CFTC enforcement

A White House teleprompter operator traded on advance knowledge of presidential speeches in prediction markets, generating over $107,000 in profits before regulators intervened. The case underscores the tension between prediction markets’ growing mainstream adoption and their vulnerability to insider information abuse.

• Gabriel Perez, a White House teleprompter operator, traded presidential mention contracts between December 2025 and February 2026 using advance text access.
• The CFTC ordered Perez to disgorge $107,539.02 in profits, pay a $65,000 civil penalty, and accept a three-year trading ban.
• Kalshi’s surveillance team flagged and referred the trades to the CFTC, but the exchange’s detection came after profits were already realized.

• $107,539.02 in prediction-market profits that Perez generated through insider trading activity
• $65,000 civil monetary penalty imposed, substantially reduced due to Perez’s cooperation
• 3 years trading ban duration imposed as part of the administrative settlement

Gabriel Perez, employed as a White House teleprompter operator, exploited access to presidential speech texts to trade contracts on prediction market Kalshi that settled based on whether the President would use specific words or phrases during speeches. Between December 2025 and February 2026, Perez converted this material nonpublic information into more than $107,500 in profit, according to a Commodity Futures Trading Commission settlement order released this month. The case marks a high-profile enforcement action against insider trading in prediction markets at a moment when these platforms are expanding into mainstream finance.

Prediction markets have gained increasing legitimacy and visibility in recent years, with platforms like Kalshi operating as regulated derivatives exchanges under CFTC oversight. These markets allow participants to buy and bet on the outcomes of future events, from election results to corporate earnings announcements, with contract prices theoretically reflecting collective probability assessments. The Perez case represents the first major enforcement action against insider trading within this rapidly growing segment of financial markets.

How Advance Speech Access Created an Unfair Trading Edge

Perez’s position as teleprompter operator gave him knowledge of prepared presidential remarks before delivery, fundamentally distorting the risk calculation for traders betting on word or phrase usage. Other market participants were pricing the probability that a phrase would be spoken based on publicly available information and market sentiment. Perez, by contrast, already possessed the text that would determine whether the contract settled in his favor, eliminating the uncertainty that legitimate traders face.

The mechanics of such insider trading in prediction markets differs from traditional securities insider trading, but the underlying principle remains identical. While insider traders in stock markets exploit advance knowledge of corporate events, Perez exploited advance knowledge of a specific public event that had already been authored but not yet delivered. His informational advantage was complete and cost-free.

The CFTC determined that Perez misappropriated this material nonpublic information in breach of a duty of trust and confidence owed to his employer, the White House, establishing a legal foundation for enforcement action.

Kalshi’s Surveillance Flagged Trades, But After Profits Mounted

Kalshi’s compliance and surveillance team flagged and investigated the suspicious trading activity, then referred it to the CFTC. The exchange was credited for its assistance in the regulatory settlement, though the CFTC’s official release does not disclose the detailed timing of Kalshi’s review, investigation, or referral to regulators. This sequence reflects the divided enforcement landscape: exchanges maintain independent surveillance duties, while the CFTC retains authority to investigate and prosecute violations.

The settlement outcome shows both coordination and latency in the enforcement chain. Kalshi detected anomalous activity and escalated it appropriately, yet the detection occurred only after Perez had completed his profitable trading period and realized the full $107,539.02 gain. The CFTC subsequently ordered Perez to disgorge all profits and imposed a $65,000 civil penalty, with the penalty amount reduced substantially in recognition of Perez’s exemplary cooperation with investigators.

Regulatory policy on insider trading penalties typically aims to eliminate the economic benefit of violations while imposing additional sanctions to deter future conduct. The combination of profit disgorgement plus a substantial civil fine is standard CFTC enforcement practice for significant violations. Perez’s decision to cooperate likely spared him from more severe consequences, including potential criminal referral or significantly larger penalties.

