Prediction Markets Surge to $64 Billion Amid Centralization Risks
By John Nada·Feb 11, 2026·6 min read
Prediction markets soared to $64 billion in 2025, but centralization poses significant security risks. The sector's integrity issues could impact institutional adoption.
Prediction markets surged to $63.5 billion in annual trading volume in 2025, marking a fourfold increase from 2024, according to a report by blockchain security firm CertiK. This growth was driven by a few dominant platforms consolidating control over the sector, which is evolving into an institutional-scale product. Notably, the elevated activity persisted beyond the US election cycle and into January 2026, indicating that trading behaviors may have shifted from sporadic spikes to more sustainable patterns of user engagement.
The total volume rose significantly from $15.8 billion in 2024 to $63.5 billion in 2025. This dramatic rise in trading volume reflects a growing acceptance of prediction markets, moving them from a niche sector to a high-turnover trading venue. The week ending January 18, 2026, set a record of about $6 billion in notional volume, underscoring the quick transition of prediction markets into mainstream financial discussions.
However, CertiK cautions that this rapid expansion is colliding with critical integrity issues. Currently, three platforms dominate more than 95% of the global prediction market volume, each pursuing different paths to market leadership. Kalshi operates as a regulated venue in the US, positioning itself as the compliance-first model. Polymarket caters to crypto-native users and international participants, while Opinion has quickly scaled its market share to about 30% through aggressive ecosystem incentives. This concentration in the market introduces systemic risks; a failure at one of these venues could lead to widespread trust issues affecting liquidity pools and user balances across the board.
A notable incident in December 2025 highlighted these vulnerabilities when accounts using centralized login methods were compromised, putting user funds at risk while the on-chain settlement layer remained secure. CertiK characterized this incident as an identity failure rather than a settlement failure, underscoring the dangers of relying on centralized authentication methods in a sector that promotes decentralization. The trade-off between user experience and security illustrates the uncomfortable reality for an industry that markets itself on decentralization.
As prediction markets gain traction, the reliance on Web2-style onboarding could expose users to risks similar to those found in traditional finance, where centralized points of failure can lead to significant losses. The report indicates that prediction markets can support fully collateralized on-chain settlements while still retaining the same third-party risks that plague conventional fintech, such as account recovery and platform-level access controls.
The report also differentiates between trading volume as a measure of adoption and probability outputs as indicators of information quality. CertiK found that while incentive programs may inflate trading activity, they do not necessarily enhance the accuracy of forecasting signals. For example, wash trading remains widespread, with estimates suggesting that artificial volume reached as high as 60% on some platforms during peak airdrop-farming periods. This prevalence could mislead institutional users regarding the depth of liquidity and organic participation within the markets.
Although wash trading has inflated volume metrics, CertiK argues that price accuracy has not yet been compromised. Probability outputs have remained reliable for forecasting, which creates a tension for market leaders who must balance short-term volume boosts against the long-term credibility needed to attract institutional capital. If distribution and credibility depend on information quality, platforms may need to become less tolerant of behaviors that drive volume but undermine the optics and trust essential for institutional investment.
Recent trends indicate a structural shift in how liquidity is executed in prediction markets. While Polygon maintained its legacy dominance during the November election cycle, BNB Chain's volume surged in late 2025, coinciding with Opinion's aggressive incentives. By mid-January 2026, BNB Chain captured the majority of weekly flows, signaling a potential shift in market dynamics and execution methods. This transition changes the participation landscape, trade clearing processes, and the viability of different market structures.
CertiK notes that many on-chain venues are evolving from automated market makers to central limit order books on high-throughput chains. This shift not only tightens spreads and aligns with familiar trading mechanics for professional traders but also introduces risks typically associated with centralized exchanges, such as front-running and transaction-ordering disadvantages on public networks. As prediction markets approach an exchange-like microstructure, these risks must be carefully managed to ensure the integrity of the trading environment.
Another significant concern lies in the resolution mechanisms that determine how probabilities translate into cash payouts. CertiK identifies oracle manipulation as the primary technical risk, as the methods for resolving market outcomes directly impact fund distribution. Disputes over ambiguous market definitions have already surfaced across major platforms, particularly in politically contested outcomes. CertiK outlines the different resolution models used by platforms, each bearing distinct trust assumptions that may complicate governance as prediction markets scale.
Polymarket is described as using UMA’s optimistic oracle, where outcomes resolve automatically unless disputed within a challenge window, leading to potential vulnerabilities. Kalshi employs centralized arbitration, relying on human arbiters to resolve outcomes based on authoritative sources, which while predictable, necessitates trust in the platform operator. Meanwhile, Opinion uses consensus oracles, where designated parties must agree on an outcome, which distributes authority but still depends on the incentives and integrity of the resolvers involved.
As prediction markets continue to evolve and integrate into mainstream finance, the implications of these structural challenges will become increasingly pronounced. The reliance on centralized login methods, the persistence of wash trading, and the risks associated with resolution mechanisms are areas that require critical examination. The industry's marketing of decentralization may face scrutiny if these vulnerabilities lead to significant market dislocations or governance crises. For prediction markets to successfully transition into an accepted part of financial decision-making, they must align their operational integrity with their advertised ethos of decentralization.
Ultimately, as prediction markets mature, it will be essential for stakeholders to address these fundamental challenges to foster a secure and credible environment for all market participants. The path forward will require not only innovation in technology and governance structures but also a commitment to transparency and accountability in operations. Only through such measures can the prediction market industry hope to regain and maintain the trust of users and institutional investors alike, ensuring its place in the broader financial ecosystem.