The High Price Of Insider Information: What Prediction Markets Mean For Investment Funds And Corporate Clients

A Teleprompter, a Trade, and a Compliance Warning

A White House teleprompter operator, Gabriel Perez (“Perez”), is the latest name tied to a federal insider trading inquiry involving prediction markets. Perez allegedly used advance knowledge of President Trump's prepared remarks to win more than $100,000 on Kalshi's "Mentions" markets. On July 16, 2026, it was widely reported that Kalshi's surveillance system flagged the trades, froze roughly $90,000 in profits, and referred the matter to the Commodity Futures Trading Commission (“CFTC”). Perez is on unpaid leave and reportedly in settlement talks with the CFTC. He has not been criminally charged, and federal prosecutors in Manhattan declined to open a criminal investigation.

Kalshi now requires users to disclose their employer before placing certain bets, and that requirement is not just a box to check. The CFTC’s own Director of Enforcement has explained that the agency’s insider trading authority rests on the misappropriation theory, not the classical theory that applies to corporate insiders trading against their own shareholders. Liability under that theory turns on whether the trader breached a duty of trust and confidence owed to the source of the information, typically the employer. That is precisely why Kalshi now asks who you work for before you can bet: it is collecting the fact that determines whether a duty existed and to whom it was owed. For companies, that distinction is the starting point for building an effective compliance plan, since it shows exactly what creates liability and where policies need to focus. It is also a jurisdictional limit specific to the CFTC. The Securities Exchange Commission (“SEC”) and Department of Justice (“DOJ”) are not bound to the same theory and can pursue related conduct under securities fraud, wire fraud, or other statutes. A trade that falls outside the CFTC’s misappropriation framework can still draw scrutiny from other agencies.

The case sits inside a larger shift. Kalshi plans to open betting on FDA approvals and clinical trial results, a category with a fraught history: 2000s-era insider trading around a drug rejection sent both a pharmaceutical CEO and a well-known businesswoman to prison. At the same time, reported enforcement case volume at the CFTC and SEC has declined in recent periods even as these markets expand into more sensitive categories. Only two people, Gannon Ken Van Dyke and Michele Spagnuolo, have been criminally prosecuted for prediction market abuse so far, and both are contesting the charges. Companies and investment funds active in this space, or with employees who trade on it, should treat this as a live compliance priority rather than a one-off story.

What Kalshi Is Doing

Traders must disclose their employer before placing bets in markets tied to material nonpublic information, including company performance and national security events. Kalshi will not verify this information upfront in most cases but will investigate and demand proof of employment once an account is flagged. The company has paired this with an expanded whistleblower program and made more than 20 referrals to federal regulators in the first quarter of 2026 alone.

Kalshi's planned move into FDA and clinical trial betting raises the stakes further. The company says it will bar employees of drugmakers and anyone with access to unblinded trial data and will delay betting until after trial enrollment closes. That policy governs who can bet. It does not govern who inside a drug company might act on nonpublic trial information through other channels.

The Perez Case and What It Signals

Perez held a position with routine advance access to remarks before delivery. Investigators allege he placed bets on more than a dozen speeches over three months, including the State of the Union and a Medal of Honor ceremony. A March 2026 internal memo from the White House had already warned staff that trading on nonpublic information was a serious violation, which may bear on how the pending CFTC settlement is resolved.

No criminal charges were filed here. That outcome fits a broader pattern of declining enforcement volume even as prediction markets grow. Companies should not read declining enforcement as declining risk. A civil settlement can still carry real consequences, and a company's name can enter a federal file even where no one is ever charged.

What This Means For Your Business

Prediction market activity creates legal exposure well beyond the trader. An employee's advance access to earnings data, product timelines, trial results, or public statements can support a regulatory referral even where no criminal charge follows.

Employer disclosure requirements expand your footprint in these investigations. Kalshi's policy means your company can be identified as part of an inquiry the moment an employee's account is flagged, often with no advance notice.

A thinner enforcement record raises the value of internal controls. With reported case volumes down at both agencies, companies cannot count on regulators to catch problems early. Internal policies, monitoring, and training carry more of the load than they did two years ago.

Life sciences and pharma clients face a new category of exposure. Kalshi's move into FDA and trial-result markets creates fresh insider trading risk for drug company employees and their business partners, well before any single case tests the policy.

Preservation obligations can arise before any subpoena does. Kalshi caught Perez through its own surveillance system and referred him to the CFTC on its own initiative, well before any subpoena or law enforcement request was involved. That kind of platform-initiated referral is often the first signal a company gets that an employee is under scrutiny. Companies should have a preservation protocol ready to activate the moment they learn of one.

Existing trading policies likely do not cover this. Most employee trading policies address securities markets and say nothing about prediction markets. Companies should confirm their policies extend to this conduct and that employees understand they do.