Prediction markets are scaling at a massive pace right now that has surprised analysts and traders alike. However, despite the momentum being in their favor, the industry has a glaring problem that is not even close to being solved today.
But first, let us look at some figures. Major prediction markets like Polymarket and Kalshi posted a combined monthly trading volume of under $5 billion back in September 2025. However, within 7 months, the volume had exploded to roughly $24 billion by April 2026, based on a Pew Research Center analysis of data from The Block.
Just a year or so ago, the emerging sector was seen as yet another extension of the betting economy, but the sector quickly collected more than $63 billion in total volume across 2025 alone, while at the same time, American sports betting remained flat around the $14 billion monthly figure. The figure for 2026 is expected to be even bigger than that, and now we have to acknowledge that this is an entirely new disruptive sector, not just the reimagining of online gambling.
While the growth of these contract-based markets is phenomenal, cracks are starting to emerge from within the ecosystem. The entire purpose of a prediction-based approach is to tell the truth, and the price of the contract shows the crowd’s honest take regarding the outcome. However, the faster these platforms continue to scale, the faster the problems are starting to appear from them.
The promise of a true prediction market.
Despite the rapid ongoing development and decentralized contracts, prediction markets, at their core, are a simple idea rooted in history. They trace their roots to the 19th-century Wall Street election betting and the more recent University of Iowa’s electronic markets from 1988.
Quite simply, participants buy and sell contracts valued between $0 and $1. If a certain event’s outcome goes a specific way, the contract settles at $1, and if it doesn’t, the contract settles at $0. The overall probability estimate drives the prediction markets.
There are two conditions why these prediction markets are being embedded by Google and often used as benchmarks for trading: firstly, the trades have to be real and not fraudulent, where one party can potentially run away after making a bad bet, and secondly, the event’s outcome needs to be settled fairly without any foul play.
If either one of these basic conditions isn’t met, it will result in chaos, and the system will become meaningless. Given the success of these prediction platforms like Polymarket and Kalshi, it would appear that these basic requirements are protected. However, upon closer inspection, it doesn’t appear to be so.
Trust cracks keep showing everywhere
While cases against Polymarket and Kalshi remain commonplace, a recent June 2026 case against the former has grabbed headlines. The case was filed by the National Association of Consumer Advocates in the Superior Court of the District of Columbia. The lawsuit alleges that Polymarket paid influencers money to appear to place and win major bets on a simulated version of the platform while they advertised the situation as organic trades.
To their credit, Polymarket has stated that it is reviewing its promotional activity and will address it wherever necessary. However, if these allegations are true, they go against the first pillar of prediction contracts, as the platform is promoting paid/fake trades as real activity.
The troubles of these overly centralized prediction outlets don’t end here. Kalshi, another major player, was sued by Nevada gaming regulators in February 2026 and by the Arizona Attorney General in March 2026, in disputes centered on how its products are classified and whether they amount to unlicensed gambling.
As problems mount for these aggressively expanding outlets, they are looking to straighten their act. On March 23, 2026, both Kalshi and Polymarket publicly announced new measures to discourage insider trading through integrity controls, which is another major scourge on these platforms.
But Who Decides the Outcome?
While the two major prediction platforms are engaged in damage control, the fundamental engineering problem remains unaddressed: who passes the judgment? As long as an objective way to establish the outcome remains unaddressed, trust will remain elusive.
Prediction markets live and die on the resolution side of things. There are tangible results, like which team won, that are easier to manage. However, more difficult questions like “Did the government implement a certain policy?” require judgment and a resolution. Whoever has the capacity to make this judgment has incredible power, and currently, major platforms are heavily centralized, meaning they make the decisions themselves.
This is the problem that the next-generation prediction platforms are fixated on right now. They are racing to engineer a solution to this problem, and that is where things get interesting.
Opinion Labs is currently working to address this challenge by using cryptography and zero-knowledge-based verification for its settlements, through a partnership with Brevis announced in December 2025. The idea is to make things verifiable independently and transparently, rather than having to take the word of the platform alone.
While this is a useful approach, other platforms are focusing on the creation of these markets and the resolution side of things because it cannot be fair without both of them. Rain Trade allows users from all backgrounds, languages, and locations to create prediction markets rather than allowing a centralized control mechanism to dictate the proceedings.
According to the platform, it employs a hybrid regime to determine the outcome fairly. For objective events, such as sports outcomes, elections, and other objective results, AI can be used, while outcomes requiring a lot more nuance or human judgment can be resolved with a manual approach. Trades are settled in USDT, with the platform handling bridging and conversion automatically.
However, community creation and trust are challenges that are built over time. There is no magic fix for this problem, as history shows us.
Why this matters for the future
This is the perfect time to come up with an effective solution. The 2026 FIFA World Cup has already resulted in a massive spike in prediction-based trading activity, with as much as $2.5 billion reportedly targeted in industry estimates. While an avalanche of new users is entering these markets, legal issues remain for the established platforms.
The problem faced by developers is that prediction markets have scaled faster than integrity infrastructure, and as a result, we are stuck in dangerous territory. The success story for years to come will not belong to platforms with the shrewd influencer campaigns, but to those that can objectively verify and solve the two fundamental problems facing us: the activity has to be real, and the outcome has to be objectively ascertained.
Making prediction market contracts is easy enough. Trust is not. The interesting question is who is actually building their platform around it, and who is just spending on influencer campaigns and riding on popularity alone.