rulebook, enforce it fairly, and use technology to monitor and detect any bad behavior quickly.”

Prior added that contract design is far more rigorous than many assume. ForecastEx, for example, maintains a dedicated team focused on ensuring contracts meet CFTC standards. “You’d be surprised at how prescriptive the CFTC regulations are,” he said.

“We spend an awful lot of time vetting the source agencies and the reference data necessary for resolution.” Interestingly, these contracts are often simpler than traditional derivatives—fully collateralized, long-only, and structured with clearly defined outcomes.

Another notable shift is the convergence of retail and institutional interest. With sophisticated tools now widely accessible, retail participants are entering the space equipped with resources that would have been exclusive to institutional desks just two decades ago.

“There’s this preponderance of data and tools that today would make any trader from 20 years ago jealous,” Prior said. This democratization of data, combined with a growing appetite for real-time, event-driven insight, is drawing in a broader, more engaged audience.

In fact, prediction market platforms are not just seeing increased trading activity—they’re becoming hubs of discourse and analysis. PredictIt, for instance, has markets with over a million user comments, many from participants deeply engaged in political and policy developments. “These markets are drawing in people who are not necessarily just traders,” said Phillips. “They’re becoming engagement tools, and it’s unparalleled.”

What’s more, the data produced by these markets is being actively studied by academics and used by media outlets. PredictIt has partnerships with over 100 U.S. universities, providing anonymized trading data to researchers exploring the mechanics of forecasting, behavioral finance, and the characteristics of so-called “super forecasters.” “They’re researching why markets are accurate when they are—and, interestingly, when they’re not,” Phillips said.

Technology plays a central role in all of this. As Sio noted, Nasdaq has invested heavily in AI tools that help analysts monitor markets and understand new types of contracts quickly—something especially important in prediction markets, where the underlying subjects can vary widely and shift quickly. “Analysts need to be educated up to speed on a huge variety of events,” he said. “We use AI to help them identify whether something unusual is happening. The diversity of events is just fascinating.”

As these platforms grow, so does the diversity of contracts, making consistent, high-quality oversight increasingly complex. Leveraging AI and data analytics is essential to staying ahead of bad actors and maintaining a level playing field.

All three participants emphasized that establishing a credible, respected prediction market requires sustained effort.

The CFTC has laid out a framework, and the industry has responded by adopting best practices from traditional finance—such as time and price priority, robust surveillance, and clear resolution procedures. Building trust, as Tony Sio explained, “takes a long time… and it’s something you have to protect and reinforce every day.”