In recent research, 92% of senior private markets fund of funds professions surveyed across the UK, Europe and the U.S. said that “unstructured and delayed GP data had negatively affected investment decisions or reporting”. The findings from the 2025 Accelex/Carta report The Hidden Cost of Growth: Data Challenges for Fund-of-Funds, also found among those surveyed that the biggest source of friction was how GPs deliver information, with 31% citing unstructured formats and inconsistent delivery methods such as PDFs, emails and scanned files as their “number one pain point”. Operationally this matters to fund of funds (FoF) managers because those surveyed also noted that their teams spend around one-third of their time on data wrangling rather than value-add activities, which means a lot of what LPs think of as inadequate service is often a data collection and collation problem.
Fund of funds have always offered investors a practical route to diversification across managers, vintages, strategies and geographies, opening access to opportunities that are hard to source directly. The structure is particularly effective in segments such as small- and mid-market funds as a vehicle for broader participation and diversified exposure. Preqin’s research shows that diversification was the top reason LPs allocated to most private markets asset classes in its June 2025 survey, and McKinsey reports that LPs still intend to allocate more capital to private markets over the coming year.
For fund of funds managers though, beyond the strain of finding the right managers to invest in, they too must manage the growing weight of information that sits behind those allocations. That is why the modern FoF platform has become a multi-layered reporting business that is dependent on underlying GPs for timely, accurate data; is expected to gather look-through information from portfolio companies; and is answerable to LPs who want fast, granular reporting.
From our experience as FoFs and secondaries proliferate, managers are working to ensure they have a single source of truth for all the data layers. It is an operational necessity to be able to efficiently extract and collate information across both the underlying funds and the portfolio companies those funds invest in, and gaining quick access to all these layers of data is critical for risk oversight, portfolio analysis and investor communication. That is why solving how to manage vast amounts of information at scale is paramount.
Beyond investor requirements, Preqin’s historical benchmark data shows that fund of funds managers also need clean data to more effectively identify and monitor the best performing managers to invest in. To do this they need to gather and interpret large amounts of disparate data over a long period of time, further raising the operating burden for managers.
This means for both managers and their investors operational capability is part of the value proposition, especially as investors are also asking more detailed questions and are less willing to accept opaque answers. In the Private Funds CFO Insights Survey 2026, 49% of respondents said LPs’ questions on data and data management are “very detailed”, and 58% said the same for accounting procedures, underlining how closely operational reporting is now being examined. In practical terms this makes reporting part of the product, particularly as private markets products diversify and investor expectations move closer to public-market standards.
First, the strongest FoF managers treat data as a core operating capability, building a controlled data backbone that links source documents, fund accounting records and reporting outputs, which gives them a traceable “single source of truth”. As S&P Global notes, the industry’s “great data chain problem” is fundamentally about fragmented systems that prevent firms from seeing the whole picture. Fund of funds managers feel that problem directly, managing data from 100s of GPs and their underlying portfolio companies.
Second, they automate the point of greatest friction: data ingestion and standardisation. That matters because one of the most persistent drag factors in FoF operations is collection and technology is able to remove this. Aztec’s fund of funds research points to artificial intelligence (AI) including Large Language Models (LLM), Optical Character Recognition (OCR), Natural Language Processing (NLP) and Application Programming Interfaces (APIs) as practical tools for obtaining documents from various sources and turning them into reportable
A simple hypothetical example shows the difference. Imagine a fund of funds manager invested across 250 underlying GPs, each sending quarterly reports in different formats and on different timetables. Without a structured ingestion tool, the manager’s team can end up spending weeks manually collecting documents into spreadsheets and checking for inconsistencies before any analysis even begins. A tool that incorporates a suite of ingestion tools can help absorb that complexity at source by extracting the relevant data, mapping it into a consistent structure and flagging exceptions for review. This dramatically reduces the administrative burden, giving managers access to a faster usable view across hundreds of GP relationships.
Third, best practice still depends on human judgement because though automation can accelerate extraction and first-pass mapping, it cannot replace specialist review. The best operating models combine system-led efficiency with oversight expertise to challenge anomalies, interpret edge cases and preserve governance around the final output. That is one reason why the role of the specialist fund administrator is expanding rather than shrinking. In the Private Funds CFO Insights Survey 2026, 43% of firms said they expect to increase outsourcing of fund accounting over the next 12 months, pointing to sustained reliance on specialist providers as operational demands grow.
Fourth, leading managers are designing their reporting model around look-through transparency from the outset to help investors understand sector concentration, geographic exposure, portfolio company performance, ESG alignment and the real drivers of returns beneath the headline NAV. This means fund of funds managers are being judged not just on who they back, but on how well they can explain what sits underneath.
All of this has direct implications for the kind of support fund of funds managers need from a fund administrator. They need a partner that understands the multi-layered nature of the structure and can keep capital flows, communications, reporting and compliance aligned across each layer. The operational challenge goes beyond volume, it is orchestration.
For FoF managers trying to scale, the real value of an administrator lies in consolidation, normalisation and the reduction of operational drag. That, ultimately, is where the conversation becomes more strategic. In today’s market, the differentiator for fund of funds managers is the ability to operationalise diversification, which means gathering data from disparate sources, converting it into consistent insight, and delivering reporting that stands up to investor scrutiny. The managers that do this well will meet LP expectations, make better portfolio decisions and scale in a more streamlined way.
From our experience working with a selection of fund of funds managers success is built by combining technology that can automate the collation, extraction and standardisation of both fund-level and portfolio company data, with the human validation around the output.
Aztec Group is at the forefront of technology designed to “simplify scale” and help fund of funds managers better manage data volume, while incorporating the composition and performance of portfolio companies.
Powered by AI, our end-to-end data management solution, Aztec Xtract, automates the collation, extraction, and standardisation of fund and portfolio company data for fund of funds structures.
To learn more about how we’re supporting fund of funds managers with their data management and broader operational requirements, please contact us directly.
