House Bill Targets Political Insider Trading on Prediction Markets
Representative Don Davis (D-NC) has introduced the "No Betting on Your Own Race Act," a legislative measure aimed at barring federal candidates, their spouses, and campaign committees from trading prediction market contracts related to their own elections. According to Decrypt, violations of the proposed law would incur a civil penalty of $10,000 per offense or three times the net financial gain, whichever is larger.
The prohibition is drafted broadly to encompass direct and indirect exposure. It covers contracts settling on overall election winners, vote shares, margins, placement, and whether an individual remains in a race. The bill also penalizes candidates who induce others to trade or fund another person's position with knowledge of its intent.
Platform Immunity and FEC Requirements
A significant portion of the bill focuses on shielding exchanges from liability. Prediction market platforms would receive legal immunity for acting in good faith to suspend accounts, void positions, and report suspected breaches to the Commodity Futures Trading Commission (CFTC), the Attorney General, or the Federal Election Commission (FEC). To facilitate compliance and screening for platforms offering prediction markets with API access, the FEC would be mandated to publish a free, machine-readable list of all federal candidates, updated at least weekly.
Until now, exchanges have largely had to police the issue internally. Kalshi previously issued fines and suspensions to congressional candidates, including Mark Moran, for trading on their own races in Minnesota, Texas, and Virginia. As the debate over Kalshi vs Polymarket regulatory approaches continues, political insider trading remains a critical vulnerability for the sector.
The urgency of the issue is reflected in broader industry discussions. According to NEXT.io, the upcoming NEXTPredict summit on October 22-23 will feature a dedicated session on insider trading chaired by WilmerHale's Matthew Kulkin. NEXT.io co-founder Pierre Lindh highlighted the practice as the industry's "most exposed point" and the most difficult challenge to resolve as prediction markets reach mainstream audiences.