Why a Prediction Market Is Now Asking Users Where They Work

Kalshi is a legal prediction market exchange in the United States. It lets people bet on things like whether interest rates will go up or whether a law will pass. According to The Wall Street Journal (June 9, 2026), Kalshi now plans to require users to say where they work before they can trade on certain contracts. The company is still building this system, but the announcement signals that Kalshi is serious about preventing unfair advantages in its marketplace.

Why Your Job Title Matters on a Prediction Market

Imagine a used-car market where one person selling is a mechanic who knows the cars are about to fail, but other buyers don't. That mechanic has an unfair edge. Prediction markets work the opposite way — they try to gather the honest guesses of many different people to figure out what's likely to happen. The price that emerges reflects what people collectively think.

But if someone trades on a prediction market and they work for, say, the Federal Reserve or a big pharmaceutical company, they might know things that haven't been announced yet. A Fed employee might know the committee's decision before it's public. A pharma researcher might know how a drug trial really went. When they trade, they're using private information, not genuine forecasting. Everyone else on the other side of that bet is at a disadvantage.

Kalshi's response is to require users to disclose their employer before trading certain contracts. It's similar to what stock brokers and investment advisers are already required to do — know who their customers are and watch for conflicts of interest. If you're about to trade on whether a central bank will raise rates, and you work at that central bank, you should have to say so. That's the first step to stopping unfair trades.

Kalshi Has Already Caught Traders Breaking the Rules

This isn't Kalshi's first attempt at fair play. Earlier this year, Kalshi (February 25, 2026) announced it had shut down at least two cases of insider trading violation — people using non-public information to trade unfairly. The company can ban violators from the exchange for up to five years.

A five-year ban is serious. For professional traders who use Kalshi, losing access for that long means losing a trading opportunity they can't easily get elsewhere. The fact that Kalshi is publicizing these enforcement cases tells regulators and users that the exchange is willing to take action. It's not just writing rules and ignoring violations — it's actually enforcing them.

How Will Kalshi Actually Check Where People Work?

The details matter a lot here. Kalshi could require disclosure in a narrow way — only for trades directly related to your industry — or a broad way — for every single trade. At the narrow end, a healthcare employee might have to disclose before trading on FDA approval contracts, but not others. At the broad end, Kalshi would collect employer information on everything, creating a bigger database but also more friction for users.

Right now, Kalshi hasn't released all the fine print. The Wall Street Journal's story establishes that the requirement is coming, but the specifics are still being worked out. Which contracts trigger disclosure? How does Kalshi verify you actually work where you say you work? What happens if you lie?

Verification is the hardest part. Simply asking users to type in their employer is not reliable — people can lie. Kalshi will likely need to check claimed affiliations against suspicious trading patterns. They may also need to make the penalty for false claims so severe that lying isn't worth the risk.

Similar Safeguards Already Exist in Other Markets

This kind of problem isn't new to financial markets. Bond traders and currency traders faced similar challenges when electronic trading became common. Exchanges and brokers built systems to classify customers — to tell the difference between informed traders (those with better information) and uninformed traders (those without). Market makers price their trades differently depending on who they're trading with. If a market maker can't tell whether they're trading with someone who has inside information, they widen the gap between their buy and sell prices, or they leave the market entirely.

Kalshi's new rule serves two purposes at once: it's a compliance measure (following the rules) and a market-structure measure (making the exchange work better). When the exchange can cleanly separate informed participants from uninformed ones, professional market makers are more willing to trade there. That leads to tighter spreads — smaller gaps between buy and sell prices — and a deeper market where larger trades are possible. Everyone wins.

The Broader Regulatory Context

Prediction markets operate in uncertain legal territory. The CFTC — a federal regulator — oversees them, but the rules are still being written. As Kalshi pushes into bigger and more sensitive contracts — bets on interest rate decisions, election outcomes, major regulatory rulings — the legal questions get more complicated. Critics worry that prediction markets could be a vehicle for insider trading on sensitive public decisions.

Kalshi's employer-disclosure rule can be read as the company showing the CFTC that it's taking these concerns seriously. It's saying, "We are building safeguards; we are not ignoring the problem." Whether the CFTC thinks the safeguards are strong enough will depend on how thoroughly Kalshi implements the rule and whether it continues to publicize enforcement action against violators.

Questions the Industry Is Watching

As Kalshi builds out this disclosure system, several practical questions will shape how it actually works:

• Which trades trigger disclosure? A broad rule catches more potential problems but creates more hassle for users. A narrow rule is simpler but may miss cases where insiders could cheat.
• How will Kalshi verify your employer? Will it check LinkedIn profiles? Cross-reference trading patterns? Require document upload?
• What happens to the data? Employer information is private. How Kalshi stores it, protects it, and shares it with regulators will matter to users who care about privacy.
• Will competitors follow? If Kalshi's system works and doesn't create too much friction, other prediction markets may adopt the same approach — making it an industry standard rather than a single company's choice.

As prediction markets grow and attract bigger stakes and bigger traders, the policing around them will need to get more sophisticated too. Kalshi is building that infrastructure step by step. The employer-disclosure requirement is the latest piece.