A White House teleprompter operator has been suspended without pay after regulators said he used advance access to presidential speeches to make more than $100,000 on prediction-market wagers tied to words and phrases expected to appear in public remarks.
The U.S. Commodity Futures Trading Commission confirmed the matter after receiving a referral from Kalshi, a regulated prediction-market platform that said it detected unusual betting patterns connected to keywords in several speeches delivered by Donald Trump. The platform froze about $90,000 in the account before notifying federal authorities, according to accounts of the case.
Gabriel Perez, who has worked as Trump’s teleprompter operator since 2016, was accused of placing wagers on whether specific phrases would be spoken during major public appearances, including a prime-time address in December 2025, the World Economic Forum in Davos in January, the State of the Union in February and a Medal of Honor ceremony in March.
Investigators found that Perez had access to final or near-final versions of prepared remarks before they were delivered publicly. That access allegedly gave him an edge in “mention” markets, where traders bet on whether a speaker will say a particular word or phrase during a public event.
The White House later confirmed that Trump personally approved Perez’s suspension after being briefed on the findings. Perez, who earned $175,000 a year as a presidential assistant and technical adviser, also agreed to repay profits and stop participating in related prediction markets as part of an administrative resolution.
Prosecutors declined to bring criminal charges after consultation with the CFTC, determining that the conduct did not involve classified information, did not amount to a national security breach and did not justify imprisonment. The case, however, has become one of the clearest examples yet of how federal watchdogs are treating event-based digital markets as a venue where misuse of non-public information can trigger enforcement action.
How the alleged scheme worked
The trades were tied to a fast-growing corner of prediction markets in which participants buy contracts based on whether a public figure, executive or performer will mention a certain word during a scheduled event.
In ordinary trading, the outcome is uncertain. A trader may study past speeches, policy priorities, media themes or public statements and try to estimate what a speaker is likely to say. In Perez’s case, regulators said the advantage came from something far more direct: access to written speech drafts before they appeared on television, on official transcripts or before live audiences.
That access was especially valuable because some contracts were narrowly framed. Instead of betting on broad political outcomes, traders were wagering on the presence or absence of specific terms. If a prepared speech contained a listed phrase, a person who had seen the draft could buy the corresponding contract with far greater confidence than the general public.
Investigators also said Perez appeared to manage risk when Trump departed from prepared text. Public speakers often improvise, skip lines, repeat phrases or add comments not present on a teleprompter. According to the findings, Perez sometimes hedged positions or absorbed losses when Trump moved away from the wording in the written remarks. That pattern helped delay detection because not every wager produced a perfect result.
The alleged activity continued for roughly three months and generated more than $100,000 in gains before Kalshi’s compliance systems flagged the account.
Platform referral triggered the review
Kalshi’s report to the CFTC was the turning point in the case. The platform told regulators it had identified bets that appeared inconsistent with normal trading behavior and were closely connected to language later used in presidential remarks.
After reviewing the activity, Kalshi froze approximately $90,000 in Perez’s account. The referral then moved to federal regulators, who examined whether the trades were based on privileged access to non-public government information.
The CFTC’s involvement reflects the agency’s growing role in overseeing event contracts. While prediction markets differ from stocks, bonds and commodities, the core regulatory concern is familiar: people with privileged access to material information should not be allowed to use that access for unfair financial gain.
In this case, the material information was not a crop report, corporate merger plan or interest-rate decision. It was the text of a public speech before the public had heard it. But regulators treated the basic problem the same way: one person allegedly had access to restricted information and used it to trade against others who did not.
White House response
The White House said it acted after being briefed on the findings. Perez was suspended without pay, and the matter was handled through an administrative process rather than a criminal prosecution.
The case also followed an internal reminder sent to White House staff in March warning that wagering based on non-public information violated ethical standards. That notice came as prediction markets were gaining mainstream attention and as more public officials, staff members and contractors became aware that seemingly routine information could carry financial value in digital event markets.
Government employees and political staff members often encounter non-public information before it is released. That information may include speech drafts, travel plans, staffing decisions, policy announcements, scheduling changes, embargoed reports or internal talking points. In conventional ethics policies, such material is normally treated as sensitive even when it is not classified.
The Perez case shows how quickly that type of access can become financially relevant when prediction-market contracts are built around public events.
Why “mention” markets are difficult to police
Mention markets have become one of the most vulnerable areas of event wagering because the outcome can be shaped or known by a small number of people.
In a market based on inflation data or a central bank decision, many safeguards exist before release. The information is often protected by formal embargoes, strict distribution rules and established government security procedures. Even then, regulators monitor for leaks and suspicious pre-release activity.
By contrast, a speech can pass through many hands before delivery. Writers, technical staff, communications aides, event producers, teleprompter operators and senior officials may all see drafts. Even if no one changes the text, multiple people may know whether a target word appears.
The problem is even sharper when the speaker can control the outcome in real time. A host, executive or performer who knows a contract exists may be able to say the relevant word deliberately. That creates a direct manipulation risk.
