Why Prediction Markets Need Trust and Safety Professionals

Prediction markets are no longer a niche corner of fintech. They are rapidly becoming a central feature of the modern information and financial ecosystem. While the explosive growth of sports betting following the 2018 repeal of PASPA reshaped the gambling landscape, a quieter but equally consequential shift has taken place in event-based markets. The turning point came when the sports betting company Kalshi secured a landmark 2024 court victory enabling it to offer prediction markets on US elections, followed shortly by its expansion into sports-related contracts ahead of the 2025 Super Bowl.

Since then, the industry has accelerated dramatically. Sports-related prediction markets account for the majority of activity on Kalshi and more than 60% of open interest on Polymarket, both of which are reportedly on trajectories toward valuations exceeding $20 billion. This growth is unfolding in a political environment broadly favorable to the sector, further reinforcing expectations that prediction markets will scale quickly in both scope and influence.

But as these platforms expand, they are doing more than creating new financial instruments. They are embedding financial incentives directly into how real-world events are reported, interpreted, and even contested. That shift introduces a new category of risk that existing regulatory and integrity frameworks are not fully equipped to address.

Expanding risks

As prediction markets expand, so too does the range of events they encompass. What began with relatively contained domains like elections and sports has broadened to include pop culture outcomes, weather events, geopolitical conflicts, and even questions tied to the tenure or survival of political leaders. This expansion fundamentally changes the risk profile of these platforms.

The most immediate concern is insider trading. Reports have already surfaced of individuals attempting to profit from privileged or nonpublic information. A widely cited case involved an employee dismissed from OpenAI after allegedly using proprietary information to inform trades on external prediction markets. Other examples include allegations tied to geopolitical events, where traders appeared to anticipate military developments, raising concerns about access to sensitive information. In Israel, authorities have reportedly investigated soldiers suspected of using classified knowledge to place bets tied to conflict-related outcomes. Recently, the US charged an individual from Army special forces for profiting from classified intelligence by placing bets on the US military operation in Venezuela.

Beyond insider activity, there is growing evidence that participants may attempt to manipulate the information environment itself. Analysts have pointed to cases where publicly available data or reporting was altered in ways that aligned with market incentives. Even more concerning are incidents that would involve direct pressure on journalists. In one documented case, a reporter covering a missile strike reported receiving threats and financial inducements from individuals seeking to influence his reporting to affect the resolution of a high-value prediction market.

These dynamics illustrate a deeper structural issue. Prediction markets do not simply reflect reality; they can incentivize actions that shape it. When financial gain is tied to how events are reported, verified, or interpreted, participants may seek to influence those processes directly. This transforms prediction markets from passive forecasting tools into active components of the information ecosystem and introduces risks that extend far beyond traditional concerns about fraud or market manipulation.

Legislative policy response and its limits

Once financial incentives are attached to wars, political crises, and other high-stakes events, the regulatory question becomes unavoidable: How should governments oversee markets built on real-world uncertainty?

Lawmakers in Washington have begun to engage. Senators Jeff Merkley (D-Ore.) and Amy Klobuchar (D-Minn.) introduced legislation that would bar senior federal officials from participating in prediction markets, citing concerns about conflicts of interest and the emergence of so-called “death markets.” Representative Ritchie Torres (D-NY) has advanced a more targeted proposal focused on insider trading, seeking to prohibit the use of nonpublic government information in event-based trading.

These efforts address real risks, but they also highlight how narrow the current policy conversation remains. One major challenge is attribution. Detecting insider participation requires not only legal authority but also systematic monitoring (something government agencies are not yet equipped to perform at scale). Another issue is ambiguity. Many contracts may implicitly hinge on outcomes such as death or incapacitation, even when not explicitly stated, creating legal and ethical gray areas that are already producing disputes.

Technological change further complicates the picture. Emerging decentralized platforms could allow users to create markets without centralized oversight, undermining regulatory approaches that rely on identifiable intermediaries. In short, policymakers are attempting to regulate a market structure that is evolving faster than the frameworks designed to govern it.

Emerging integrity monitoring focused on sports trading

Regulators are beginning to respond, particularly in the context of sports-related prediction markets. Recent guidance from the Commodity Futures Trading Commission (CFTC) emphasizes the need for exchanges to partner with leagues and establish data-sharing relationships with integrity organizations. A key component of this approach is the use of third-party data integrity partners to monitor trading activity and detect potential manipulation.

Industry actors have moved quickly to align with this model. Polymarket, for example, announced a partnership with Palantir aimed at building a comprehensive integrity infrastructure, including real-time anomaly detection, trade monitoring, prohibited participant screening, and formalized investigation and reporting processes. Similarly, platforms like Kalshi describe internal systems designed to detect suspicious trading, investigate irregularities, and enforce rules through penalties or referrals to regulators.

