Comprehensive database of ESG ratings and sustainability metrics for 1,200+ global companies including Fortune 500. Coverage indicators for Environmental, Social, and Governance factors.

Unlike traditional ESG data sets that are focused on annual ratings and periodic corporate disclosure, Event Registry monitors company ESG behavior at the speed of current events detected in global news. We utilize AI to analyze over 150,000 sources and uncover ESG risks and opportunities hidden in unstructured news and PR articles. We identify company events leveraging the 26 ESG categories defined by the Sustainability Accounting Standards Board (SASB) and 17 Sustainable Development Goals (SDGs). The data feed covers 200.000+ companies with up to 5 years of history.

The initial sample of this study covers the A-share companies listed on the Shanghai and Shenzhen stock exchanges during the period 2008-2021. We then screened and processed the initial sample data, including (a) Screening for companies with both RepRisk's ESG rating and Bloomberg's ESG rating. Specifically, the selection is based on samples with the same ISIN code and companies' English names in the Bloomberg and RepRisk lndex (RRI) databases. The ISIN code is a securities coding standard developed by the International Organization for Standardization (ISO) and is a unique code used to identify securities in each country or region around the world. We exclude samples that do not provide ISIN codes or have inconsistent English names. (b) We exclude observations with missing values for the main variables. (c) We exclude the ST, *ST and PT trading status samples during the observation period. Our final sample contains 1456 firm-year observations.The ESG disclosure score data and ESG performance score data required for the ESG-washing construction are respectively obtained from the Bloomberg database and the RepRisk Index (RRI) database of the Wharton Research Centre for Data Studies (WRDS). Positive media coverage data is sourced from the China Research Data Services Platform (CNRDS), while the instrumental variable (IV_population) is obtained from the EPS database and Juhe Data (https://www.gotohui.com/). Unless otherwise stated, all other data in this study are from the China Stock Market and Accounting Research (CSMAR) database.Data on executive company changes were collected manually by the authors back-to-back and independently. Then we compared and reconciled the data collected by each, and where there were discrepancies, we again collected and calibrated the data to maximize their reliability. We first obtained executive biographies from the CSMAR database, and the missing values were retrieved from Sina Finance ( https://finance.sina.com.cn/). Due to the unstructured nature of the resume data, we manually processed more than 30,000 resumes of executives to get the data of executives' company changes, based on which we calculated the per capita number of job hops of all executives in each company. The number of part-time jobs held by executives also reflects their pursuit of career changes and development, so in the robustness test the per capita mean of the number of part-time jobs held by executives is used as a proxy variable for careerist orientation. These data can be obtained directly from the CSMAR database.

The dataset contains: - the first differences of logarithms of CDS spreads and the first differences of ESG scores of US companies from 2016 to 2023; - Refinitiv Instrument Codes and OrgIDs that were used to download CDS spreads and ESG scores from the Refinitiv Eikon database.

ESG Data Vendor Aggregation Market Outlook

According to our latest research, the ESG Data Vendor Aggregation market size reached USD 2.14 billion globally in 2024, propelled by a robust demand for comprehensive Environmental, Social, and Governance (ESG) data solutions across financial and corporate sectors. The market is expected to advance at a CAGR of 17.6% from 2025 to 2033, reaching an estimated value of USD 7.34 billion by 2033. This remarkable growth is driven by the increasing integration of ESG criteria into investment decision-making, regulatory mandates, and the growing emphasis on sustainability reporting and risk management.

The primary growth factor for the ESG Data Vendor Aggregation market is the accelerating pace of ESG integration across investment portfolios and corporate strategies. Institutional investors, asset managers, and financial institutions are under mounting pressure from stakeholders and regulators to incorporate ESG considerations into their risk assessments and investment decisions. As a result, there is a surging demand for high-quality, comprehensive, and standardized ESG data that can be aggregated from multiple sources, validated, and analyzed to provide actionable insights. The proliferation of ESG frameworks and the evolving regulatory landscape—such as the EU Sustainable Finance Disclosure Regulation (SFDR) and the US SEC’s climate-related disclosures—are compelling organizations to seek reliable ESG data vendor aggregation services that can streamline compliance and enhance transparency.

Another critical factor fueling the market’s expansion is the increasing complexity and volume of ESG data sources. Companies and investors are grappling with disparate data sets, ranging from public disclosures and proprietary databases to alternative data such as satellite imagery and social media analytics. This complexity necessitates robust data aggregation and analytics platforms capable of integrating, validating, and harmonizing ESG data from multiple channels. Vendors that offer advanced data aggregation, analytics, and reporting solutions are witnessing heightened demand, as organizations strive to make sense of vast and varied ESG information to inform strategic decisions and stakeholder communications.