Kalshi’s New Controls Target Future Insider Trading But Came Too Late

In June, Kalshi announced new risk-scoring systems for markets flagged as having heightened insider or manipulation risk, employment verification for certain participants, and expanded whistleblower tools. These measures were designed to move surveillance and policing ahead of trades rather than after profits are realized. However, all of these controls were implemented after Perez’s December-to-February trading window, and available sources do not establish whether they would have prevented his activity had they been in place earlier.

The employment verification requirement appears particularly relevant to the Perez case. Had Kalshi required users to disclose employment in sensitive positions with access to material nonpublic information, the exchange might have identified Perez and implemented heightened monitoring on his accounts. Such disclosure requirements are common in traditional securities brokerages but have been slower to develop in prediction markets, which have historically prioritized accessibility and low friction for users.

The broader challenge facing prediction market platforms involves balancing regulatory compliance and fraud prevention against market accessibility. Excessive friction and disclosure requirements could reduce participation and market liquidity, particularly among retail traders. Insufficient safeguards expose the platform to enforcement action and reputational damage, as the Perez case demonstrates.

The Perez settlement confirms that prediction markets attract enforcement attention for insider trading, but leaves unresolved whether current safeguards are sufficiently timely or robust to prevent similar violations. Regulators and exchanges will face continued pressure to demonstrate that surveillance and preventive controls can stop prohibited trades before execution rather than after settlement. As prediction markets continue to mature and expand their market coverage, the accuracy and timeliness of compliance systems will become increasingly critical to maintaining regulatory approval and public trust.

A White House official’s insider trading on prediction markets resulted in a $65,000 fine and three-year ban, with the CFTC crediting “exemplary cooperation” for a substantial penalty discount. The case underscores how Kalshi and regulators are enforcing rules on event contracts, even as the industry faces scrutiny over market integrity.

• Gabriel Perez, a White House teleprompter operator, disgorged $107,539.02 in profits and paid $65,000 in fines for trading on Trump speech text before delivery.
• The CFTC granted Perez a substantial discount on his fine due to exemplary cooperation, paying roughly 60 cents per dollar of profit versus one-to-one penalty ratios in comparable cases.
• Kalshi detected the suspicious account activity and reported it to regulators, triggering the enforcement action that resulted in a three-year trading ban for Perez.

• $107,539.02 Amount of unlawful trading profits that Perez was required to disgorge to the CFTC
• $65,000 Civil monetary penalty assessed against Perez, discounted for cooperation with investigators
• 3 years Length of trading ban imposed on Perez, matching the penalty duration in prior prediction market cases

Gabriel Perez, a teleprompter operator at the White House, engaged in insider trading on Kalshi’s prediction markets by wagering on the content of President Trump’s speeches before the president delivered them publicly. The Commodity Futures Trading Commission issued an enforcement order on Friday requiring Perez to surrender $107,539.02 in profits and pay an additional $65,000 civil penalty. He is barred from trading for three years. Kalshi’s compliance team identified the unusual trading pattern and escalated the matter to federal regulators, initiating the investigation that led to the action.

The case represents one of the first major enforcement actions involving insider trading on prediction markets since these instruments gained broader regulatory approval and public attention. Prediction markets, which allow traders to bet on the outcomes of future events, have grown into a significant segment of the derivatives industry. These markets are designed to aggregate information and forecast probabilities, but they also create opportunities for individuals with nonpublic information to profit illicitly.

Perez’s access to advance knowledge of presidential speech content gave him a clear informational advantage. Speech transcripts can move markets, particularly when they contain policy announcements, economic forecasts, or statements affecting specific industries or asset classes. The ability to trade on this information before the public receives it constitutes classic insider trading, violating securities and commodities law.

CFTC Credits Cooperation In Reducing Penalty Against White House Staffer

The CFTC explicitly cited Perez’s cooperation as justification for reducing his financial penalty to well below historical precedent. In its order, the agency stated that Perez “must disgorge the profits he made from his unlawful trading totaling $107,539.02 and pay a civil monetary penalty of $65,000, representing a substantial discount…because of Perez’s exemplary cooperation with the CFTC.”

