Former U.S. Rep. George Santos has been permanently barred from trading on Kalshi after the prediction-market operator concluded that he traded a contract connected to his own attendance at the State of the Union address, according to a settlement notice filed Monday. Kalshi said the case marks its first permanent ban imposed on an individual trader.
The company also ordered Santos to pay a fine of slightly more than $71,000. Its compliance department said it had “reasonable cause” to believe that Santos engaged in trading activity in markets tied to whether he would attend the presidential address, creating a conflict between his market position and his ability to influence the event being traded.
Kalshi’s action follows a separate settlement Santos reached with the Commodity Futures Trading Commission last month. The CFTC alleged that Santos used Kalshi trades to influence the outcome of his State of the Union position by making public statements about whether he would attend the speech.
According to the agency, Santos made those statements roughly two weeks before the address, and the comments moved the price of the relevant contract. Prediction-market contracts rise and fall as traders reassess the probability of an outcome, meaning a participant with both a position and influence over the underlying event can potentially profit from reactions to their own conduct.
Santos agreed to pay $35,000 in the CFTC matter without admitting or denying the regulator’s findings. The Kalshi settlement adds a private-market sanction with no stated end date, removing him from the platform rather than merely imposing a financial penalty.
A different kind of market-abuse case
The Santos matter centers on a problem that is particularly difficult for event-contract platforms: a trader does not necessarily need confidential information to hold an unfair advantage. In some markets, a participant may be directly involved in the outcome.
A contract on whether Santos would attend the State of the Union depended, in part, on a decision he could make himself. Public comments from someone in that position can carry more weight than ordinary political speculation, especially when the market is thin or when participants believe the speaker has firsthand knowledge of the result.
Kalshi’s notice did not describe the full sequence of trades or say how the company calculated the fine. It framed the sanction around violations of its trading rules and the company’s conclusion that Santos had traded markets related to his own attendance.
The case gives the platform a visible example of how its internal discipline can go beyond federal enforcement. The CFTC’s civil settlement required a payment; Kalshi’s decision cuts off Santos’s access to its marketplace permanently.
Santos represented New York in the House of Representatives from January 2023 until the end of that year. He was expelled from Congress after a House Ethics Committee investigation examined misconduct and ethics violations.
Enforcement pressure reaches politically sensitive markets
The action arrives as prediction markets attract greater attention from regulators and lawmakers over whether people with privileged access can profit from events before the public learns material information. Markets tied to elections, government announcements, military events and presidential speeches can draw participants who may have professional proximity to the outcome.
On Friday, the CFTC ordered Gabriel Perez, a former White House teleprompter operator, to pay more than $172,000 to settle allegations that he used advance access to President Trump’s speeches to profit from Kalshi “mention markets.” Those contracts allow traders to take positions on whether a particular word, phrase or topic will appear in a speech.
The CFTC also recently pursued Santos over statements related to his own State of the Union attendance. Together, the two cases place scrutiny on markets whose resolution may be influenced by political staff, government officials, speakers or people close to a scheduled event.
In a separate case, the Justice Department in April arrested an active-duty U.S. Army soldier over allegations that he used confidential information to place prediction-market bets before the capture of former Venezuelan President Nicolás Maduro. The allegation involved non-public information rather than an individual’s ability to influence an outcome, but both situations raise the same core concern: a market can lose credibility when one participant has access unavailable to everyone else.
Several bipartisan bills have been introduced in Congress to restrict prediction-market trading by people who hold non-public information. None of those proposals has become law, leaving platforms and regulators to rely on existing market rules, agency enforcement and individual compliance programs.
Platforms face pressure to screen sensitive participants
Some major prediction-market platforms have begun introducing measures such as employment verification for traders seeking access to sensitive contracts, alongside other controls intended to detect or deter trading based on privileged information. Such systems could make it harder for employees, officials and contractors to trade markets linked to their work, though they also raise practical questions about how broadly a platform can identify relevant job roles.
The Santos ban illustrates another route available to operators: treating certain conflicts as a rule violation even where a trader’s information comes from their own expected actions rather than a leaked document or confidential briefing.
That approach may prove especially relevant for contracts involving public appearances, official announcements and decisions controlled by a small group of identifiable people. A former officeholder deciding whether to attend an event sits unusually close to the outcome; similar questions could arise around corporate executives, campaign staff, government employees and contractors involved in scheduled public announcements.
Prediction markets have expanded rapidly, with combined monthly global trading volume on the two largest exchanges reaching about $24 billion in April 2026, according to Pew Research Center. Growth in trading activity gives enforcement cases more visibility and raises the stakes for platforms seeking to show that prices reflect public information rather than privileged access.
For participants, the Santos case offers a straightforward boundary: trading an event contract becomes far riskier when the trader can materially influence the event itself. Kalshi’s permanent ban indicates that a platform can impose consequences separate from a regulator’s financial settlement, particularly where its internal rules treat self-dealing as incompatible with fair market participation.
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