ESG Data Market: No Stopping Its Rise Now

Executive Summary


As the bid to invest responsibly has become mainstream over the past few years, the demand for environmental, social and governance (ESG) data has skyrocketed. While originally limited to scores and ratings assessing the extra-financial performance of companies, ESG data now cover a wide variety of products and services used at most financial institutions and, to a lesser extent, at corporates. The market development is notably due to an increased demand from investors and the development of new types of non-financial data for different use cases. Above all, the development of the ESG data market has been made possible by the enhancement of ESG data quality and the continual improvement of related methodologies by data providers.

ESG Data: a Work in Progress

The growth of the ESG data market has been supported by regulatory progress, notably in Europe where ESG considerations are now sanctioned as part of institutional investors‘ fiduciary duty. Originally, ESG data were used for compliance and marketing purposes, allowing financial institutions to “tick the box”, and the flagship product offered by ESG data providers was ESG ratings, whose appeal were their usability and affordability. But as ESG integration advances among asset managers and asset owners, the range of ESG data products and services is evolving together with the number of use cases at institutions. For instance, asset managers use ESG data all along the investment decision process, including for portfolio selection, index construction, risk management, voting practices, and engagement with issuers, while corporates leverage ESG data to benchmark against peers or to understand where sources of sustainability risk and opportunities lie.

Different use cases will necessitate different levels of detail and data granularity. While ESG ratings are still very useful as a warning product, engagement with corporates requires delving into the details of the different metrics of the issuer.  As a result, ESG data providers have developed a full gamut of ESG products ranging from raw data to ESG aggregated scores by way of analytical tools, such as climate change scenarios or carbon emission footprints.

Consequently, data vendors have contributed to an overall improvement of ESG data quality that was long considered the main barrier to greater ESG adoption and integration.

These vendors have multiplied their data sources, thanks largely to the use of technology (e.g., artificial intelligence, web scraping, natural language processing, etc.), the enlargement of their coverage areas (number of companies covered, sectors, regions, asset classes, etc.) and the improvement of their methodology and its transparency.

Technologies, however, will not be the panacea:  some data will always be missing, and some corporate reporting will remain based on proxies and estimates. The only guarantee for their reliability will be the quality of the methodology developed by data providers.

A Thriving Market

The ESG data market is flourishing around the globe, bolstered by the increasing demand for ESG data and the responsive offerings developed by a growing number of providers.

In total, Opimas estimates the ESG data market was US$617 million in 2019. With an expected annual growth rate of 20% for ESG data and 35% for ESG indices, the market could approach US$1 billion by 2021.

Figure 1. ESG Data Market Size


Source: Opimas estimates


In terms of geographic distribution, 60% of ESG data spending is driven by Europe in response to regulatory pressure. North America accounts for one-third of the market, with Asia accounting only for a small portion of spending.

Asset managers are the heaviest spenders (59%) as they already buy ESG data for different use cases, in varying forms ranging from raw data to ESG ratings, and from different providers.

New data vendors

While they have diversified their offerings, ESG data vendors are trying hard to differentiate themselves. The landscape has been particularly affected by acquisitions over the past few years, with several incumbent players acquiring smaller firms that have strong expertise in ESG.

Today, different categories of ESG data providers coexist in the market: generalist data vendors (e.g., Bloomberg or Refinitiv), ESG-focused data vendors (e.g., Sustainalytics, Carbone 4, CDP), credit rating agencies (e.g., Moody’s), exchanges (such as LSE, JSE, etc.), and asset managers (e.g., Arabesque, RobecoSAM, etc.).

The range of services differs among these vendors, but they tend to all offer a range of products allowing access to different levels of data granularity, covering all use cases at financial institutions and corporates.


Next Stages for ESG data

Until now, the industry has mostly focused on a quantitative approach, particularly with the use of ESG ratings that attempt to transform qualitative information into hard numbers. As ESG integration and the corollary need for granular data continue to grow, ESG data providers should consider adding a qualitative layer on top of their quantitative data. We expect financial analysts, notably within sell-side institutions, to embrace ESG criteria in their company reports as they certainly have a role to play in enriching quantitative information within their qualitative research.

The comparability of ESG data is still an issue. Due to the lack of certain data (e.g. Scope 3 emissions, which cover all indirect carbon emissions that occur in the whole value chain of the reporting company) and the absence of standards to estimate them, comparing ESG data of two different companies is difficult, if not impossible. ESG ratings use should be limited to assess the evolution of a company over time and its trajectory towards sustainability rather than for comparing firms, even within the same industry. This is particularly true regarding carbon emissions data, which are still too imperfect to be used as is in the investment decision process.

With the development of the ESG data range covering different degrees of granularity, the challenge will be to find the right balance between usability and granularity.

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