House Lags Senate on Prediction Market Trading Ban

Lawmakers in the House are weighing new restrictions on prediction markets following reports of individuals using nonpublic information to place bets on political and policy outcomes. The discussions come as more than a dozen bills targeting such platforms have been introduced this year, though none have advanced far in the legislative process.

Prediction markets allow participants to wager on events ranging from election results to regulatory decisions. Platforms such as Kalshi and Polymarket have seen billions in volume weekly, drawing interest from traders seeking to profit from accurate forecasts. Proponents have long argued these markets aggregate dispersed information more effectively than traditional polling or expert analysis.

Recent cases have raised questions about misuse. Federal prosecutors charged a U.S. soldier last month with using classified material to secure over $400,000 in gains on a bet involving the removal of Venezuelan leader Nicolás Maduro. Separate reports indicated a campaign staffer profited thousands by betting on a candidate with access to unreleased polling data. These incidents prompted Rep. Ritchie Torres of New York to introduce legislation that would prohibit campaign staffers from betting on their own races and impose criminal penalties, including up to five years in prison, for using campaign funds in such markets.

Torres and a bipartisan group of colleagues have also urged House leadership to adopt internal rules barring members and staff from participating altogether. The Senate has already moved to restrict its own personnel from these activities. House members and aides remain free to trade for now, a distinction some view as inconsistent.

The push for tighter controls reflects broader congressional efforts to address emerging financial technologies. Similar patterns appeared with cryptocurrency and artificial intelligence, where lawmakers introduced numerous measures yet struggled to enact comprehensive rules before markets expanded. Kalshi has responded by implementing its own limits on certain bets involving government insiders, though critics say voluntary steps fall short.

From a market perspective, outright prohibitions risk driving activity offshore or underground without eliminating the underlying incentives for informed betting. Existing securities and insider trading laws already apply to many forms of nonpublic information use, suggesting enforcement enhancements might address abuses more directly than new categorical bans. Historical experience with regulatory expansions shows they often impose compliance costs that favor larger platforms while reducing liquidity for smaller participants.

Data from past election cycles indicate prediction markets frequently outperformed conventional forecasts in accuracy, providing signals that influenced media coverage and campaign strategies. Restricting access for those closest to policy decisions could blunt this informational edge without guaranteeing cleaner outcomes. Lawmakers face the challenge of distinguishing legitimate trading from prohibited conduct in fast-moving digital environments where enforcement remains resource intensive.

Continued debate will likely center on whether targeted rules for federal employees suffice or whether broader prohibitions better serve public confidence.