Woofun AI reports that Gabriel Perez, a long-serving speechwriter for Donald Trump, is under federal investigation for allegedly exploiting non-public information to trade on prediction market platforms. The core allegation centers on Perez using his privileged access to draft presidential remarks to place wagers on whether specific topics or phrases would be mentioned during public addresses. This incident has triggered a suspension from the White House and a formal probe by the Commodity Futures Trading Commission (CFTC), exposing the vulnerabilities of prediction markets to insider manipulation. The platform Kalshi identified the irregular trading patterns, leading to the immediate freezing of Perez’s account and the seizure of his illicit gains. This case underscores the growing tension between informational asymmetry in government roles and the transparency demands of financialized prediction ecosystems.

The timeline of discovery began on July 16, when federal regulators launched an inquiry into Perez’s activities. Simultaneously, the White House announced his suspension from duty, effectively halting his access to sensitive materials. This swift administrative action followed the detection of suspicious trading behavior that spanned several months. The coordination between regulatory bodies and the executive branch highlights the severity with which such breaches are now treated. Perez’s removal from his post was not merely procedural but signaled a zero-tolerance stance toward the monetization of insider knowledge. The immediate consequence for Perez was the loss of his position and the initiation of legal proceedings that could result in significant financial penalties and professional bans.

Perez’s role within the Trump administration provided him with unique access to information that was not available to the general public. Since 2016, he has been responsible for managing the president’s speech devices, a task that places him at the center of communication logistics. On March 27, 2026, in Miami Beach, Florida, Perez was seen preparing Trump’s device ahead of the Future Investment Initiative summit, a routine duty that underscored his proximity to the president’s messaging. He is typically the last assistant to review and adjust speeches, often receiving last-minute changes directly from Trump. This final layer of access meant that Perez knew the exact content of speeches before they were delivered, giving him a decisive advantage in prediction markets. His position allowed him to anticipate deviations from prepared texts, enabling him to adjust his bets in real-time.

The scope of Perez’s illegal trading activities was extensive, covering a period of approximately three months. Investigators from the CFTC found that he traded on more than 12 of Trump’s public speeches, including high-profile events such as State of the Union addresses, speeches at the Davos World Economic Forum, prime-time addresses, and Medal of Honor ceremonies. On Kalshi’s "Mentions" market, Perez placed bets on whether certain words, phrases, or topics would appear in these speeches. He sometimes withdrew his bets mid-speech when Trump skipped parts of his prepared text, demonstrating a real-time reaction to insider information. This behavior was not random but systematic, leveraging his knowledge of the president’s ad-libbing tendencies. The variety of events targeted suggests a deliberate strategy to maximize profits across different contexts and audiences.

Detection of these activities was driven by Kalshi’s advanced monitoring system, which flagged Perez’s trades in March this year. The patterns of buying and selling did not conform to typical market behavior, raising red flags among platform analysts. Market makers further corroborated these suspicions through reporting channels, providing additional evidence of irregular activity. In response, Kalshi froze Perez’s account and seized almost all of his profits, preventing him from withdrawing the funds.

Robert DeNault, Kalshi’s head of enforcement, stated via CNBC that the monitoring team quickly identified these transactions and that the platform is cooperating fully with regulatory authorities. This proactive stance by Kalshi demonstrates the increasing sophistication of compliance mechanisms in prediction markets. The collaboration between private platforms and public regulators is becoming a critical tool in combating insider trading.

Woofun AI data shows that Perez earned over $90,000 in total profits from these trades, but most of this amount was frozen by Kalshi. Currently, Perez is engaged in settlement talks with the CFTC, which may require him to return all his profits and face a ban from engaging in similar trading activities. The Manhattan U.S. Attorney’s Office is aware of the matter but has decided not to launch a criminal investigation, focusing instead on civil enforcement. This decision reflects the complex interplay between regulatory priorities and prosecutorial discretion. The financial impact on Perez is significant, as the loss of his illicit gains and potential legal fees could outweigh any short-term benefits. The case serves as a warning to others who might consider exploiting insider information for personal gain.

The White House reaction to the scandal was swift and unequivocal. Press secretary Karoline Leavitt confirmed at a press conference that Perez has been placed on unpaid administrative leave and is no longer responsible for operating speech devices. She stated that Perez will not continue working in the White House, effectively ending his tenure. Leavitt revealed that Trump himself was aware of the situation and considered it "extremely unfortunate and simply shameful," making the decision personally. This personal involvement by the president underscores the political sensitivity of the issue. An internal memo issued in March this year warned staff members not to use non-public information to trade in prediction markets, indicating that the White House had already recognized the risk. The strict ethical standards enforced by the administration aim to prevent similar incidents in the future.

Perez’s case is not an isolated incident but part of a broader trend of insider trading in prediction markets. As early as May 2025, Kyle Langford, a candidate for governor of California, made trades worth about $200 in markets related to his campaign. Although he made little profit, he was fined $2,246 and banned from the platform for five years. From August to September 2025, Artem Kaptur, a video editor who obtained program schedules in advance, was flagged for unusually high win rates. He earned about $5,400, had his profits recovered, and was fined an additional $15,000 and banned for two years.

In February 2026, former congressman George Santos bet that he would not attend Trump’s State of the Union address while publicly promising to do so, earning tens of thousands of dollars. His account was frozen and referred to authorities. In April of the same year, three congressional candidates were investigated for small bets in election-related markets, resulting in fines of several hundred to several thousand dollars and five-year bans. These cases illustrate that even small profits can lead to severe penalties.

Similar violations have occurred on other major prediction market platforms, such as Polymarket. Gannon Ken Van Dyke, a sergeant in the U.S. Special Forces, used classified information about military operations to capture former Venezuelan President Maduro from December 2025 to January 2026 to buy contracts on Polymarket, earning over $400,000. He was arrested in April this year and faces criminal and civil charges. In May of the same year, Google software engineer Michele Spagnuolo was prosecuted for using internal data on "annual search trends" from October to December 2025 to trade on Polymarket, earning about $1.2 million. These cases highlight the cross-sector nature of insider trading, affecting both government and corporate insiders. The high liquidity in these markets provides ample opportunities for those with insider knowledge, undermining market fairness.

Regulatory crackdowns and future measures are intensifying to address these issues. Kalshi has updated its policies, requiring traders in specific markets to disclose their professional backgrounds and strengthening preventive measures through KYC procedures. In the first quarter of this year alone, the platform conducted over 150 investigations, froze more than 100 potentially suspicious transactions, and referred over 20 cases to law enforcement agencies.

The CFTC has repeatedly invoked rules prohibiting the misuse of non-public information and is working with the Department of Justice to pursue criminal charges. Those who use internal government information or corporate data for trading may face charges such as fraud and money laundering, along with several years in prison. This marks a significant shift in the enforcement landscape, where prediction markets are no longer viewed as harmless gambling but as regulated financial instruments subject to strict oversight.