Amit Mahensaria, the CEO of the P2P sports prediction exchange Pred, agrees that self-regulation is a “must-have.”
“Any platform serious about longevity should be building integrity infrastructure regardless of whether a regulator is watching,” Mahensaria said. Such self-regulation involves implementing surveillance systems, clear settlement rules, manipulation detection, and transparent reporting.
The Limits of Self-RegulationHowever, Mahensaria concurs with critics that self-regulation has its limits. While incentive structures are apparent in the short term, history suggests industry players often take serious action against malpractice only after encountering significant crises.
While blockchain-based platforms are broadly scrutinized, those focused on verifiable outcomes with natural timelines have faced less backlash. Mahensaria noted that platforms like Pred have a structural integrity advantage over markets based on political events or geopolitical conflicts, where outcomes can be subjective, manipulable, or ethically fraught.
“Markets on assassinations, wars, or political crises raise real ethical concerns that the industry shouldn’t dismiss as squeamishness,” Mahensaria said. “The question isn’t just whether such markets can be settled accurately. It’s whether they create perverse incentives and whether the information they aggregate is worth the moral cost of the mechanism.”
When asked who should be mandated with curating bets before listing, Mahensaria suggested a combination of platform discretion and regulatory frameworks. He argued that platforms must exercise judgment and explain it publicly, while regulators should set boundaries around clearly harmful categories.
Meanwhile, some proponents are turning to artificial intelligence to detect insider trading, a vision epitomized by the recent partnership between Polymarket, Palantir, and TWG AI. Mahensaria believes the industry is currently lagging behind traditional financial markets in this deployment.
“AI is genuinely useful here. The core application is pattern recognition across large datasets: identifying trading behavior that deviates from expected models in ways that correlate with insider knowledge or coordinated manipulation,” Mahensaria explained.
FAQ What has sparked scrutiny of prediction markets recently? Increased mainstream attention followed their accurate forecasting of Donald Trump’s 2024 presidential victory. What are the main concerns regarding prediction markets? Concerns include insider trading allegations and the potential for creating ethical dilemmas and perverse incentives. What regulatory approaches are being proposed? U.S. lawmakers are advocating for legislation to restrict certain high-stakes contracts like those involving death and war. How do industry leaders propose to address these challenges? Amit Mahensaria suggests adopting self-regulation alongside proportionate government oversight to establish ethical standards without stifling innovation.
