Why Prediction Markets Are Keeping Compliance Chiefs Up at Night 

That’s the warning at the heart of a new legal alert from Ropes & Gray, a prominent global law firm. The firm is urging companies to take a hard look at whether their existing compliance programs are equipped to handle the growing risks posed by prediction markets. These are online platforms where users wager real money on the outcome of future events, from elections to economic indicators to corporate deals.

The core problem, according to Ropes & Gray, is a regulatory blind spot. Companies have long had systems in place to prevent employees from trading stocks based on inside information. But prediction markets fall outside those guardrails entirely. An employee can place a bet informed by sensitive company research or confidential client data, and current pre-clearance systems won’t catch it. These are the internal checkpoints companies use to flag suspicious trades.

“Existing pre-clearance systems do not cover such activity,” the firm writes, “thus allowing the prediction market position to be placed without detection.”

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The risks do not stop at the individual employee level. Ropes & Gray outlines two categories of information that could be exploited. The first is client and counterparty data, meaning sensitive details shared under confidentiality agreements or NDAs. Using that information to place a prediction market bet could breach those agreements, even if the information does not technically qualify as insider trading under securities law.

Related: Predicting the Scope of Forthcoming Prediction Market Regulation

The second risk is a company’s own proprietary research and analytical models. That kind of intellectual property is expensive to build. Using it for a personal side bet, the firm argues, is a fundamental breach of trust.

The reputational stakes are high. Clients who discover their confidential information was used to place personal wagers will lose faith quickly. Beyond the trust damage, companies could face contractual liability from information owners and may even be required to notify those owners that their data was misused.

So what should companies actually do? Ropes & Gray lays out four questions every compliance leader should be asking. Does the company want to outright prohibit employees from participating in prediction markets? Do existing policies, most of which were written before prediction markets existed, actually cover this kind of activity? Are there tools in place to detect undisclosed activity? And are information barriers strong enough to manage conflicts, or is a blanket ban the safer path?

The firm stops short of prescribing a single answer. But the direction of travel is clear. Companies that rely on broad, principles-based codes of conduct may be technically covered, but that may not be enough. Specific training, updated policies, and clearer examples are increasingly necessary.

Prediction markets have grown fast. Regulation has not kept pace. And as these platforms attract more users and more money, the pressure on compliance teams will only increase. Ropes & Gray’s message is simple: get ahead of this now, before a headline forces your hand.