Prediction markets are growing fast, but the industry still has a major infrastructure problem. Talking with River Markets Co-Founder Oscar Levy made it clear that the next phase of the space may not only be about more users or more event contracts. It may be about building the serious trading infrastructure needed for larger firms to participate.
River Markets is positioning itself as a prime brokerage platform for prediction markets. In plain English, that means the company is trying to make it easier for institutions and professional traders to access liquidity, route orders, manage portfolios, and trade across multiple exchanges through a single system. River Markets' own documentation describes features such as liquidity aggregation, smart order routing, unified market IDs, and subaccounts for portfolio management.
Exclusive Interview With Oscar Levy
One thing that stood out from the conversation was how different River Markets feels from the retail-facing side of the industry. Most people hear the term' prediction market' and immediately think of Kalshi, Polymarket, or whatever political or sports contract is trending that day.
River Markets is focused more on the layer underneath that. The company is thinking about execution, liquidity, professional trading workflows, and how larger participants can interact with prediction markets more cleanly.
That is a very different part of the industry, but it may end up being one of the most important.
River Markets is Not Just Another Trading App
River Markets describes itself as "prime brokerage for prediction markets," which is a big clue about how the company sees the opportunity. This is not a consumer app built around casual users checking prices during a game or election night. It is more like an infrastructure layer for serious market participants.
The platform currently lists Kalshi and Polymarket as available supported exchanges, with Polymarket US, ForecastEx, and MIAXdx listed as coming soon. They explain that users can search for markets across supported exchanges, place orders via unified IDs, track positions in real time, and manage strategies via subaccounts.
That matters because prediction markets are still fragmented. A trader looking across multiple platforms has to deal with different interfaces, identifiers, collateral systems, and execution rules. River Markets is trying to smooth that out.
Why Institutions Need Better Market Plumbing
The institutional angle is where this gets especially interesting. If prediction markets are going to attract hedge funds, trading firms, asset managers, or other professional participants, the current setup probably isn't enough. Large firms usually need reliable execution, clean reporting, risk controls, and the ability to manage positions across venues.
They are not going to operate comfortably in a market structure that feels stitched together across separate apps and APIs. That is why River Markets prime brokerage framing makes sense. Traditional finance has spent decades building infrastructure around execution and access. Prediction markets are now starting to need their own version of that stack.
Levy's background as both a builder and market participant makes the story more interesting. River Markets is not approaching this from the outside. The company is clearly studying how these markets actually move, where inefficiencies appear, and what tools professional traders may need next.
AI Research is Also Part of the River Markets Story
River Markets is also publishing research on prediction market microstructure, execution, and quantitative trading strategies. Its research page says the company aims to bridge academic rigor with practical market infrastructure, which aligns with how Levy describes the space. One paper by Levy examines how LLMs can help filter for lead-lag relationships in prediction markets.
The research combines statistical methods with semantic analysis to identify relationships that make actual economic sense, rather than chasing fragile correlations. River Markets has also published work on mention markets, including research on how language models can help interpret company mentions during earnings calls. That is a fascinating corner of the industry because it shows how prediction markets, AI, and information analysis are increasingly overlapping.
The Trade Handle Prediction Markets Take
The biggest takeaway from speaking with Oscar Levy is that prediction markets are developing a real professional layer. The public side of the industry is still mostly about platforms, headlines, prices, and big legal fights. Underneath that, companies like River Markets are working on the infrastructure that could make prediction markets more usable for serious trading firms.
We think that is a major shift. Prediction markets are no longer just about whether more people open an app. The next stage may come down to whether the industry can build the plumbing needed for larger capital, smarter execution, and more sophisticated research.