Summary

  • Kalshi has announced that traders must disclose their employers before engaging in certain high-risk markets, as part of a new "market integrity" initiative that takes effect immediately.
  • So far this year, the exchange has launched over 150 investigations, prevented more than 100 potential insider trades, and sent over 20 cases to law enforcement.
  • These actions come in response to multiple insider trading scandals, congressional inquiries, and criminal prosecutions impacting the prediction market industry.

Kalshi, a prominent player in the prediction market space, is introducing enhanced compliance protocols to tackle rising fears regarding insider trading, as stated by the exchange on Tuesday. This initiative represents the latest effort to safeguard the integrity of a sector facing increasing scrutiny.

The new disclosure requirement targets markets identified as high-risk for insider trading or manipulation, according to a blog post from Kalshi.

We have announced that Kalshi will now require employment disclosures for trading in specific markets.

Market integrity is not just an ideal for us; it’s the reason we gather identification from all traders, monitor our markets continuously, and…

— robertjdenault (@robertjdenault) June 9, 2026

The new rule applies only to markets marked by the exchange as having a high likelihood of insider trading or manipulation, including contracts linked to company performance, national security, and significant geopolitical events like the Iran war.

Traders in these flagged markets will need to submit an online form detailing their employment. Kalshi indicated that it would not verify this information unless an investigation is already in progress, although some users may be restricted from trading specific contracts based on their employment status.

Risk Assessment Framework

Along with the disclosure requirement, Kalshi has introduced a "risk scoring framework" to pinpoint markets with increased insider trading risks.

When a market is proposed for listing, it undergoes an evaluation based on six criteria, which include corporate KPI or event risk, outcome concentration risk, market significance, regulatory risk, non-traditional insider risk, and national security risk.

Markets deemed less significant but with high insider trading or manipulation risks may be denied listing altogether.

This framework also evaluates potential national security risks associated with markets before they are listed.

Robert DeNault, Kalshi's head of enforcement, stated, "By assessing the national security risks a market may present before listing, we can better avert dangerous situations that could adversely affect our markets—or the other way around."

Additional measures include expanded whistleblower tools that allow users to report suspicious activities directly to the company's surveillance team, which monitors public order books around the clock.

The independent Surveillance Audit Committee, responsible for overseeing the integrity and enforcement program, will continue to provide quarterly reports.

This year, Kalshi confirmed it has initiated over 150 investigations, blocked more than 100 possible insider trades using new screening methods, referred over 20 cases to law enforcement, and enacted five disciplinary measures.

The exchange has also fined and suspended three political candidates for trading on their own electoral outcomes, which they termed "political insider trading." Recently, Rep. Bryan Steil (R-WI) proposed adding provisions to the House congressional stock ban bill to encompass prediction markets.

Despite these challenges, Kalshi has quickly expanded its offerings, achieving over $1 billion in perpetual futures trading volume within a week of launch, as reported by data shared with CNBC. The exchange is also seeking to self-certify contracts associated with 12 major altcoins, including Ethereum, XRP, Solana, and Dogecoin.

A Practical Filter

The employment disclosure requirement is described by Marcin Kazmierczak, co-founder and COO of the modular oracle Redstone, as "a useful filter, not a complete solution."

According to Kazmierczak, while this measure will catch obvious violations, such as an employee trading on their own company’s earnings contract, it has inherent limitations. He pointed out that since the information is self-reported and only verified when an investigation is initiated, it creates an incentive for both honest and dishonest individuals.

He elaborated that material non-public information often does not travel through clear employment channels, instead circulating through contractors, suppliers, advisors, friends, and family—none of whom would be captured in an employer disclosure.

Thus, Kazmierczak believes that disclosures should serve primarily as an input into the risk-scoring and surveillance framework rather than standing alone as a barrier. He cautioned against the risk of overreach, insisting that prediction markets thrive on informed participants trading based on their expertise.

He emphasized that there is a significant distinction between trading based on legitimate knowledge and trading on material non-public information, warning that overly broad employer checks could inadvertently hinder legitimate traders alongside true insiders.

Kazmierczak concluded by stating that users should be informed about how their employment data is stored, accessed, and shared with regulatory bodies, noting that while this is standard for regulated brokerages, it is uncharted territory for prediction markets, and users should expect similar standards for financial platforms handling identity and conflict data.