As brokers experiment with prediction markets, attention is shifting from product rollout to how these products fit into broader client acquisition efforts. In that context, prediction markets are increasingly viewed as an acquisition channel rather than just another trading product.
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According to Yossi Tamir, Head of Business Development at Leverate, event-based trading is attracting a type of user that traditional CFD products often struggle to reach.
A New Entry Point for Retail Traders
Prediction markets are bringing in users who would not typically engage with traditional trading products. According to Tamir, the demographic entering retail trading over the past few years discovered financial markets through a completely different door of event-based platforms covering sport, politics, economics, and entertainment.
Effectively, prediction markets became an entry point for a significant portion of the next generation of retail traders and offered brokers an opportunity to attract a demographic their existing product catalogue simply couldn’t reach.
«The strategic value wasn’t just a new revenue line; it was a new acquisition channel that could route high-intent users into a broader product suite», Tamir added. «That combination of demographic tailwinds and broker-level commercial logic made it the right moment to build».
How Prediction Markets Differ from CFDs and Derivatives
From a technology perspective, event-based markets may become a challenge for a traditional broker. As Tamir explains, prediction markets differ from CFDs and derivatives more fundamentally than many brokers initially expect.
«With CFDs or FX, you have continuous price discovery driven by deep, established liquidity pools. The infrastructure challenge is execution speed, spread management, and routing. With prediction markets, you’re creating markets around discrete events, often with thin early liquidity, and the pricing engine has to hold its integrity from the very first trade, before any meaningful order flow exists».
To address this, Leverate uses a hybrid AMM model that combines LMSR pricing with Central Limit Order Book execution. This combination helps mitigate erratic pricing and avoid loss of confidence among traders.
Apart from that, Tamir pointed out that prediction markets have a defined resolution event, which requires automated settlement logic, compliance audit trails, and protection against manipulation around the resolution window.
«That’s a fundamentally different operational challenge from managing a continuously rolling CFD book», he added.
Why Brokers See Commercial Potential in Prediction Markets
According to Tamir, brokers that launched prediction market products are already seeing stronger retention driven by open positions and pending outcomes that keep traders returning to the platform.
At the same time, prediction markets generate additional spread and fee revenue with relatively low operational overhead once the infrastructure is deployed.
However, Tamir argues that the stronger commercial argument is user acquisition rather than direct monetization. Prediction markets attract audiences that traditional CFD campaigns often fail to reach, including sports fans, crypto-native users, and politically engaged traders.
«When a broker acquires one of those users through a prediction markets product, they’re starting a relationship with someone who has demonstrated they’re comfortable with risk, comfortable with digital platforms, and willing to engage with market outcomes».
According to Tamir, brokers that moved early into the segment are already building communities around event-based products and converting part of that audience into multi-product clients.
«The cross-sell path into traditional instruments is real and measurable», he added. «That’s the commercial flywheel that makes this genuinely strategic rather than just a line extension».
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Build vs Buy: Why Brokers Choose White-Label Solutions
Tamir argues that the infrastructure requirements behind prediction markets make the build-versus-buy decision even more tilted toward white-label solutions than in traditional trading infrastructure.
According to him, developing a pricing engine capable of handling thin liquidity, automated resolution, fraud protection, and real-time rebalancing can take more than eighteen months of engineering work before even considering the front-end or admin layer.
«Most brokers don’t have that development capacity or that timeline», he said. Tamir noted that brokers exploring internal development often discover that the core pricing and liquidity problem is significantly more difficult than expected.
As a result, many eventually move toward white-label infrastructure while still wanting full ownership over branding and client relationships. «Brokers don’t want to send their clients somewhere else; they want to own the relationship and the experience end-to-end».
The platform also supports custom event creation alongside external liquidity feeds through API integrations. According to Tamir, this hybrid model gives brokers access to externally sourced event markets while still allowing them to launch localized or niche markets unavailable through standard liquidity providers.
Tamir cited one example of a broker creating localized event contracts tied to African political and economic developments that were unavailable through standard liquidity providers.
Prediction Markets vs Binary Options
Tamir acknowledges that prediction markets are frequently compared with binary options because both rely on binary outcomes. However, he argues that the key distinction lies not in the binary payoff itself, but in the market structure behind it.
Binary options in retail FX drew regulatory scrutiny because of opaque pricing, conflicts of interest, and models where brokers effectively acted against the client. Prediction markets, by contrast, operate through exchange-based structures where participants trade against each other rather than against the platform itself.
«Pricing is determined by participant activity, LMSR ensures fair value, and resolution is tied to verifiable real-world events rather than synthetic price levels», he said.
Tamir also stressed that compliance infrastructure became a core part of prediction market platforms as the sector matured. Leverate’s system includes KYC and AML integration, transaction monitoring, audit logging, and configurable compliance controls designed to match local regulatory requirements.
He pointed to the US market as an example of growing institutional legitimacy around the segment. «In the US, for example, the CFTC has provided greater clarity on exchange-based prediction markets, and major regulated venues have launched event contracts. That’s been an important legitimising signal for the category globally».
At the same time, Tamir emphasized that Leverate positions itself as an infrastructure provider rather than a market operator. «We don’t make product decisions for them, but we make sure the platform supports responsible operation from day one».
