CFTC Hits White House Aide With $107,539 Disgorgement in Bitcoin (BTC) Prediction-Market Enforcement

The CFTC ordered White House aide Gabriel Perez to disgorge $107,539.02 and pay a $65,000 fine over Kalshi bets on Trump's speech text before it was read aloud.

(10:39 PM UTC)
4 min read
AI SummaryAI
  • CFTC ordered Gabriel Perez to disgorge $107,539.02 in Kalshi speech-bet profits.
  • Perez paid a $65,000 civil penalty and received a three-year trading ban.
  • George Santos paid a $17,500 fine with $17,569.98 clawed back in July.
  • A May CFTC policy reserves the deepest penalty discounts for self-reporters.
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CFTC Order Hits White House Speech Bets

The Commodity Futures Trading Commission (CFTC) and prediction-market operator Kalshi both moved against a White House teleprompter operator on Friday, closing a case that first surfaced in July. Gabriel Perez had wagered on the text of a presidential speech before Donald Trump read it aloud, and the CFTC enforcement order now requires him to hand back every dollar of it: $107,539.02 in profit disgorged. On top of that, Perez owes a $65,000 civil monetary penalty and cannot trade for three years. The penalty was reduced, and the order says so explicitly, crediting what it describes as Perez’s exemplary cooperation with the agency. That cooperation came with an asterisk: Kalshi flagged his account and sent the file to Washington itself, and Perez spoke to investigators only after they reached him. He never turned himself in. That detail matters because a CFTC policy issued in May reserves its deepest penalty discounts for people who report themselves first, and the order never states which tier Perez actually landed in. For our desk, the takeaway is structural rather than personal — even routine trading volume on a US-regulated venue leaves a full audit trail, and an insider position on speech content is no harder to trace than any other order-book record. The speech bets were already public knowledge by July, when Perez still held the job, which made the unwind only a matter of time once the exchange acted.

Kalshi Enforcement Warning and the Santos Benchmark

Kalshi’s head of enforcement, Robert DeNault, published the outcome and framed it as a warning to every user of the platform, writing that it does not matter who you are — violate the rules or federal law and consequences follow. The pricing of that outcome becomes clearer when set beside the agency’s previous case. In July, the CFTC fined former congressman George Santos $17,500 and clawed back $17,569.98, meaning Santos paid roughly one dollar in penalties for every dollar he made. Perez paid about 60 cents on the dollar. Both men drew identical three-year bans, and their orders landed just 28 days apart. Measured on the Santos yardstick, Perez would have owed close to $107,000 in penalties; he was assessed $65,000. The gap is the market price of cooperation, at least as this agency currently applies it. The timing also carries political weight: only eight days earlier, CME Group chief Terry Duffy had cited this very episode in a clash over prediction markets, arguing that US-listed event contracts can be gamed, while CFTC Chairman Michael Selig dismissed the examples as offshore activity. Friday’s order undercuts that framing. Perez traded on a domestic, CFTC-regulated exchange — the same exchange that caught him — and Kalshi continues to list contracts on whatever the president says next, treating enforcement as part of the product rather than a threat to it. Readers tracking the market in real time can follow live spot and futures prices on Bitget.

What the Order Sets as Precedent

COINOTAG’s reading of the document itself: this is a final enforcement order, not a proposed rule, and it binds Perez directly through disgorgement, penalty and ban while signaling to every account holder on a CFTC-regulated venue that insider-style wagering is prosecutable conduct. For Bitcoin (BTC) and the broader US market-structure debate, the case is a quiet counterargument to claims that regulated American venues cannot police manipulation. It also quantifies cooperation — roughly a 40% penalty discount for someone who did not even self-report — which traders and compliance teams on dapp-based and exchange-listed prediction markets alike should price into their risk models going forward.

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