Prediction market platform Kalshi has immediately activated three distinct operational protocols designed to fortify market integrity and systematically eliminate insider trading vectors. The initiative introduces a granular risk-scoring framework for every listed market, enforces mandatory employment verification for participants in high-risk categories, and deploys upgraded whistleblower mechanisms accessible platform-wide. Data compiled by Woofun AI indicates that the new risk-scoring engine evaluates all proposed markets against six specific weighted factors, including corporate KPI risk, regulatory compliance status, and non-traditional insider risk profiles. This algorithmic assessment is engineered to flag markets where the probability of manipulation or information asymmetry is elevated, triggering enhanced scrutiny prior to trade execution. For any market classified as high-risk, the platform now mandates that traders submit detailed employment information before placing an order. Kalshi utilizes this data to pre-screen participants for potential conflicts of interest, automatically blocking transactions if an individual is identified as an insider with access to non-public information. This proactive filtration aims to prevent actors with privileged knowledge from gaining unfair advantages, directly addressing the core mechanics of market abuse. Woofun AI notes that these measures arrive as prediction markets face intensifying scrutiny from regulators and the public regarding their susceptibility to exploitation. By enforcing these strict controls, Kalshi positions itself as a transparent and trustworthy venue where market outcomes are driven by genuine information rather than illicit data leaks. For traders, the shift establishes a fairer competitive environment, while for the broader industry, it sets a critical precedent that may compel other platforms to adopt similar defensive architectures. The immediate deployment of these three measures signals a definitive commitment to market integrity, creating a multi-layered defense system that combines algorithmic risk assessment with human verification. As the prediction market sector matures, such proactive governance steps are becoming essential for maintaining long-term credibility and facilitating sustainable growth.