How Did the ESG Data Industry Build the Information Infrastructure of Sustainable Finance?

ESG investing requires ESG data. Analyzing whether a company manages environmental risks adequately, treats its workers fairly, and governs itself with appropriate oversight requires information that does not appear in traditional financial statements. A small, specialized industry built that information infrastructure over three decades — gathering, processing, and selling ESG data to institutional investors. Today, the ESG data market is dominated by a handful of major providers, serves tens of thousands of institutional clients, and generates billions in annual revenue. It is also structurally controversial: its ratings disagree profoundly, its methodologies are opaque, and the quality of its inputs is difficult to verify.

Quick definition: ESG data providers are firms that collect, analyze, and distribute non-financial information about companies covering environmental, social, and governance factors. Their products — ESG scores, ratings, controversy alerts, and thematic data — are the primary information inputs for ESG investment decision-making.

Key takeaways

• KLD Research & Analytics (1988), the first ESG data firm, created the original database that MSCI later acquired and expanded into the world's largest ESG ratings system.
• The ESG data market grew from a handful of specialized boutiques in the 1990s to a consolidating industry generating over $1 billion annually by the early 2020s.
• MSCI, Sustainalytics (owned by Morningstar since 2020), S&P Global ESG, Bloomberg ESG, ISS ESG, and Refinitiv (LSEG) are the dominant providers.
• The major providers' ESG scores for the same companies frequently diverge dramatically — a methodological and structural problem described in depth in Chapter 3.
• Proposed regulation of ESG rating agencies, including the EU's ESG Rating Regulation (expected implementation mid-2020s), would for the first time impose licensing, methodology disclosure, and conflict-of-interest management requirements on the industry.

The Origins: KLD and the Pioneer Era

The modern ESG data industry traces its origins to KLD Research & Analytics, founded in Boston in 1988 by Peter Kinder, Steve Lydenberg, and Amy Domini. KLD developed the first systematic, multi-factor ESG database covering US public companies — assessing environmental, social, and governance factors against defined criteria and recording both positive and negative indicators for each company and category.

KLD's methodology was groundbreaking in its time: it combined analysis of publicly disclosed information (regulatory filings, corporate reports, litigation records) with survey data from companies and proprietary research. The resulting database — which covered hundreds of US companies by the mid-1990s and thousands by the 2000s — became the foundation for the first generation of ESG-screened investment products and academic research.

KLD also developed the Domini 400 Social Index (now the MSCI KLD 400 Social Index), launched in 1990, which became the first major US ESG equity index. The index's performance track record, stretching back to 1990, provides one of the longest historical time series for academic research on ESG portfolio performance — a dataset that continues to be used in studies of ESG and returns.

Industry Consolidation: 2010–2020

For the first two decades, the ESG data industry was fragmented: KLD, Vigeo Eiris (European), Ethibel, BMJ Research, Innovest, and dozens of other boutiques served different client bases with different methodological approaches. Consolidation began in earnest in the 2010s as institutional ESG demand scaled and the major financial data firms recognized that ESG represented a significant revenue opportunity.

MSCI acquired KLD and Innovest in 2010, combining KLD's governance and social ratings with Innovest's environmental analytics into a unified MSCI ESG research platform. Subsequent acquisitions of GMI Ratings (governance analytics, 2014) and Burgiss (private market data with ESG integration, 2019) made MSCI the largest ESG data firm by coverage and revenue.

Morningstar acquired a controlling stake in Sustainalytics in 2017 and full ownership in 2020. Sustainalytics, founded in Amsterdam in 1992, had developed a distinctive ESG Risk Ratings methodology that assessed how much ESG risk a company was exposed to that was "unmanaged" — a concept different from ESG score rankings and more directly linked to financial risk.

S&P Global acquired Trucost (environmental data specialist) in 2016 and the Sustainable1 brand consolidates its ESG data offering, including the Corporate Sustainability Assessment originally developed by RobecoSAM (now part of S&P Global).

Bloomberg developed its own ESG disclosure scores, focusing on the quantity and quality of ESG data that companies disclose rather than independently assessing performance. Bloomberg ESG scores are widely used in quant investment processes because of Bloomberg's deep integration with portfolio analytics platforms.

ESG data industry consolidation

The Business Model Question

ESG data providers operate under business models that create structural conflicts of interest analogous to those in the credit rating industry. Two models dominate:

Investor-pays: The data provider sells ESG scores, ratings, and research to investment managers and asset owners. This model — used by Sustainalytics, ISS, and portions of MSCI's business — aligns the provider's incentives with the investors who are the end users of the data. The challenge is that comprehensive coverage of companies requires significant fixed costs that are only amortized over large subscriber bases.

Issuer-pays: Some providers charge companies for participation in their ESG assessment process — most prominently the S&P Global Corporate Sustainability Assessment (CSA) and to some extent Bloomberg's ESG disclosure service. The conflict is obvious: companies that pay for assessments have some interest in favorable scores, and providers who rely on issuer revenue have some interest in maintaining good relationships with assessed companies.

