Prediction Markets Have a Trust Problem. Here's How to Solve It.

Prediction markets such as Kalshi and Polymarket have rapidly grown from niche services into highly social platforms with millions of users, creating moderation challenges that traditional gambling and financial products were not designed to address. Features including live trade chats, comments, and social feeds can expose platforms to manipulation, harassment, scams, and other harmful behavior, particularly when real money and fast-moving events are involved. The piece argues that compliance and content moderation serve different purposes, with licensing addressing legality while moderation helps protect users, platform integrity, and access to infrastructure providers such as app stores, cloud services, and payment processors. Citing cases involving Parler, Omegle, and 8chan, it warns that inadequate moderation can produce serious reputational and operational consequences. Stream, which says it moderates 80% of prediction markets, promotes context-aware detection, language models, multilingual tools, and customizable rules as ways for platforms to distinguish ordinary user discussion from coordinated or escalating abuse, while framing user trust and retention as central to the sector’s long-term sustainability.

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