Technological advancements in data analytics, artificial intelligence, and cloud computing are further propelling the ESG Data Vendor Aggregation market. The adoption of AI-driven analytics and machine learning algorithms is enhancing the accuracy, reliability, and timeliness of ESG data aggregation and validation processes. Cloud-based platforms are enabling scalable and flexible deployment of ESG data solutions, making them accessible to a broader range of organizations, including small and medium enterprises. These innovations are not only improving the quality and accessibility of ESG data but also reducing operational costs and facilitating real-time insights, thus accelerating market growth.

From a regional perspective, North America and Europe are leading the ESG Data Vendor Aggregation market, accounting for the majority of global revenues in 2024. North America’s dominance is attributed to stringent regulatory requirements, a sophisticated financial ecosystem, and early adoption of ESG frameworks. Europe, driven by robust policy initiatives and investor activism, is rapidly expanding its ESG data vendor landscape. The Asia Pacific region is exhibiting the highest growth rate, fueled by rising awareness of ESG issues, regulatory developments, and increasing foreign investment in sustainable assets. Latin America and the Middle East & Africa, while still emerging, are witnessing growing traction as multinational corporations and local stakeholders prioritize ESG integration and reporting.

Service Type Analysis

The ESG Data Vendor Aggregation market is segmented by service type into Data Aggregation, Data Analytics, Data Validation, Reporting Solutions, and Others. Data Aggregation services form the backbone of the market, as organizations increasingly seek to consolidate ESG data from a myriad of sources, including public disclosures, proprietary databases, and alternative datasets. The complexity of ESG data—spanning environmental metrics, social indicators, and governance factors—necessitates advanced aggregation capabilities to ensure data completeness, consistency, and comparability. Vendors specializing in data aggregation are leveraging autom

AI in ESG Reporting Market Outlook

According to our latest research, the global AI in ESG Reporting market size reached USD 1.92 billion in 2024 and is projected to grow at a robust CAGR of 21.6% from 2025 to 2033. By the end of 2033, the market is forecasted to achieve a value of approximately USD 13.1 billion. This accelerated growth is primarily driven by increasing regulatory mandates, heightened investor focus on sustainability, and the growing complexity of environmental, social, and governance (ESG) data management. As per our latest research, the AI in ESG Reporting market is witnessing rapid adoption across diverse sectors, reflecting a paradigm shift in how organizations approach sustainability and compliance reporting.

One of the fundamental growth drivers for the AI in ESG Reporting market is the expanding regulatory landscape. Governments and international bodies are continuously tightening ESG disclosure requirements, compelling organizations to adopt advanced technological solutions for efficient compliance. AI-powered ESG reporting platforms facilitate real-time data collection, automate complex analytics, and ensure timely submission of comprehensive reports. This automation not only reduces human error but also accelerates the reporting process, enabling organizations to stay ahead of regulatory changes. As climate change and social responsibility take center stage, businesses are increasingly investing in AI-driven solutions to ensure accuracy, transparency, and adherence to global standards.

Another significant factor fueling market expansion is the escalating demand from investors and stakeholders for transparent, data-driven ESG insights. Institutional investors are placing greater emphasis on sustainability metrics to guide their investment decisions, which has led to a surge in demand for reliable ESG reporting tools. AI technologies empower organizations to analyze vast volumes of structured and unstructured data, providing actionable insights that enhance decision-making and risk management. The integration of AI in ESG reporting not only strengthens corporate accountability but also helps organizations differentiate themselves in a competitive market by demonstrating their commitment to sustainable business practices.

The proliferation of big data and advancements in natural language processing (NLP) and machine learning algorithms are further accelerating the adoption of AI in ESG reporting. As organizations amass increasingly complex and voluminous ESG datasets, traditional reporting methods become inadequate. AI-driven platforms can seamlessly aggregate, cleanse, and interpret data from multiple sources, including IoT sensors, internal databases, and external ESG rating agencies. This capability enables organizations to deliver high-quality, consistent, and auditable ESG reports. Additionally, AI-powered predictive analytics help identify emerging risks and opportunities, allowing companies to proactively address ESG issues and enhance long-term value creation.

From a regional perspective, North America currently dominates the AI in ESG Reporting market, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The North American market benefits from a mature technological infrastructure, early adoption of AI, and stringent ESG regulations, particularly in the United States and Canada. Europe is witnessing significant momentum, driven by the European Union’s Sustainable Finance Disclosure Regulation (SFDR) and the Corporate Sustainability Reporting Directive (CSRD). Meanwhile, the Asia Pacific region is poised for the fastest growth, fueled by increasing awareness of ESG principles, evolving regulatory frameworks, and the rapid digital transformation of enterprises across China, Japan, and India.

