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How ESG data markets have evolved for financial services

There are rapid changes transforming ESG data markets, driven by increased demand from financial institutions.

In brief

  • The ESG data market is evolving, to meet the increasing demand from financial institutions, their investors and to meet regulatory requirements.
  • Large vendors dominate the ESG data markets, but more specialized data providers are addressing the niche gaps that financial institutions require.
  • There are challenges and shortcomings in the quality of data available, and it’s likely multiple data providers will be required for the foreseeable future.

The ESG data market is growing in scale, sophistication and maturity. Increasing day-to-day usage by virtually all financial institutions means that the market is far larger than when last reviewed two years ago. ESG data providers generated revenues in excess of $1b in 2021, and this could rise to $1.3b in 20221.

Investor demand is a key driver of growth in the ESG data market. Financial institutions with strong ESG propositions are increasingly seen as enjoying a competitive advantage over their peers. This pull factor is reinforced by a strong push from regulation, which continues to actively shape ESG data markets. More institutions are falling within the scope of mandatory European disclosure rules, and emerging regulations in the US2 and Asia3 promise to stimulate demand in other markets. Asset managers are the heaviest spenders on ESG data, representing 59% of all buyers, followed by insurers and other institutional investors.

Europe’s ESG data markets are the world’s largest. Our assessment of the geographical coverage offered by data vendors reflects the maturity of the region’s available ESG data sets. European organizations account for 60% of global spending on ESG data4. Coverage in other markets is growing fast too, especially in the US where attitudes to sustainability have shifted significantly since 2020. The number of data providers offering some APAC coverage has also grown rapidly, although the breadth and depth of data is typically much lower than in Europe. ESG data markets in the Middle East and Latin America are relatively small.


ESG data markets are dominated by a handful of large vendors, followed by a second tier of close rivals and a long tail of smaller, more specialized data providers. Niche operators aiming to address specific gaps in data coverage continue to be launched, but these emerging providers are often acquired by larger incumbents aiming to become one-stop shops for their clients. This trend, if it continues, is likely to see the market’s long tail shorten as the industry matures.


The position of leading data providers is further strengthened by significant technology-related barriers to switching. Users regularly make small changes to their data suppliers, but wholesale changes are challenging. Typically, a large asset manager would need over a year to switch between core suppliers due to the difficulty of integrating multiple data types into core technology systems.

Coverage is improving, led by innovation

ESG data vendors continue to expand their asset class coverage. In the public markets, sovereign instruments and listed real estate vehicles are key growth areas. There is also expansion in private markets, although scarce data on SMEs means that availability is heavily concentrated on larger unlisted companies. Coverage of other alternative investments, such as land or real assets, is generally confined to specialized data providers.

The scope of ESG data coverage is broadening too, as investors look beyond climate and seek to address other environmental issues and social priorities. Biodiversity is one example of a nascent data category receiving growing attention from providers. The introduction of the new TNFD5 framework, currently in development, is likely to spur the availability of data and help investors to set nature positive targets.

ESG data providers are pursuing a range of innovative approaches. Larger firms often prefer to integrate new data sources into proven platforms — for example, by using existing estimation methodologies to develop biodiversity ratings. In contrast, niche players are more likely to experiment with new approaches and data. This might include using satellite data to monitor changes in land use, or applying machine learning tools to gather and analyze large volumes of unstructured data. However, novel data types can be hard for the users of data to incorporate into their own systems and decision-making.

Data quality is falling short of expectations

Despite the increasing availability of ESG data, ever-growing user expectations mean there are always gaps to be filled. Scope 3 emissions data is one area where the limitations of underlying disclosure leave data providers heavily reliant on interpretation and proxy metrics.

As explored in EY’s article “How to realize the full potential of ESG+”, there needs to be a stronger connection between financials and ESG – “FESG” – where data supports businesses in using ESG data to inform strategic choices, drive innovation and create long-term value. 

More fundamentally, many users remain dissatisfied with quality of ESG scores. When asked about the limitations of ESG data, shortcomings in comparability and consistency accounted for four of data purchasers’ top six concerns (see table). These concerns are illustrated by the fact that different data providers can generate starkly contrasting ratings of the same companies. For example, one study found a correlation of just 0.61 for ESG ratings, compared to more than 0.95 for credit ratings6 .

Some users take the view that contrasting ratings from different data providers allow them to explore different perspectives and build an informed picture. However, others see potential for investment outcomes to be negatively impacted. Some commentators see a risk of users being able to “pick and choose” the rating that suits them, rather than reaching the best decision for investors.


Inconsistent ratings reflect several structural weaknesses in ESG data. A lack of harmonization between jurisdictions, not to mention the incompleteness of crucial taxonomies, can lead to huge inconsistencies in the corporate disclosures that ESG data vendors use to create their scores and ratings.

Reliance on company disclosures for data collection can also lead to selectivity and interpretation bias, as well as favoring the ESG scores of larger companies which can allocate the greatest resources to corporate reporting and engagement with ratings providers. Media reports are increasingly being used to validate formal disclosures and spot potential controversies, but media sources pose their own challenges around reliability and judgment.

