Corruption Risks Inherent in Prediction Markets

In January 2026, shortly before US forces captured Venezuela’s then-President Nicolás Maduro, a new, anonymous account on the prediction market Polymarket bet on the leader’s removal from power, turning $32,000 into over $400,000 in profit. In March, more than 150 accounts bet on the timing of US strikes on Iran, with six traders together netting over $1.2 million. In April, more newly-created accounts perfectly timed bets that White House would announce a ceasefire. These winning bets were made despite the fact that the Commodity Futures Trading Commission (CFTC), which regulates US-based prediction markets, prohibits bets related to war, among other issues. However, Polymarket listed those bets on its main platform, which, though it bars US-based customers, can be accessed using a VPN.

Either these users are making great guesses, or they are trading on insider information, which is where the corruption risk arises. As Joshua Mitts of Columbia Law School and Moran Ofir of the University of Haifa wrote in their March 2026 draft paper, From Iran to Taylor Swift: Informed Trading in Prediction Markets, “approximately $143 million in aggregate anomalous profit” on Polymarket and its competitor Kalshi can be tied to bets in which “traders appear to have exploited material nonpublic information.”

A more troubling possibility is that traders may be betting on outcomes they themselves can influence. This risk was underscored by Senator Chris Murphy when he and Representative Greg Casar introduced the “Banning Event Trading on Sensitive Operations and Federal Functions (BETS OFF) Act” in March. Similarly, Senators Merkley and Klobuchar introduced the “End Prediction Market Corruption Act,” and Senators Todd Young and Elissa Slotkin introduced the “Public Integrity in Financial Prediction Markets Act,” both proposing to ban elected and public officials from trading event contracts. Meanwhile, the Wall Street Journal reported that the White House issued a memo warning staff against betting on nonpublic information.

The CFTC, which previously fined Polymarket $1.4 million, leading the company to exit the US market before it was permitted to resume limited US operations, appears ready to crack down. In March, Director of Enforcement David I. Miller offered remarks at NYU Law School naming insider trading, including in prediction markets, as the top enforcement priority. He specifically called the idea that insider trading law does not apply to prediction markets a “myth.” He drew a distinction between using one’s “own knowledge and information to make trading decisions,” for example to hedge risk, with those who use “misappropriate” information, specifically citing “the illegal use of government information to trade.” 

It should be noted that these risks of betting on insider political information are playing out not only on online prediction markets. For instance, in April, trades of nearly $1 billion were placed on oil futures, timed with the ceasefire announcement. It has now been reported that the CFTC is looking into those trades, as several Senators have urged.

The Securities and Exchange Commission (SEC) is also looking more closely at prediction markets, under SEC Rule 10b-5 e, which covers insider trading. Further, the US Attorney for the Southern District of New York, Jay Clayton, said that his office is looking more closely at prosecutions tied to insider trading on prediction markets. At the same time, a federal judge blocked Arizona from prosecuting Kalshi, holding that federal jurisdiction preempts state regulation. This Congressional Research Service brief provides a good overview of the range of legal mechanisms that can be deployed by different regulators in such cases. Both Polymarket and Kalshi have introduced new restrictions prohibiting insider trading, aiming to get ahead of a legislative or regulatory crackdown. Meanwhile, firms are being advised to take measures to prevent employees from betting on insider information, similar to bans on insider stock trading. 

It is clear that online prediction markets have moved far from their original roots, for example as an important informational tool to predict election results, a way to correct for gaps in polling capabilities in an increasing digital world. Platforms that allow for a wide array of bets, operate offshore, may settle in cryptocurrency, allow anonymous accounts and utilize blockchain technology have outpaced much regulation and legislators’ technical knowledge. This push to update the governing frameworks is critical, to limit corruption risks from geopolitical events.

Marc Schleifer

Governance, Democracy and Economic Development Expert