Prediction markets face fresh scrutiny over insider trading amid regulatory gap

High-stakes bets on prediction platforms raise concerns over exploitation of privileged information, prompting regulatory and corporate responses amid legal ambiguities.

Prediction markets face fresh scrutiny over insider trading amid regulatory gap

High-stakes bets on prediction platforms raise concerns over exploitation of privileged information, prompting regulatory and corporate responses amid legal ambiguities.

A series of large, precisely timed wagers on prediction platforms has prompted fresh scrutiny of whether people with privileged information are exploiting these markets for gain. High-profile episodes , including a six-figure Polymarket payoff following the capture of Venezuelan president Nicolás Maduro, reports of a single account netting roughly $1 million from accurate predictions about Google’s 2025 search rankings, and sizeable, well-timed bets on an OpenAI product launch , have fuelled allegations that insiders may be placing bets before news becomes public. According to Axios and reporting in The Information, these events triggered immediate questions about transparency and fairness. [3], [7], [2]

The pattern echoes historical securities abuses from the 19th and early 20th centuries, when corporate insiders routinely traded on nonpublic knowledge prior to modern federal securities rules. Unlike conventional equity markets, however, prediction platforms occupy a legal and regulatory grey area: they are structured as event contracts or wagers rather than traditional securities, and some operate offshore, complicating enforcement. Background on Polymarket’s crypto-based model and its regulatory posture underscores those jurisdictional complications. [5], [7]

Operators of the largest venues insist they prohibit trading on material nonpublic information and maintain surveillance. Kalshi and Polymarket both assert rules against insider trading and other fraudulent behaviour, and platform “watchdog” users sometimes flag suspicious positions for the community to see. Kalshi’s chief executive has publicly supported legislation to bar public officials from trading when in possession of nonpublic government information, framing statutory clarity as complementary to internal controls. [4], [6]

Regulators have begun to respond more directly. In a rare public statement in February 2026 the Commodity Futures Trading Commission’s Enforcement Division asserted it has broad authority to investigate illegal trading on designated contract markets and listed conduct it may pursue under the Commodity Exchange Act, including misappropriation of confidential information, pre-arranged or wash trades, disruptive trading and fraud. The CFTC also emphasised that the DCMs themselves bear surveillance and enforcement duties and said it would work with platforms on referrals for investigation. These pronouncements place prediction-market scrutiny squarely within the commodity regulator’s orbit for now. [1], [2]

Rule 180.1, modelled on SEC antipode provisions, already provides a potential enforcement hook where event contracts are treated as commodities, and the CFTC has invoked similar rules in past insider-trading matters in commodity markets. Where an employee or other insider uses confidential information learned through work, or information subject to NDA protections, regulators say misappropriation theory and existing CFTC rules could support enforcement even if the underlying instrument is nontraditional. Platform employees with privileged platform access also pose a separate compliance risk under existing CFTC personnel rules. [1], [2]

Beyond agency action, a range of federal statutes could be deployed against illicit insiders. Prosecutors have relied on wire fraud and commodities-fraud statutes in prior cases involving misappropriation of market-moving data, and those tools were central in recent prosecutions tied to sports and commodities betting. The Department of Justice and U.S. attorneys have signalled interest in prediction-market abuses; as one senior prosecutor observed, the fact a market is labelled a “prediction market” does not immunise actors from fraud charges. Civil statutes and the Computer Fraud and Abuse Act may also furnish remedies for platforms seeking to block repeat offenders or recover losses. [1], [2]

States may pursue complementary avenues. Consumer-protection and commodities-fraud laws at the state level provide enforcement options, as illustrated by proactive guidance and alerts from state attorneys general ahead of major events. While no high-profile state insider-trading prosecutions tied to prediction markets have been publicly reported to date, regulators possess broad statutory powers they could adapt to these novel trading venues. [1], [4]

Private-sector reactions suggest compliance programmes will need updating. Companies such as OpenAI have already disciplined employees for placing external prediction bets using confidential information, signalling that corporate policies are being applied to these new outlets. Legal advisers and compliance officers are increasingly urging firms to revisit confidentiality, trading and disclosure policies to address the risk that employees or contractors might monetise nonpublic operational or product-planning information on third-party markets. [2], [4]

The emerging enforcement landscape therefore combines established criminal and civil fraud tools, CFTC rulemaking and platform self-policing, together with potential new legislation aimed at closing specific gaps , notably proposals to bar government officials from trading on nonpublic information. As the markets evolve and the volume of event-contract trading grows, regulators, platforms and firms are positioning to deter and, where warranted, punish insider betting using the legal mechanisms that already exist while considering whether more targeted statutory measures are necessary. [1], [6], [4]

Source Reference Map Inspired by headline at: [1]

Sources by paragraph: - Paragraph 1: [3], [7], [2] - Paragraph 2: [5], [7] - Paragraph 3: [4], [6] - Paragraph 4: [1], [2] - Paragraph 5: [1], [2] - Paragraph 6: [1], [2] - Paragraph 7: [1], [4] - Paragraph 8: [2], [4] - Paragraph 9: [1], [6], [4]

Source: Noah Wire Services