Suspicious Trading Surges on Prediction Markets: Kalshi and Polymarket Under Scrutiny

Sharp Rise in Flagged Trades

Prediction market platforms, which allow users to bet on outcomes of events ranging from elections to economic indicators, are experiencing a notable surge in suspicious trading activity this year. According to sources familiar with the matter, Kalshi has already identified and flagged over 400 suspicious trades year-to-date—more than double the total number it investigated throughout the entire 2025. Rival platform Polymarket has reportedly witnessed a similar uptick, raising concerns about market integrity and the effectiveness of surveillance measures.

Suspicious Trading Surges on Prediction Markets: Kalshi and Polymarket Under Scrutiny

Kalshi's 400+ Suspicious Trades

Kalshi’s internal monitoring teams have been busy: the flagged trades span various markets and involve patterns that suggest potential manipulation, such as wash trading, spoofing, or coordinated activity. The volume of flagged trades so far in 2026 already exceeds the total volume from the prior year, indicating that either the platform has improved detection methods or that bad actors have become more active. Sources emphasize that being flagged does not necessarily mean a trade is illegal, but each instance triggers a review.

Polymarket Follows Similar Trend

Polymarket, another leading prediction market, has also detected a rise in questionable activity. While exact numbers were not disclosed, the pattern mirrors Kalshi’s experience. Both platforms operate under U.S. regulatory oversight—Kalshi is registered with the Commodity Futures Trading Commission (CFTC) as a designated contract market, while Polymarket operates with CFTC oversight as well. The surge may lead to increased scrutiny from regulators who are already examining the role of prediction markets in influencing public opinion and financial markets.

Behind the Surge: What's Driving the Activity?

Industry observers point to several factors behind the uptick. First, prediction markets have grown significantly in popularity, attracting a wider user base that includes both retail traders and sophisticated actors. Second, the nature of the events being traded—such as political elections, economic forecasts, and pandemic outcomes—creates incentives for manipulation to sway betting odds or send false signals. Third, the relatively new and decentralized structure of these markets can make surveillance challenging. Unlike traditional exchanges, prediction markets often rely on blockchain technology and pseudonymous users, complicating efforts to trace and verify identities.

Implications for Market Integrity and Regulation

The rise in suspicious trades has significant implications. If left unchecked, manipulated markets could distort public perception of event probabilities, erode trust in the platforms, and attract regulatory enforcement actions. The CFTC has already warned that prediction markets must comply with anti-manipulation rules. Both Kalshi and Polymarket have compliance teams dedicated to monitoring trades, but the volume suggests they may need to invest further in automated detection systems and data analysis.

Furthermore, the surge highlights a broader challenge: balancing market accessibility with robust oversight. As these platforms scale, the risk of illicit activity grows, making proactive surveillance essential. Regulators may push for stricter reporting requirements, including real-time trade monitoring and mandatory reporting of suspicious activity to authorities.

How Platforms Are Responding

Kalshi has publicly stated its commitment to market integrity and has enhanced its monitoring protocols. The platform uses algorithms to detect anomalies and employs a specialized team to review flagged trades. Polymarket has similarly bolstered its surveillance capabilities, utilizing on-chain analysis tools to identify patterns across its decentralized order books. Both companies cooperate with regulators and have implemented user verification processes to reduce anonymity.

Despite these efforts, the sheer volume of flagged trades—more than double previous levels—indicates that the arms race between malicious actors and compliance teams is intensifying. Future developments may include tighter authentication measures, increased use of artificial intelligence for predictive flagging, and cross-platform information sharing.

For users and observers, the key takeaway is that prediction markets are not immune to manipulation. As the industry matures, the expectation for transparency and accountability will only increase. Those participating in these markets should be aware that suspicious activity is being closely monitored, and regulatory action may follow.

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