Prediction markets have been having a moment. These platforms, where you can bet on everything from election outcomes to whether OpenAI or Anthropic goes public first, have exploded in popularity across the US. But with that growth has come a ugly underbelly: insider trading that makes traditional markets look tame by comparison.
Now Kalshi, one of the biggest players in this space, is hitting back with a surprisingly aggressive move. The company announced it will start requiring users to disclose where they work before placing certain bets. The goal? To identify and block potential insiders before they can trade.
The logic behind the new rule
Kalshi is targeting what it calls “markets with heightened insider or manipulation risk.” These aren’t your typical sports betting markets. We’re talking about prediction markets that could theoretically be influenced by people with access to non-public information — like employees at the very companies being bet on.
The company plans to use a risk scoring system to flag markets that appear more vulnerable to manipulation, particularly those involving national security matters. By running an assessment on the national security risk a market might present before listing it, they say they can prevent dangerous scenarios where market activity itself becomes a problem.
It’s a smart way to frame it. These platforms have been under fire from multiple directions lately.
The scandals that made this necessary
Let’s be honest: this new policy didn’t come out of nowhere. The investigation into former Congressman George Santos for alleged insider trading on Kalshi made headlines. Then there were the congressional candidates from Minnesota, Texas, and Virginia who were caught betting on their own races. That’s not even the worst of it.
In the first quarter of this year alone, Kalshi referred over 20 cases to law enforcement after conducting more than 150 internal investigations. A Google employee was charged with insider trading for using company information to place bets on Polymarket, a rival platform. A US special forces soldier was allegedly making successful bets regarding the removal operation of Venezuelan President Nicolás Maduro. And the White House even had to warn staff not to use insider information to place bets on prediction markets following suspiciously timed trades ahead of the US-Israel war with Iran.
That’s quite a rap sheet.
So will this actually work?
Here’s where I have some doubts. Asking people where they work is one thing. Verifying that information is quite another. Someone serious about insider trading isn’t likely to honestly answer “yes, I’m an OpenAI employee planning to bet on our IPO timeline.” The system relies on honesty or somehow catching lies after the fact.
That said, it’s not nothing. The policy creates friction, and friction is sometimes enough to deter casual abuse. The real test will be whether Kalshi follows through on screening people out before trades are placed, or if this becomes another paper tiger policy that looks good in a press release but changes little in practice.
What concerns me more overall is the bigger question these markets raise. By letting millions of people wager billions of dollars on essentially any public event, including military actions and political outcomes, we’re effectively gamifying serious real-world issues. The insider trading problem is real, but it’s a symptom of a larger question we haven’t really answered: should prediction markets exist at all in their current form, and what happens when they becometoo big to fail?
