Gabriel Perez, a White House teleprompter operator, is under CFTC investigation for using inside knowledge of Trump's speeches to bet on Kalshi's prediction markets. He has been placed on unpaid leave.
When a teleprompter operator knows the president's next words before the president does, that knowledge is supposed to be a professional tool—not a betting edge. But according to federal investigators, one White House employee allegedly turned that inside access into a personal profit center on the prediction market Kalshi.
Gabriel Perez, who has operated President Donald Trump's teleprompter since 2016, is under investigation by the Commodity Futures Trading Commission (CFTC) for potential insider trading. The case marks the first known instance of a White House employee alleged to have used non-public information to trade on prediction markets, according to CNN.
Perez is accused of placing bets on Kalshi's "Mentions" market, where users wager on whether specific words, phrases, or topics will appear during a public speech. The CFTC found that Perez made more than a dozen trades on Trump's speeches, winning more than $100,000, according to ABC News sources. CNN reported the figure as more than $90,000 in profits, which have been frozen.
The key detail: Perez allegedly used his advance knowledge of the president's prepared remarks to place bets before the public heard them. Kalshi's surveillance team flagged the suspicious activity and referred it to the CFTC.
"Our surveillance team promptly flagged and referred these trades to the CFTC, and we are cooperating and assisting regulators," Kalshi's lead lawyer, Bobby DeNault, said in a statement to ABC News.
White House Press Secretary Karoline Leavitt told reporters Thursday that Perez has been placed on unpaid administrative leave. She said she spoke with President Trump about the situation, and he called it a "disgrace" and made the decision to put Perez on leave himself.
Leavitt said she was unaware of any other White House staffers who have made similar trades. "The White House has strict ethics guidelines that we expect all staffers and officials to follow," White House spokesperson Davis Ingle said.
Perez is in settlement talks with the CFTC, according to The Hill. Another teleprompter operator handled Trump's primetime address to the nation on election integrity Thursday night.
This case raises questions about how prediction markets—which have exploded in popularity—handle the risk of insider trading. Unlike traditional stock markets, where material non-public information about a company is the currency of insider trading, prediction markets create a new category of valuable knowledge: advance awareness of what a public figure will say.
Kalshi has said it is introducing new security measures to combat insider trading. The company's swift referral of Perez's trades to the CFTC suggests the platform is aware of the reputational risk. But the case also highlights a gap in existing ethics frameworks: White House staffers are bound by strict rules about trading stocks and bonds, but prediction markets are a newer phenomenon that may not be fully covered by those guidelines.
Perez is cooperating with the CFTC investigation, according to sources. His profits have been frozen, and settlement talks are ongoing. The case could set a precedent for how prediction market regulators handle insider trading by government employees.
For the White House, the incident is an unwelcome distraction. The administration has emphasized that no other staffers are known to have made similar trades, and that Perez's alleged actions were an individual violation of ethics guidelines.
But for the tech and finance communities watching prediction markets grow, this case is a stress test. If a teleprompter operator can turn advance knowledge of a speech into six-figure profits, what other forms of non-public information are being traded on these platforms? And how will regulators respond?
The answers will shape the future of prediction markets—and the ethics rules that govern the people who have access to the most sensitive information in the world.
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