Under the order, Perez must disgorge the profits he made from his unlawful trading totaling $107,539.02 and pay a civil monetary penalty of $65,000, representing a substantial discount because of Perez’s exemplary cooperation with the CFTC.

CFTC enforcement order

The discount becomes apparent when compared to a similar case involving former U.S. Representative George Santos, who faced a Kalshi enforcement action in July. Santos paid $17,500 in fines while disgorging $17,569.98 in profits, resulting in a one-to-one penalty-to-profit ratio. Perez’s ratio of 60 cents per dollar earned represents a meaningful reduction. On the Santos benchmark, Perez’s penalty would have approached $107,000 rather than the $65,000 he actually paid.

Cooperation discounts are standard enforcement practice across financial regulators and securities agencies. The theory underlying such discounts is that cooperation accelerates investigations, reduces litigation costs, and produces more complete factual records. Cooperation also signals to other potential violators that turning state’s evidence carries material benefits.

One critical distinction undermines any argument that Perez received preferential treatment: he did not voluntarily self-report.

Perez Did Not Self-Report, Unlike CFTC’s May Guidance On Cooperation Tiers

Kalshi’s compliance system flagged Perez’s account and submitted the file to Washington, rather than Perez approaching regulators first. The White House official engaged with investigators only after the CFTC contacted him directly. This distinction matters because the CFTC issued new guidance in May establishing tiered discounts, with the deepest reductions reserved for individuals who voluntarily self-report violations before detection.

The enforcement order does not specify which cooperation tier Perez occupied under this May policy framework.

The circumstances suggest that Perez received credit for assisting the investigation after being identified, rather than for initiating disclosure. Despite this limitation, his cooperation discount significantly reduced what the CFTC might otherwise have assessed under the one-to-one standard established by the Santos precedent just weeks earlier.

Kalshi’s role in detecting and reporting Perez’s activity highlights the importance of exchange compliance infrastructure. Prediction market platforms operate under heightened scrutiny regarding manipulation and fraud. Real-time monitoring systems can flag unusual trading patterns, account creation anomalies, and suspicious correlations between trades and subsequent market-moving events. This surveillance capability serves as a critical first line of defense against insider trading.

Kalshi Issues Enforcement Warning Following White House Trading Violation

Robert DeNault, head of enforcement at Kalshi, issued a statement accompanying the CFTC order. “It doesn’t matter who you are: violate our rules or federal law and you will face the consequences,” DeNault said, signaling to the broader user base that insider trading on the platform carries serious repercussions regardless of a trader’s standing or position.

The timing of Perez’s enforcement action adds weight to an ongoing debate over prediction market integrity. Eight days prior, CME Group Chief Executive Terry Duffy raised concerns about event contracts at the presidential level, arguing that U.S.-listed contracts could be vulnerable to manipulation. CFTC Chairman Michael Selig countered that the examples Duffy cited involved offshore venues. Friday’s order demonstrates that the risk is not theoretical and that violations can occur on domestically regulated exchanges subject to CFTC oversight.

Kalshi continues to list contracts on future Trump speeches and other presidential remarks, with the platform operating under heightened regulatory scrutiny.

The Perez case also raises questions about information access policies within government. Federal employees and contractors occupy positions that provide access to nonpublic information routinely. Ethics regulations and insider trading laws apply equally to government workers, but enforcement requires vigilant monitoring and reporting mechanisms. The White House and other agencies may need to strengthen procedures restricting trading by personnel with access to market-sensitive information.

The substantive question raised by Perez’s case is not whether Kalshi or the CFTC can detect and punish insider trading, but rather what incentives the enforcement framework creates going forward. The $65,000 penalty represents a 60-cent-per-dollar reduction versus historical precedent, even absent voluntary self-reporting. As more traders become aware of cooperation discounts and the relatively light penalty relative to profits, the CFTC may face pressure to calibrate whether its tiered approach adequately deters future violations or inadvertently encourages traders to calculate the cost-benefit of detection.