Key Takeaways
- New academic research proposes that prediction market insider trading enforcement requires “calibration, not maximization”
- An economic model demonstrates that excessive or insufficient enforcement both diminish market precision
- Kalshi implemented mandatory employer disclosure for traders participating in high-sensitivity markets
- During Q1 2026, Kalshi submitted 20+ reports to authorities and prevented 100+ suspected insider transactions
- Criminal charges were filed against a Google employee and a military service member for insider trading on Polymarket in 2026
Prediction platforms face mounting scrutiny over insider trading abuses, prompting Kalshi to implement significant operational changes. Simultaneously, fresh academic analysis is challenging the conventional wisdom around enforcement strategies.
Balbinder Singh Gill, who serves as an assistant professor specializing in finance at Stevens Institute of Technology, released research on June 2 contending that enforcement measures need careful calibration rather than blanket maximization.
His economic framework revealed that prediction market precision follows a “hump-shaped” pattern relative to enforcement intensity. Insufficient oversight allows insiders to dominate and displace ordinary participants. Conversely, excessive enforcement eliminates the valuable intelligence that informed insiders contribute.
“The identical insider transaction that enhances price accuracy in the present can diminish the participation that sustains price informativeness in the future,” Gill explained.
Enforcement Should Vary by Trade Type
Gill contends that insider trades cannot be treated uniformly. Participants who developed information through independent analysis deserve minimal enforcement, since penalizing them discourages valuable knowledge creation.
Participants exploiting leaked or confidential materials warrant stronger enforcement measures. Those with actual power to influence outcomes — such as political figures wagering on their own electoral contests — require the most severe consequences.
“Transactions by individuals capable of affecting outcomes demand the strongest enforcement, as their positions create manipulation incentives,” Gill stated.
Kalshi Implements New Compliance Measures
Kalshi unveiled updated regulations this week following recommendations from its independent Surveillance Audit Committee, established during February 2026.
Participants trading in high-sensitivity markets — encompassing those connected to corporate results or national defense matters — now face mandatory employer disclosure through a digital submission system before executing trades.
Kalshi additionally deployed a risk-assessment algorithm for individual markets, evaluating variables including regulatory alignment, insider trading exposure, and national security implications.
New whistleblower mechanisms were introduced, enabling platform users to flag questionable trading activity directly to compliance teams.
Throughout Q1 2026, Kalshi submitted over 20 cases to law enforcement agencies, conducted more than 150 internal investigations, and prevented over 100 suspected insider transactions through its detection infrastructure.
These initiatives arrive following two prominent prosecutions on competing platform Polymarket. Criminal charges were filed in May against a Google engineer accused of leveraging proprietary corporate intelligence to generate approximately $1.2 million in profits. In April, a U.S. military member faced charges for executing trades based on classified operational knowledge.
Last week, reports emerged that the DOJ and CFTC were examining former congressman George Santos after Kalshi suspended his account due to questionable trading activity connected to President Trump’s February State of the Union speech.
Kalshi documented $16.81 billion in monthly transaction volume during May 2026, representing growth from $14.81 billion in April. Polymarket registered $7.08 billion in May, declining from $9.01 billion the previous month.
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