The conflicts are not purely theoretical. Research has documented patterns suggesting that companies' ESG scores improve after they begin paying for assessments from relevant providers — a correlation consistent with, though not proof of, a pay-to-play dynamic. This concern has driven regulatory interest in ESG rating agency oversight.

Real-world examples

MSCI's 2010 acquisition strategy: MSCI's decision to acquire KLD and Innovest simultaneously in 2010 was a bet on the emerging institutional demand for ESG data — a bet that generated enormous returns as ESG assets grew from $13 trillion to $35+ trillion over the following decade. MSCI's ESG revenues grew from negligible to over $300 million annually by the early 2020s.

CDP's data contribution: CDP (formerly Carbon Disclosure Project), though technically a reporting platform rather than a ratings provider, contributes essential input data to virtually all ESG data providers' environmental ratings. CDP's annual disclosure survey of tens of thousands of companies provides the most comprehensive public repository of corporate environmental data — making it effectively an upstream infrastructure provider to the entire ESG data industry.

Controversy data overlays: Specialty providers including RepRisk, Verisk Maplecroft, and Media Tenor developed controversy-monitoring services that track media, NGO, and regulatory sources for corporate ESG violations. These controversy feeds are sold to and integrated by major ESG raters as real-time adjustment mechanisms for static annual ESG scores. Their ability to identify emerging issues before they appear in formal disclosures makes them valuable complements to backward-looking annual assessments.

Common mistakes

Assuming ESG data providers are objective: ESG scores reflect specific methodological choices — what to measure, how to weight it, how to handle missing data — that are neither universal nor neutral. Two providers making different methodological choices will produce different scores for the same company. There is no ground truth against which scores can be validated the way a bond rating can eventually be validated against actual default behavior.

Relying on a single provider: The structural divergence among major ESG raters — documented in peer-reviewed research — means that any single provider's score gives an incomplete and potentially misleading picture. Triangulating across multiple providers, especially on dimensions most relevant to a specific investment thesis, produces more robust conclusions.

Ignoring data vintage: ESG data often has significant time lags. Annual sustainability reports reflect prior-year performance; ESG scores are typically updated annually rather than continuously. A company that suffered a major environmental incident in January may not have its ESG score updated until its next annual assessment cycle. Controversy monitoring services provide more timely updates but cover a narrower range of issues.

FAQ

How many ESG data providers are there globally?

Estimates vary, but the ESG data landscape includes six to eight major global providers, dozens of regional specialists, and hundreds of boutique firms offering niche data products. FactSet has tracked over 150 ESG data and ratings providers in its periodic market landscape assessments.

Do ESG data providers cover private companies?

Coverage is much weaker for private companies than public ones. Some providers — including Sustainalytics, Bureau van Dijk (Moody's), and specialized credit-risk ESG tools — extend coverage to private companies, but data quality depends heavily on whether the companies have chosen to disclose ESG information voluntarily. Mandatory ESG disclosure requirements being implemented through the EU's CSRD will eventually extend to large private companies operating in the EU.

How do ESG data providers handle companies that don't disclose ESG data?

Different providers handle missing data differently. Some substitute industry-average estimates; others use negative adjustment for non-disclosure (treating absence of data as evidence of poor performance). Bloomberg ESG scores are explicitly designed to reflect disclosure quality rather than performance — a company that discloses nothing receives a score of zero. This creates incentives for disclosure but can reward disclosure-without-performance.

What is the regulatory status of ESG rating providers?

As of the mid-2020s, ESG rating providers operate without mandatory licensing or oversight in most jurisdictions. The EU's proposed ESG Ratings Regulation (expected to come into force mid-2020s) would require ESG rating providers serving EU investors to be authorized by ESMA, disclose their methodologies, manage conflicts of interest, and provide complaint-handling mechanisms. The UK Financial Conduct Authority has also proposed a comparable voluntary code for ESG rating providers operating in the UK.

How do I access ESG data as an individual investor?

Most institutional ESG data is sold through subscription services not accessible to retail investors. However, some ESG data is available publicly: CDP's disclosure database, GRI sustainability reports on companies' own websites, SASB-aligned disclosures, and proxy voting records are all free. Free retail ESG research tools are available from Morningstar (limited Sustainalytics data), As You Sow (weapon/tobacco/fossil-fuel screens), and similar platforms.

Related concepts

• How ESG Ratings Work
• ESG Rating Disagreements
• MSCI ESG Ratings Methodology
• ESG Rating Conflicts of Interest
• ESG Rating Regulation
• ESG Glossary

Summary

The ESG data industry built the information infrastructure that makes ESG investing possible. From KLD's pioneering 1988 database to the consolidated platforms of MSCI, Morningstar Sustainalytics, S&P Global ESG, Bloomberg, ISS, and Refinitiv, the industry grew from a small community of mission-driven data gatherers into a multi-billion-dollar sector serving the world's largest investors. Its structural features — methodological divergence, business-model conflicts, coverage gaps, and data-quality limitations — are not incidental flaws but endemic characteristics of a field that is trying to quantify something inherently complex and contested. Understanding these limitations is prerequisite to using ESG data effectively.

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