These measures represent a significant step forward but they are largely derived from the sports betting playbook. They are well-suited to identifying match-fixing, insider athletes, or irregular betting patterns. They are far less equipped to address a different class of risk: the manipulation of information, the targeting of journalists or institutions, and the broader incentives that prediction markets create around shaping real-world narratives.

Expanding integrity beyond sports

While the efforts to help build integrity frameworks for sports markets are a strong foundation, they are insufficient for the broader universe of prediction markets, especially those tied to geopolitics, public safety, and societal outcomes. These markets introduce risks that extend beyond trading behavior into the realm of information integrity and real-world harm.

Addressing these challenges may seem daunting, but there is an existing field with relevant expertise: trust and safety. Professionals in this domain have spent years managing the real-world consequences of digital platforms, from harassment and coordinated manipulation to policy design across jurisdictions. Their skillset is directly applicable and urgently needed in the prediction market ecosystem.

1. Platform governance: market design and rules

Trust and safety professionals can play a critical role at the earliest stage of market creation: how questions are framed and structured. The wording of a prediction market contract is not neutral, because it defines the incentives for participants and can create unintended pathways for manipulation or harm.

For example, ambiguous phrasing such as “out as President before…” can create confusion around whether outcomes like death, resignation, or removal are included. Such ambiguity not only increases the likelihood of disputes but can also incentivize harmful speculation or behavior. Trust and safety teams are well-versed in identifying how language can be exploited, a skill developed through years of safety operations and content policies.

Incorporating pre-listing risk assessments that are similar to frameworks proposed in integrity monitoring models would allow platforms to evaluate how a given market might incentivize harmful actions. This includes assessing source vulnerabilities, identifying potential targets (such as journalists or public officials), and designing clear resolution criteria.

Working alongside sports betting professionals, who bring expertise in odds-making and fraud detection, trust and safety teams can help ensure that market design minimizes both financial manipulation and real-world harm.

2. Enterprise risk: insider threats and external pressure

Prediction markets introduce a new category of enterprise risk for companies and institutions. Employees with access to sensitive information may be incentivized to use that information for personal gain, while organizations themselves may become targets of external pressure from market participants seeking to influence outcomes, and also organizational harm to brand reputation, as we are currently seeing in professional sports.

Trust and safety professionals are uniquely equipped to address these challenges. Their experience with insider risk, data governance, and abuse prevention can inform internal policies that restrict trading based on access to nonpublic information. This includes identifying high-risk roles, implementing monitoring mechanisms, and establishing clear enforcement protocols.

At the same time, trust and safety teams can help organizations respond to external threats. Journalists, researchers, and public-facing employees may face harassment or coercion from individuals attempting to influence reporting or decision-making tied to market outcomes. Established trust and safety practices (such as escalation protocols, incident response frameworks, and cross-platform coordination) can be adapted to these scenarios.

Additionally, techniques used to detect coordinated inauthentic behavior (CIB) can help identify efforts to manipulate markets through misinformation campaigns or coordinated trading activity, further bridging the gap between platform integrity and organizational security.

3. Public policy: regulation, enforcement, and governance

At the policy level, trust and safety professionals can help governments design more effective and realistic regulatory frameworks. Rather than relying solely on prohibitions (which may push activity offshore or into decentralized systems) policymakers should focus on enforceable standards that address both market behavior and information integrity.

This includes establishing requirements for third-party integrity partners, creating independent dispute resolution mechanisms, and developing consent-based approaches to market creation. Models from traditional betting, such as independent adjudication services, offer a useful starting point but must be adapted to the complexities of geopolitical and information-driven markets.

Trust and safety expertise is particularly valuable in addressing challenges like attribution, cross-platform coordination, and harm mitigation. Professionals in this field routinely navigate jurisdictional differences, platform interoperability, and evolving threat landscapes capabilities that are directly relevant to prediction market governance.

As regulatory authority potentially becomes more fragmented (especially if courts shift oversight toward states) this expertise will become even more critical in ensuring consistent and effective enforcement.

Conclusion

Prediction markets are evolving rapidly, and the risks they introduce are not theoretical—they are already materializing across industries and geographies. As these platforms grow, so too does the need for a robust integrity framework that goes beyond traditional models borrowed from sports betting.

The next step is clear. Platforms, regulators, and organizations should begin establishing dedicated “prediction market integrity” roles, integrating trust and safety expertise into their governance structures. The CFTC should expand its focus on integrity partners beyond sports markets to encompass the full spectrum of event-based trading.

At the same time, the trust and safety community must engage with this emerging domain, building familiarity with prediction markets and contributing to their development from the outset. Incorporating these issues into professional forums and industry discussions will be essential. The window to shape this ecosystem for the safety of the free world is still open but it will not remain so for long.