Different approaches are another factor. The ESG data spectrum is so broad that data providers often place contrasting levels of focus on different categories of E, S and G disclosures. Overall, investors are often left with a low level of confidence about using ESG ratings for investment decision-making.

Users face growing costs and risks from ESG data

Shortcomings in the reliability of ESG data have major implications for users. Most obviously, many financial institutions feel unable to rely on a single data provider (see graph). However, a blended approach based on multiple data vendors not only duplicates external costs, but also necessitates in-house spending to analyze, compare and curate ESG data. In fact, many larger users of ESG data now have their own ratings teams providing proprietary scores that draw on a range of third-party data sets.


More broadly, the lack of consistency, standardization and independent assurance undermines the credibility of ESG data markets as a whole. This is a growing concern, given the increasing costs of compliance failures and the threat from damaging allegations of greenwashing – as illustrated by a number of recent regulatory fines and high-profile resignations at major financial institutions7.


These concerns are fuelling appetite for regulation – especially of leading data vendors. In April 2022, the European Commission published a consultation on ESG ratings that will feed into an impact assessment of a possible EU intervention into ESG data markets. In a recent feedback statement, the UK’s FCA also cited a “clear rationale” for regulatory oversight of ESG data and rating providers.


Robust data management is increasingly important


Many buyers of ESG data could use it more efficiently and effectively. One common problem is that many different activities require ESG data, including regulatory reporting such as SFDR disclosures, financial reporting, portfolio management, stress testing, strategic planning and procurement. Without central coordination, firms can acquire multiple ESG data licenses in a haphazard way. Apart from the excessive costs incurred, this can also lead to confusion over data management and access.


Excessive costs are not the only problem. Many firms are also failing to extract full value from the data they have purchased. That is partly about failing to use all the data that’s available to licensees, and partly about failing to identify all of the potential applications for that data within the business.


Finally, the relative novelty of ESG data means that operations and governance can sometimes be weak. A lack of suitable technology, data professionals and oversight can lead to overreliance on manual processing, an absence of effective data validation, information silos and a loss of version control – all of which breed inefficiencies and confusion.


In response, use of strategic data management is increasing. There is clear scope for firms to cut costs and increase benefits by integrating ESG data into enterprise-wide data management strategies. After all, ESG data is increasingly being used alongside conventional financial disclosures as part of investment decision-making and for a range of client and regulatory reporting.


Looking ahead

ESG data markets are more dynamic than ever. Data coverage and categories are advancing rapidly, but there are still many gaps, questions and inconsistencies to be addressed. Quality does not always keep up with quantity.


These shortcomings will take time to address, and vendors cannot solve every problem. Even so, innovation from industry leaders and new entrants will continue to drive improvement. We are starting to see movement towards collaboration on industry platforms. Besides privately led initiatives to develop open-source platforms to exchange ESG data in a harmonized way, we also see regulators like the EU Commission pushing forward with their plan to launch the European Single Access Point (ESAP). ESAP is intended to act as a direct access point for obtaining ESG and financial company data in machine-readable form. Companies would be asked to provide annual financial statements and management reports and, once CSRD comes into effect, sustainability reports including detailed information on the EU Taxonomy. The proposal also opens up the possibility of collecting additional data on a voluntary basis, provided that certain technical and qualitative standards are adhered to8.


All this will help to improve the availability, quality and accessibility of ESG data as well as the efficiency with which financial institutions work with and use ESG data. The availability and quality of reported data should receive a further boost once the Non-Financial Reporting Directive (NFRD) and Sustainable Finance Disclosure Regulation (SFDR) take their full effect.


Even so, it’s highly likely that many users of ESG data will need to rely on multiple data providers for the foreseeable future. The good news is that there are actions users can take now to trim costs, reduce risks and maximize the value they derive from ESG data. The following focus areas will be critical to any ESG data strategy:


  • Migrating to a single data later which supports all ESG use cases and is accessible for all involved teams, will strip out the cost of duplication and lower the data risk around inconsistency.

  • Using a data model that integrates key ESG frameworks into a single data model and visualizes the data lineage will help identify overlaps between different frameworks and support the rationalization of external data sources.

  • Embedding an ESG data governance operating model can be leveraged to streamline the data governance activities required, to provide a holistic view of priority data management initiatives.

Natalie Brandau, Manager, Wealth and Asset Management, Ernst & Young GmbH Wirtschaftsprüfungsgesellschaft co-authored this article

Jo Freeman-Young, Sustainability Actuary, Consulting, Financial Services, Ernst & Young LLP co-authored this article


The markets for ESG data have never been more dynamic. Although the categories and coverage of the data are expanding rapidly, there are still numerous gaps and inconsistencies.

Once the Non-Financial Reporting Directive (NFRD) and the Sustainable Finance Disclosure Regulation (SFDR) are fully implemented, there should be an increase in both the quantity and quality of reported data. Despite this, it is highly likely that many ESG data users will need to use multiple data providers in the near future.

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