Prediction Markets – Insider Trading without Insider Trading?
Picture your standard insider trading eLearning course. The concepts are straightforward. Important (material) non-public information can’t be used by in-the-know people in the company or their buddies to trade stock to make themselves money. Easy, right?
Well, the folks at prediction markets – mostly Polymarket and Kalshi – have brought trading on inside corporate information to a whole new category of risk, and we in the compliance field have barely scratched the surface of what this means for us.
Why Prediction Markets are a Problem for Compliance Officers
Prediction markets such as Kalshi and Polymarket allow individuals to place wagers on all kinds of stuff. You probably know that people bet on election outcomes and sports, but did you know that people can wager on corporate announcements, product launches, regulatory actions, executive decisions, promotions, demotions, and marketing campaigns?
While these platforms are often marketed as forecasting tools, they may also create new opportunities for employees, vendors, contractors, government officials, and others to profit from information they obtained through their work.
This is no longer theoretical. We now have real-world (fascinating) examples showing exactly how quickly prediction markets can turn confidential information into personal profit.
Consider the Venezuela Polymarket case. According to the U.S. Department of Justice, Gannon Ken Van Dyke, a U.S. Army soldier, was charged with using classified information about a military operation involving Nicolás Maduro to place wagers on Polymarket.
The government alleged that Van Dyke participated in the planning and execution of the operation. ABC News reported that the bets netted more than $409,000 and that Van Dyke allegedly tried to conceal evidence of the trades after reports surfaced about unusual trading connected to the mission.
This Isn’t Your Usual Stock and Securities Problem
Unlike traditional investing (or insider trading), participants are not buying shares in a company. Instead, they are wagering on whether a specific event will occur.
One of my favorite cases came when federal prosecutors charged Michele Spagnuolo, a Google software engineer, with commodities fraud, wire fraud, and money laundering after he allegedly used confidential internal Google search information.
See – he was privy to the fact that D4vd was the most searched person in 2025, and he made a wager on Polymarket that yielded him $1.2 million using that information. Prosecutors said he used the username “AlphaRaccoon” – because you don’t have to use your real name or real identity on these sites.
Why Existing Insider Trading Policies Are Insufficient
Most insider trading policies were designed around securities transactions. They focus on preventing employees from buying or selling stock while in possession of material non-public information.
Prediction markets create a different challenge. The guilty employee may not trade stock. They may not touch a brokerage account. They may not think they are committing “insider trading” at all. But they are still be using confidential information to make money.
Compliance Implications
Prediction markets create several challenges for compliance officers.
First, there is the confidentiality risk. Employees who use company information for personal gain can create ethical, reputational, and potentially legal concerns.
Second, there is a monitoring challenge. Many organizations have controls related to securities trading, brokerage account disclosures, and blackout periods. Those controls generally do not extend to prediction market platforms.
Third, there is an awareness issue. Employees may not view prediction market activity as problematic. Someone who would never purchase company stock based on confidential information may see no issue with placing a wager on a future business event.
Let’s look to another real-life example. Recently, a person began betting on the outcome of various episodes of the popular Beast Games show. After having a near-perfect winning record, an investigation revealed that the person making the bets was an editor on the program. The person was kicked off the platform and fined $20,000.
This example matters because it is not about Wall Street, earnings calls, or mergers. It is about content. It shows that prediction market risk can arise wherever people know something the public does not – even when that something is the words that will be used by a gameshow host.
Training and Policy Updates to Consider
The good news is that organizations do not need an entirely new compliance framework.
Most companies already have policies addressing confidentiality, conflicts of interest, insider trading, and ethical use of information. The challenge is updating those frameworks to reflect a changing risk environment.
Compliance leaders should review whether current policies explicitly address prediction markets and similar platforms. Policies should make clear that employees, contractors, vendors, and family members may not use confidential company information to place bets, trades, or wagers on future events.
Training is equally important. Many employees have never considered the connection between company information and prediction market activity. Practical examples can help employees recognize risky situations, such as betting on product launches, customer announcements, executive departures, regulatory outcomes, litigation developments, or company-created content.
Human Resources should also be part of the conversation. Recent examples in sports betting have made the link between gambling at work and insider information uncomfortably connected in ways that can bring up mental health protections and potential litigation.
The Next Insider Risk Is Already Here
Prediction markets represent a new way for employees and other insiders to monetize information that was never intended for personal use.
It means that compliance officers should recognize that the line between forecasting, speculation, gambling, and misuse of confidential information is becoming increasingly blurred.
The organizations that address this risk now will be better positioned than those that wait until a headline, enforcement action, employee termination, or regulatory inquiry forces the conversation.
Prediction markets may be new, but the underlying compliance principle is not: information entrusted to employees should be used to benefit the organization — not individual financial interests.