StarCompliance Debuts 1st-Ever MNPI Surveillance for Prediction Markets

For legal departments and compliance officers, prediction markets have long represented a gray area in insider trading statutes. The new solution from StarCompliance and Kalshi provides a systematic method to detect and deter misuse of confidential information on these platforms—potentially setting a new standard for ‘adequate procedures’ defenses.

On June 17, 2026, enterprise compliance technology provider StarCompliance and CFTC-regulated prediction market Kalshi announced a partnership to deliver what they claim is the financial industry’s first enterprise-grade compliance solution purpose-built to monitor employee participation across prediction markets. The announcement, carried exclusively via press release, signals a significant step in addressing a growing compliance blind spot: as prediction markets attract institutional volume, employees of financial services firms gain a new, largely unmonitored channel to trade on material non-public information (MNPI). The solution expands StarCompliance’s existing employee compliance framework—which already covers traditional securities and digital assets—to ingest and analyze Kalshi trading data, providing centralized surveillance of on-chain and off-chain prediction market activity.

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The new solution from StarCompliance and Kalshi provides a systematic method to detect and deter misuse of confidential information on these platforms—potentially setting a new standard for ‘adequate procedures’ defenses.

Prediction markets have matured rapidly since the late 2010s, with platforms like Kalshi, Polymarket, and Manifold offering event‑based contracts on everything from economic indicators to geopolitical outcomes. Kalshi, in particular, operates as a registered Designated Contract Market (DCM) under the Commodity Futures Trading Commission (CFTC), giving it a legal footing that distinguishes it from many purely crypto‑native competitors. Institutional interest has been rising, but the compliance infrastructure to monitor employee misuse had not existed until now. Traditional insider trading policies were designed for equity and fixed‑income markets and generally do not account for event contracts, creating a regulatory vacuum that the StarCompliance‑Kalshi partnership aims to fill. By integrating Kalshi’s data into Star’s platform, the solution claims to provide real‑time alerts, detailed trading oversight, and audit trails that meet supervisory expectations in an era of heightened regulatory scrutiny.

The partnership highlights a broader trend where RegTech firms are racing to cover emergent asset classes before regulators mandate it. Kelvin Dickenson, Chief Product Officer at Star, noted that “as these markets evolve globally, firms need surveillance capabilities that adapt across jurisdictions and provide meaningful visibility into both on‑chain and off‑chain prediction market activity.” His counterpart at Kalshi, VP of Business Development Max Crowley, emphasized that “institutional adoption … requires compliance infrastructure that supports responsible participation while adapting to evolving regulatory expectations.” Both statements, extracted from the press release, underscore the defensive posture many firms will need to adopt: without a dedicated tool, a compliance department might be unable to prove it took reasonable steps to prevent MNPI abuse.

From a market dynamics perspective, the launch could accelerate institutional acceptance of prediction markets. Banks, hedge funds, and asset managers have been cautious about allowing employee participation in event contracts without adequate risk controls; a purpose‑built surveillance module may lower that barrier. For StarCompliance, the move deepens its RegTech moat by adding a unique offering that its competitors currently lack. For Kalshi, the partnership is a signal of institutional readiness, potentially drawing more liquidity from professionally managed pools of capital. However, because the announcement is a press release, the actual depth of integration and the number of early adopters remain unverified. Independent reporting and customer traction data would be needed to corroborate the claims.