Earlier incidents have shown the weaknesses of the format. In one televised ceremony, a host unexpectedly referenced a word during the broadcast after market attention had gathered around the term. In another case involving a 2025 corporate earnings call, an executive reportedly read every listed phrase connected to a prediction pool, effectively neutralizing the market and exposing the ease with which such contracts can be distorted.
Those examples have intensified pressure on platforms to limit markets where a small number of insiders can know or determine the result.
Larger markets draw sharper oversight
The case comes as prediction-market trading has expanded rapidly. Research cited in policy discussions has shown monthly volume across major platforms rising from less than $5 billion in September 2025 to roughly $24 billion by April 2026.
That increase has drawn closer attention from federal agencies, lawmakers and compliance teams. Higher volume means larger potential profits for anyone with improper access to non-public information. It also means that retail participants are more exposed when markets are distorted by people who know the result before everyone else.
Regulators have responded by expanding surveillance tools, reviewing account histories, examining wallet and bank-linked activity, and pressing platforms to strengthen identity checks. While prediction markets often use digital interfaces and may involve rapid movement of funds, regulators are increasingly applying principles familiar from traditional markets: suspicious timing, undisclosed conflicts, related-party activity and trades made before public release can all trigger review.
Federal watchdogs are also expected to scrutinize whether traders have employment links to the event being traded. If a person working in government, media production, corporate communications or technical operations repeatedly trades on events connected to that work, platforms may be expected to ask more questions.
Employer disclosures become a compliance tool
Kalshi recently introduced a requirement for users to disclose their employers, a step intended to help identify possible conflicts before they develop into enforcement cases.
Enforcement official Bobby DeNault said the measure is designed to identify trades that may be influenced by professional access to restricted information. The goal is not simply to collect personal details, but to allow compliance teams to compare a user’s job, access and trading activity.
For example, a person employed by a public company’s finance department may raise concerns if they trade contracts tied to that company’s earnings call. A government employee may trigger review if they trade on unreleased policy announcements. A production worker may face scrutiny if they trade on awards-show scripts, performer remarks or broadcast outcomes.
These checks are becoming more important as event markets expand from elections and economic data into entertainment, politics, corporate meetings and public speeches.
Failing to complete employer disclosures accurately can also create problems for traders. Platforms may freeze accounts, delay withdrawals, request documentation or refer activity to regulators if background information appears incomplete or misleading.
Similar cases raise concern
The Perez matter follows other cases involving people accused of using privileged information to trade on event outcomes.
One earlier case involved a U.S. special forces member who allegedly used sensitive geopolitical information to place bets before public developments were known. Another involved a technology engineer accused of using internal corporate information to trade on market events connected to a company announcement.
Together, those cases suggest that regulators see insider misuse in prediction markets as an emerging enforcement priority. The facts differ from case to case, but the pattern is consistent: a person gains access to information through a job or professional role, then uses that access to place wagers in a market where other traders do not have the same knowledge.
The concern is not limited to government. Any workplace that handles confidential plans can create risk if employees trade on related events. Corporate earnings, product launches, merger talks, policy announcements, litigation outcomes, award results and media appearances can all become sensitive when a prediction contract is tied to them.
Safer markets and rising risk awareness
The enforcement action is likely to accelerate a shift away from narrow, easily influenced contracts and toward larger markets tied to broad public indicators.
Contracts linked to national economic data, central bank rate decisions or official growth figures may still carry risk, but they are less likely to be controlled by a single person holding a speech draft. These events usually involve formal release procedures, multiple layers of review and stronger controls around pre-publication access.
By contrast, markets tied to spoken words at small events, private gatherings, corporate calls or scripted public appearances can be vulnerable because one person may know or influence the exact outcome.
For active traders, the clearest compliance lesson is to keep work-related information separate from personal trading activity. Anyone with access to unreleased documents, internal drafts, embargoed figures or confidential plans faces heightened risk if they trade on related contracts.
That risk applies even if the information is not classified or formally labeled secret. The Perez case did not involve a leak of national security material, but regulators still treated the alleged use of non-public speech drafts as serious enough to require repayment, suspension and a ban from related markets.
A warning for the prediction-market industry
The outcome leaves several messages for the industry.
Platforms are under pressure to detect irregular trading before markets settle and funds are withdrawn. Compliance teams will likely expand monitoring for accounts that repeatedly profit from narrow event contracts tied to a user’s profession or access. Regulators, meanwhile, are signaling that digital event markets will not be treated as a loophole where insider-style behavior is ignored.
The case also shows that enforcement does not always require a criminal indictment to carry consequences. Perez avoided prison, but he lost pay, faced professional discipline, had funds frozen and agreed to give back profits. For many traders, account freezes and regulatory referrals can be damaging even without criminal charges.
As prediction markets continue to move into politics, entertainment, business and economic data, the boundaries around non-public information are becoming more important. The more specific a contract becomes, the more likely it is that someone close to the event may have an unfair edge.
Regulators appear prepared to test those boundaries. The suspension of a White House teleprompter operator may be an early case, but it is unlikely to be the last as event-based trading grows and watchdogs sharpen their focus on who knew what, when they knew it and how they traded before the public found out.
Curious about ethical prediction markets after this scandal? Explore how to avoid costly mistakes in future event trading.
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