Real estate has never been more attractive to fund managers. But without better data infrastructure, the sector risks squandering a golden opportunity. In this article, Marc Harris, Head of Real Assets, EU&ME at Vistra Fund Solutions, discusses how firms can overcome fragmented data to unlock investment in the real estate sector.
Over the past decade, real estate has steadily cemented itself as a cornerstone asset class for fund managers seeking diversification, inflation protection and long-term yields. Institutional allocations have grown, and the range of sub-sectors has expanded to include logistics, data centres and even life sciences. The global real estate deal value reached $873 billion last year, up 12% from the previous year.
However, as real estate deal sizes and volumes grow, so too does the complexity of managing investments well. To achieve this, improving the quality and consistency of data is the key challenge.
‘Location, location, location’ has been replaced with ‘location, data and technology’. GPs clinging to old ways of operating are missing key opportunities and, ultimately, may struggle to fundraise and scale their businesses.
Data matters more than ever
From our position administering funds across multiple jurisdictions, we see the consequences of fragmented data every day. Property valuations arrive in different formats from different valuers in each country. Rent roll data cannot be aggregated because every asset manager structures it differently. Capital call calculations that should take hours take days because the underlying investor and asset data sit in disconnected systems. That level of operational friction is a structural barrier to scaling a real estate platform.
The importance of data does not stop at acquisition. Investors need it to conduct due diligence, satisfy AML requirements, comply with regulatory reporting obligations and stay informed throughout the life of a fund. LPs increasingly expect transparent reporting across their investments in close to real time. To build trust, managers need to get data transparency right.
The scale of the problem is striking, and they lead to more than just marginal inefficiencies. Our recent industry research[1] shows that 64% of GPs have abandoned strategies or halted fundraising due to poor data quality. Within the EU, that figure rises to 82%. This represents significant levels of capital left on the table and real opportunities lost.
The fragmentation problem
The core of the issue comes down to unstructured and fragmented data. Fund managers handle data from a wide variety of sources and channels. Crucially, this data is all presented in differing formats, including Excel sheets, emails, multiple investment platforms and even PDFs. All this needs to be processed, reconciled and distributed back out to investors. At every step of that chain, there are opportunities for error, inconsistency and delay.
For managers operating globally, the challenge is compounded further, as different jurisdictions carry different rules and compliance frameworks. Meanwhile, many managers still rely on manually managed spreadsheets as a primary tool for data management. When the systems underpinning data are inadequate, the fragmentation problem worsens.
Legacy systems and siloed software all create their own reconciliation headaches. When a fund manager operates across multiple geographies and relies on several external service providers, each running their own systems, the potential for inconsistency multiplies. Standardising the data behind all these operating systems underpins the implementation of automation and analytics, in turn unlocking better valuation models and scenario stress testing. This vastly reduces the amount of manual work that fund managers are left with, while also cutting back on errors, giving them more confidence in the data they use to make strong investment decisions.
Charting a path forward
The regulatory environment is also raising the bar. AIFMD II, now being transposed across EU member states, brings enhanced reporting obligations including expanded Annex IV disclosures, more granular liquidity reporting and additional requirements around delegation oversight. Managers who have not already invested in their data infrastructure will find compliance with these expanded obligations significantly more costly and resource-intensive.
Fortunately, technology is providing solutions. Across the real estate sector, data standards led by industry bodies and a renewed focus on data governance are gaining traction. Pinning down common data standards is the crucial piece of the puzzle if insights are to be compared or aggregated reliably across firms and portfolios. Indeed, a lack of standardisation is the third-biggest barrier to using data more effectively.
Managers serious about addressing this must start with a data audit. You must identify where data gaps and inefficiencies exist before you can fix them. From there, change needs to be implemented in a structured, staged way across the entire fund ecosystem, covering people, processes and technology in equal measure. Modern platforms and embedded technology solutions can then bring it all together.
Artificial intelligence must also be used with caution. The excitement about AI’s potential to generate gains in real estate investing is understandable. We are already seeing practical applications: automated reconciliation of property valuations across portfolios, anomaly detection in rent collection data, and predictive modelling for lease expiry risk. But each of these use cases depends entirely on clean, standardised, well-governed data flowing through the system. Without that foundation, AI simply automates and scales existing errors.
Human judgment remains essential. AI can surface patterns and flag inconsistencies at speed, but the investment decision, the regulatory sign-off and the client relationship still require experienced professionals who understand the context behind the numbers.
Positioning for an AI future
In the coming years, data and broader technology will become pivotal for funds ramping up activity in real estate. Success in the next cycle will hinge on mastering data architecture and ensuring robust operational standards are in place so that bold, AI-driven decisions can be made with confidence.
Fund managers that bolster their data infrastructure now are positioning themselves to take full advantage of AI tools as they mature. This will enable more seamless investment decision-making, regulatory confidence and scalable growth.
[1] Report: Data at the Crossroads: https://www.vistra.com/vfs-global-real-estate-report
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