Why Did a $20 Billion Prediction Market Become Washington's Regulatory Target?

Author: Andjela Radmilac

Translation: Saoirse, Foresight News

Original Title: $700 Million Iran Bet Pushes US to Tighten Prediction Market Rules

Polymarket and Kalshi are seeking funding at valuations that would make them top-tier consumer fintech companies, while US regulators are rushing to establish new rules for such products. Both companies are reportedly in early-stage funding negotiations, with valuations expected to reach around $20 billion.

This funding boom coincides with a political storm.

Iran-related contracts have transformed prediction markets from niche forecasting tools into controversial focal points involving insider information and war speculation. Reuters investigated trading markets on Polymarket related to the timing of Iran attacks and the potential ousting of Khamenei, finding approximately $529 million invested in attack timing contracts and about $150 million in contracts related to Khamenei; meanwhile, reports indicate six accounts made precise trades, earning a total profit of about $1.2 million.

Now, US lawmakers are drafting relevant legislation, and the Commodity Futures Trading Commission (CFTC) has announced plans to advance new regulatory rules.

Wall Street believes that event probability predictions will become part of the information ecosystem; however, Washington is blocking this, fearing that such systems could, at the worst moments, benefit those who shouldn’t profit.

Why Wall Street Is Optimistic About Prediction Markets

Prediction markets can turn attention into trades, earning fees from transactions, while generating real-time probability data packaged as information products.

It is this data product that has moved prediction markets out of the “gambling” category and into the realm of information tools similar to market data, polls, and financial terminals—because their output formats and quote prices are highly similar.

Mainstream media have begun partnering with these platforms:

• CNBC has signed a multi-year agreement with Kalshi to incorporate its probability data into TV and digital programs starting in 2026.
• Dow Jones has an exclusive partnership with Polymarket, integrating prediction data into platforms like The Wall Street Journal and Barron’s, viewing contract prices as foundational news infrastructure alongside earnings reports, interest rates, and election coverage.

These collaborations have amplified the impact of scandals: once probability data is embedded in mainstream media, it influences public perceptions of event likelihood and urgency. This is why regulators believe platforms must adhere to higher standards of fairness, monitoring, and settlement.

This also explains why, despite political controversy over Iran-related trades, the valuations of these companies continue to rise.

Iran Incident Turns Prediction Markets Into a Washington Dilemma

The greatest advantage of prediction markets is their ability to access information in advance. Iran-related contracts clearly demonstrate that these platforms touch on sensitive information that governments seek to control.

On March 2, bets on attack timing reached $529 million, and contracts related to Khamenei’s death and removal totaled about $150 million. Just hours before the attack on Iran’s senior officials, six accounts suddenly funded positions and profited $1.2 million from these contracts.

As conflicts escalate, numerous reports indicate that many newly registered accounts are precisely betting on Iran-related events. Such reports have brought platforms like Polymarket directly into government regulatory and law enforcement scrutiny.

The core issues now facing these platforms are trust and fairness.

For prediction markets to operate, users must believe that rules are stable, outcomes are consistently judged, and there is no insider bias. When the traded events involve military actions, trust issues escalate into political concerns—because the motivation for early trading could be to leak sensitive or even classified information.

This is why policy responses are rapidly intensifying.

Congressional representatives Mike Levin and Chris Murphy are drafting legislation aimed at regulating prediction markets. The bill will explicitly define which event contracts can be legally traded.

Additionally, CFTC Chair Michael Selig announced that the agency has submitted a pre-rulemaking notice to the White House Office of Management and Budget, signaling upcoming regulatory frameworks for prediction markets that could impact contract design, monitoring, and enforcement.

Washington faces a clear choice:

• Recognize prediction markets as legitimate event contracts, strengthen regulation, set clear restrictions, and allow the industry to grow within rules;
• Or outright ban categories related to war, assassination, and leadership removal, as these trades are highly susceptible to insider trading and malicious motives.

The following data reveals why this conflict is difficult to resolve:

Kalshi’s own disputes also illustrate that regulation alone cannot fully resolve trust issues.

On March 5, Kalshi faced a class-action lawsuit, with users alleging the platform refused to pay approximately $54 million in winnings—bets that Iran’s top leader would be ousted before March 1. The plaintiffs claimed that after the attack on Iran’s leadership, the platform temporarily activated a “death-related exception clause” to deny payout.

Kalshi stated that its rules regarding leadership death-related trades had been clear from the start, and that it had refunded fees and compensated users, with no losses incurred.

This exemplifies the current dilemma faced by investors and policymakers.

Investors want the industry to grow and become mainstream, with probability prediction data integrated into the broader information ecosystem in a rational manner.

Users, on the other hand, want platform rules to be stable and trustworthy, especially when event outcomes are controversial and emotionally charged.

Regulators aim to prevent sensitive national actions from becoming tradable products, avoiding scenarios where “access to confidential intelligence yields the best trading profits.” Once these prices influence public opinion and information environments, the associated risks can evolve into governance challenges.