Webinar Recap: Cracking Private Market Data Complexity

Private markets have become a core part of institutional portfolios. As allocations continue to grow, firms face a challenge that many know well: the data infrastructure supporting private markets has not evolved at the same pace. 

In a recent webinar, Rimes and Liqueo explored how investment teams can address this challenge, what AI can realistically deliver, and what successful modernization looks like in practice. 

The Challenge Is Structural 

A live audience poll revealed that most firms still operate in fragmented data environments. Manual processes, disconnected systems, and inconsistent reporting formats remain significant obstacles. 

As Yamelin Castillo, Director of Private Markets at Liqueo, put it: “The human has become the integration layer.” 

Capital calls, distributions, valuations, and performance metrics arrive from different managers in different formats, forcing teams to spend valuable time reconciling data instead of analyzing it. 

Neil Naidoo, Head of Investment Intelligence at Rimes, emphasized that solving the problem requires more than adding another dataset or platform. “You have to think about it in terms of the data ecosystem you are creating. How robust and well-formed it is to manage hygiene, lineage, and how data flows through your organization.” 

The firms making the most progress are building around a total portfolio view, where public and private assets are managed together through a governed, trusted data foundation. 

AI Depends on the Foundation Beneath It 

AI was a major topic throughout the discussion, but both speakers agreed on a simple truth: AI amplifies whatever data it is given. “If we have issues with that data, AI amplifies the problem. But it can also amplify the good side of it, if we have trusted, normalized, and contextualized data,” said Castillo. 

The opportunity is not to layer AI onto fragmented processes. It is to establish a governed data foundation first, then use AI to support portfolio monitoring, reporting, analytics, and operational workflows. For investment teams, becoming AI-ready starts with data quality, governance, and transparency. 

Modernization Is an Operating Model Question 

Many modernization efforts fail because they are approached as technology projects rather than operating model transformations. Organizations often discover data ownership, governance, and quality issues only after implementation begins. 

The answer is not necessarily fewer systems. According to Castillo, most firms need a stronger architecture layer that connects existing platforms, normalizes data, and delivers a consistent view across the portfolio. 

As demand for a true total portfolio view continues to grow, integration and governance matter more than wholesale replacement. 

Where Rimes Fits 

Rimes provides the trusted data layer that helps investment organizations govern, normalize, and distribute complex private markets data at scale. 

By reducing operational friction and improving confidence in data, firms can spend less time managing information and more time making investment decisions. 

To learn more, contact the Rimes team today.