SOLVE, provider of pre-trade data and predictive pricing for fixed income markets, has acquired MBS Source, the data and trading solutions provider for the mortgage- and asset-backed securities (MBS/ABS) market. The acquisition, announced on October 16, 2025, aims to enhance SOLVE’s capabilities in the structured products space by integrating MBS Source’s specialised data and analytics into its multi-asset platform.
The move will provide clients of both firms with expanded tools and insights for buy- and sell-side institutions, allowing them to better analyse and act on fixed income opportunities. SOLVE’s CEO, Eugene Grinberg, notes that the acquisition was a natural fit, given the two companies’ shared foundation in AI-powered data curation and predictive analytics.“MBS Source is an asset class specialist focusing on securitised products, particularly agency mortgages,” Grinberg tells TradingTech Insight. “They built a quote database similar to what SOLVE has done, but went deeper, especially in agency mortgages. They also developed more advanced tools for transparency and analytics. These include a new issue monitor, allowing visibility into volumes and pricing for newly issued securitised products side by side with secondary markets, and predictive analytics for mortgages featuring both prepayment and pricing models. Furthermore, MBS Source built an enhanced TRACE feed. This acquisition allows us to bolster our securitised products coverage with additional data, predictive analytics, and workflow tools.”
SOLVE already provides coverage on more than 150,000 securities, with daily visibility into over 20,000 securities and over 120,000 quotes. The addition of MBS Source’s offerings – including predictive pricing for agencies, a predictive prepayment model, a “worst to deliver” product for TBAs, derived TRACE, and new issue capabilities – will expand this dataset with new analytics and trading functionality.
The shared focus on artificial intelligence was another key factor in the acquisition. “MBS Source’s use of AI in their products was another attractive feature,” Grinberg says. “SOLVE has a long history with AI, having built a homegrown NLP platform in 2011 to collect data from unstructured messages. Our predictive analytics model is also 100% AI-based, engineered with around 300 features, encompassing bond terms and conditions, quotes, and trade data, to predict levels at which trades should happen, specific to size and side of the trade. We were attracted to MBS Source because Mihai and his team use similar quantitative and machine learning techniques for data collection (on both the secondary and new issue sides) and for predictive analytics. Our thinking around the product roadmap is very much in line.”
Looking ahead, Grinberg says the immediate priority is to ensure a seamless transition for clients of both platforms. “Our product goal is to avoid customer disruption,” he explains. “For now, the SOLVE and MBS Source platforms will remain separate. Over time, we will simplify workflows and reduce screen count through interoperability, sharing data sets between both platforms. While the ultimate aim is a single platform, we are mindful that customers are creatures of habit and will be able to continue using the platform they are used to during the transition.”
The long-term vision is to leverage the combined data and analytics capabilities to provide clients with more advanced tools for portfolio management and idea generation. “Our immediate focus is building out predictive analytics,” Grinberg says. “This creates a foundational data set that allows us to price every bond in an asset class, whether it is actively traded or not. Now that we have this data, the next step – which is already underway – is building a suite of relative value and idea-generation tools. These tools will quickly assess if individual bonds or market cross-sections are rich or cheap compared to their history or their peers. This facilitates more active portfolio management, allowing PMs to perform seamless substitutions and capture additional alpha. We are building the platform to simultaneously feed data-hungry algorithms via APIs, while also supporting the buy-side and sell-side ecosystem with workflow and visualisation tools. These tools enhance their process, improve speed and efficiency, give them greater confidence in price formation, which ultimately means they are able to do more and maximise their P&L.”
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