Data quality in the era of SFDR 2.0 and GRESB

Ensuring high quality ESG data for real assets remains complex and burdensome, particularly for fund-level ESG reporting. Achieving reliable reporting is often challenging due to several factors:

• A wide variety of systems used to collect data across real assets located in multiple countries
• Data frequently reported manually, leading to errors and inconsistencies that require significant time and effort to verify and correct
• Data often collected with delays, or sometimes too late, requiring the use of proxies whose quality may vary
• Different reporting timelines across frameworks, such as GRESB (May–June) and financial and regulatory reporting including the EU Sustainable Finance Disclosure Regulation (SFDR), which typically occurs earlier in the year (February–March)
• Limited collaboration from tenants, who are often slow or reluctant to share data
• Analytical reviews not supported by adequate methodologies to explain outliers, significant variations, or unusual trends
• Unclear ownership roles and insufficiently defined data collection frequencies

As sustainable finance continues to mature, data quality has become not only a critical enabler but also a bottleneck for credible ESG reporting. Regulatory and voluntary frameworks, particularly the SFDR and GRESB, are undergoing major changes that place greater emphasis on accurate and consistent sustainability data supported by well‑defined methodologies. As a result, ESG data quality is no longer a “nice‑to‑have”: it becomes a regulatory requirement and a competitive necessity.

While SFDR 1.0 set up the path towards sustainable finance through a  disclosure-based regime, with the publication of the SFDR 2.0 proposal on November 20, 2025, the European Commission signaled a shift away from the disclosure‑heavy regime of SFDR 1.0—often characterized by extensive narrative information—towards a framework centered on standardized  data, robust metrics, and documented methodologies. The key elements of the SFDR 2.0 include:

• Introduction of three product categories with strict eligibility criteria with minimum measurable thresholds including a transition category which is very relevant for real estate
• Adoption of a shortened and standardized two‑page format of pre‑contractual and periodic disclosure, placing greater emphasis on robust underlying data rather than lengthy narrative explanations supported by weaker datasets
• Mandatory application of EU Paris-aligned benchmark exclusions across the three product categories

Several ESG metrics in the real assets sector rely heavily on scientific, engineering-based, or forward‑looking assessments. Examples include:

• Scope 1, 2, and especially Scope 3 emissions calculations, which depend on estimates and quality of the underlying source data
• Climate scenario analysis and climate-related risk modeling, covering physical and transition risks
• Biodiversity, water impacts, social metrics, and embodied carbon

Such indicators depend on methodological choices and estimates, not simply recorded facts.

Recital 24 of the SFDR 2.0 proposal highlights the inherent complexity of the subject: “The wide range of potential investable assets for financial products that can be categorized as sustainably‑related financial products means that there will continue to be certain data gaps in relation to sustainability data from investees and other assets.”

This is further addressed in Article 12a(a)(ii) of the SFDR 2.0, which is new compared with SFDR 1.0, and introduces the following requirement: “the use of estimates that are not based on data provided by external data providers is based on formalized and documented methodologies.”

A robust methodology ensures consistent definitions, boundaries, and calculation rules, making ESG metrics comparable across real assets and across years. To achieve such robustness, third-party ESG assurance plays an important, and increasingly necessary, role by strengthening methodologies and enhancing stakeholder confidence in how ESG metrics are collected and derived.

Auditors currently provide only limited assurance on ESG data because the ESG reporting landscape lacks the mature, stable, and standardized framework that underpins an auditors’ report on financial statements.

Financial accounting data comes from controlled systems with double-entry bookkeeping, strong and mature internal controls, robust audit trails, and regulatory frameworks that ensure accuracy and completeness.

In contrast, ESG data often:

• Comes from multiple systems, spreadsheets, and external sources (e.g. utilities, contractors, tenants)
• Relies on non-harmonized estimates, modeling assumptions, and proxies
• Is often collected outside financial control environments
• Lacks robust historical records, governance, and IT integration

In the absence of a mature system of collecting ESG data associated with a strong control environment and harmonized measurement methods (e.g. EPC ratings), and internationally recognized standards (e.g. GHG emission protocols), reasonable assurance is not yet feasible.

Based on our experience of conducting external assurance on ESG data for a wide range of real‑asset financial products, we recommend the following actions to enhance data quality:

• Define clear lines of responsibility for data collection and ownership in a governance policy
• Review methodologies to ensure appropriate approaches to estimations, proxies, thresholds, exception handling, back‑testing, and error metrics
• Increase the use of technology to automate data collection
• Provide training to data contributors to build understanding of the importance of consistent, high‑quality data and to raise awareness of new regulatory requirements
• Maintain adequate audit trails so that data is reliable and accessible when requested by investors, supervisory authorities and/or internal/external auditors
• Use real‑time analytics and predictive models to support continuous monitoring and early detection of trends and outliers
• Improve the harmonization of datasets across frameworks (GRESB, SFDR, TCFD) despite the different timelines to minimize discrepancies and ensure consistency
• Extend the use of external assurance providers who can support you with additional comfort over the quality of ESG data through:
  • A review of tools, methodologies, and control frameworks
  • An assessment of your organization’s readiness for current and upcoming regulations and best market practices
  • A provision of recommendations on data governance, internal controls, and overall documentation, including those related to IT systems

This article was written by Geoffroy Marcassoli, EMEA ESG Asset & Wealth Management Leader, and Robert Castelein, Managing Director – MRICS, at PwC Luxembourg. Learn more about PwC Luxemburg here.