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Trump Aide Ordered to Pay $172k for Prediction Market Bets

A former White House employee was ordered to pay $172,000 in fines due to a Kalshi insider trading case. Gabriel Perez, a teleprompter operator for President Donald Trump, reportedly used nonpublic information for personal benefit, generating over $100,000 in initial profits. Perez cashed in on Kalshi event markets framed around…

Kevin Roberts
Kevin Roberts Writer
08/29/2026
Trump Aide Ordered to Pay $172k for Prediction Market Bets

A former White House employee was ordered to pay $172,000 in fines due to a Kalshi insider trading case. Gabriel Perez, a teleprompter operator for President Donald Trump, reportedly used nonpublic information for personal benefit, generating over $100,000 in initial profits.

Perez cashed in on Kalshi event markets framed around words that would appear in Donald Trump’s speeches. His ability to have advanced access to Trump’s speeches gave him a distinct advantage over the public, creating an unfair trading environment. Perez reportedly committed the infractions from December 2025 to March 2026, but was only recently officially fined.

White House Teleprompter Operator Exploits Access

The news of Gabriel Perez’s offense was first reported earlier this summer, with numerous outlets detailing his Kalshi insider trading case.

Perez was accused of exploiting access to President Donald Trump’s speeches, which he was able to review before they became public. Perez then used this privileged information for financial gain on Kalshi’s presidential “mention” markets.

According to the CFTC, Perez placed over a dozen wagers on what Trump would say in speeches over a three-month stretch.

Perez’s actions generated over $107,000 in profits, but his success triggered Kalshi’s surveillance team. Kalshi quickly identified patterns and flagged Perez for suspicious activity before freezing his account and referring the case to the CFTC.

More Than Just a Fine

Perez’s ruling set him back financially, as he was ordered to return the original $107k he “won”, but was also hit with an additional fine of $65,000.

On top of having to pay $172k back to Kalshi, Perez was also handed a three-year ban from exchanging event market contracts on Kalshi.

Per the CFTC, Perez actually received a light fine despite his infraction. The commission revealed that his penalty could have been steeper, but that he earned a “significant discount” due to cooperating with the investigation.

In addition to his financial setback, Perez was placed on unpaid administrative leave by the White House. 

Trump’s Interesting Relationship with Prediction Markets

Despite Donald Trump’s public backing of prediction markets, the White House reemphasized the strict guidelines its employees have to follow and submitted an internal memo to remind its staff to not use privileged information to profit on prediction markets.

It’s certainly ironic that a major Kalshi insider trading case stems from Donald Trump’s administration, especially given how vocal he has been against official prediction market regulation.

Trump’s son Donald Trump Jr., who has been involved in an adviser role for both Kalshi and Polymarket, also owns a venture-capital firm that has invested in prediction markets. 

This is interesting due to Trump’s previous statements on prediction markets, with the POTUS suggesting that it is “critically important” that the CFTC remain the exclusive authority in deciding prediction market cases.

The Trade Handle Prediction Markets Take

This is undeniably bad PR for prediction markets, and the fact that corruption can go all the way to the White House is definitely concerning.

However, there are two strong takeaways that suggest optimism in the future: Kalshi was able to identify patterns of corruption, and the prediction market platform was able to hand down real penalties.

Perez committed an obvious infraction and was caught, while he was fined, banned, and ordered to pay back the money he won.

Corruption is going to exist anytime you’re dealing with money and a quick path to make a lot of it. However, Kalshi and other prediction markets are setting a firm foundation that displays their ability to track negative activity and respond with appropriate punishment that can help deter future infractions.