Maltese Start-up Mrkts Launches B2B Prediction Market Infrastructure
The new offering allows businesses to integrate customized forecasting markets into their own platforms without building the underlying technology.
Maltese start-up Mrkts has launched a new infrastructure offering that enables businesses to integrate prediction markets directly into their own platforms. The move shifts the company's focus toward a B2B model, providing the technical foundation for other firms to deploy forecasting tools.
Developed by Malta-based Deep Ether Labs, the infrastructure allows companies to create customized markets where users trade on the outcomes of future events. According to FinTech Futures, the service is designed to democratize access to this technology, allowing businesses—such as High Roller—to deploy their own prediction markets without the need to build the complex underlying technology from scratch.
The Rise of Forecasting Markets
Prediction markets have seen a significant surge in popularity as tools for both forecasting and hedging. While the sector has historically been dominated by consumer-facing platforms, there is an increasing demand for white-label infrastructure. Enterprises are now seeking ways to leverage these markets for internal decision-making or as client-facing features, moving the technology beyond niche trading circles and into broader corporate applications.
Industry Implications
By positioning itself as an infrastructure provider rather than a direct-to-consumer platform, Mrkts is targeting the scalability of the prediction market industry. This shift potentially opens the door for a wider array of financial and non-financial institutions to utilize forecasting markets for risk management. By lowering the barrier to entry, the infrastructure allows firms to capture the collective intelligence of a crowd to better predict market shifts or operational risks.
Future Outlook
As Mrkts establishes itself as a B2B provider, the industry will be watching to see how widely these integrated markets are adopted across different sectors. While the technical foundation is now available, the success of the model depends on whether traditional enterprises are willing to trust market-based forecasting over traditional analytical methods. It remains to be seen which specific industries will be the earliest adopters of this white-label approach.