Component Analysis

The Component segment in the AI in ESG Reporting market is bifurcated into Software and Services. AI-powered software solutions are at the forefront, offering advanced analytics, automation, and visualization tools that streamline ESG data management and reporting. These platforms leverage machine learning, NLP, and predictive analytics to automate data collection, standardize metrics, and ensure compliance with evolving regulatory requirements. The software segment is expected to maintain its dominance throughout the forecast period, driven by continuous innovation, integration capabilities with existing enterprise systems, and growing dema

In the context of the ESG era, this study provides an in-depth analysis of the ESG practices of listed companies and their impact on business performance in Korea and Taiwan, two of the Four Little Dragons economies in Asia. Although these two regions are similar in terms of economic size, they show significant differences in their ESG implementation strategies and effects. Based on the Bloomberg database, this study empirically analyzes data from 113 Taiwanese and 113 Korean firms, using Tobin’s q ratio as a measure of business performance. The findings show that there is complexity in the association between ESG scores and firms’ business performance. In South Korea, government policies and large conglomerates contribute significantly to ESG practices, while in Taiwan, the economic structure dominated by SMEs has led to different characteristics of ESG practices. All of these differences reflect the influence of intra-firm factors on performance. The findings of this study not only enrich the theoretical foundation of the relationship between ESG and business performance, but the findings provide valuable regional insights and recommendations for international investors, corporate managers, and policymakers in the Asia-Pacific region to implement ESG strategies, especially when considering the specific market environment, economic structure, and internal factors of the firms they operate in order to achieve sustainable growth and competitive advantage.

ISS ESG’s Custom Ratings tool allows users to develop comprehensive custom ESG scoring models based on a broad range of responsible investment principles and user-defined criteria. By leveraging the wide range of near-time ESG and financial data available on ISS’ proprietary DataDesk platform, investors can quickly and efficiently rate companies with full control over model customization, including content selection and grouping, weighting and scoring at both the category and factor levels and defining companies for comparison.

Ratings can be used to compare a company to other companies in its industry, or to a broader set of companies, allowing investors to understand how a company performs in general and discern more subtle differences within a particular industry or group. This Custom Ratings tool further enables ISS ESG to work with clients to develop bespoke and holistic models of risk choosing from multiple factors and databases.

Data is collected based on the sources and methodology used by each ISS ESG solution. ISS ESG data is typically derived from company filings, as well as ongoing event-driven data updates as reflected in public disclosure, press releases and company web sites.

Data is used by a broad range of institutional investors, asset managers, asset owners, fund managers, banks, government institutions, universities and research firms.

Comprehensive database of corporate sustainability, ESG, and CSR reports from companies worldwide

The data comprises multiple variables from Chinese A-share listed companies between 2011 and 2021. A dual fixed-effects model was employed to examine the correlation and underlying mechanisms between corporate ESG performance and R&D innovation outcomes. The study further analyzed the impact and influence mechanisms of the three ESG dimensions—environmental, social, and governance—on R&D innovation performance. Data sources are as follows: All listed companies' financial and other data are sourced from the Wind database. Innovation and financing constraint data for listed companies are sourced from the CSMAR database. ESG data for listed companies are sourced from Bloomberg.

The data files represent the 26 estimated life-cycle-based indicators for a sample of companies and funds, obtained using the methodology described in the linked journal article. The files SD1 and SD2 contain the individual values estimated for the fund and company samples. These estimates are based on the methodology described in the linked article. The data herein is the source for producing all figures of the paper. All companies and funds have been anonymized, as the data is sourced from proprietary databases. At the same link, supplementary file SD3 contains the summary statistics and comparison of sustainable funds versus conventional funds sample. The file SD4 contains the data used to create Figure 4. The file SD5 contains sample data to create Figure 5. The file SD6 contains sample data to create Figure 6. Additional more detailed data can be provided upon reasonable request, but cannot be publicly disclosed as it contains data from licenced databases.

Discover the booming financial database market! This in-depth analysis reveals key trends, growth drivers, and leading companies shaping the future of financial data, including real-time & historical databases. Explore market size, regional breakdowns, and future projections to 2033.

Sustainable Bond Framework Advisory Tools Market Outlook

According to our latest research, the global sustainable bond framework advisory tools market size reached USD 1.42 billion in 2024, driven by a robust annual growth rate. The market is experiencing a remarkable CAGR of 16.8% from 2025 to 2033, with the forecasted market size expected to reach USD 5.07 billion by 2033. This dynamic expansion is primarily fueled by the increasing demand for sustainable finance solutions, regulatory advancements, and a shift towards ESG (Environmental, Social, and Governance) compliance across corporates, financial institutions, and government agencies globally.

One of the most significant growth factors for the sustainable bond framework advisory tools market is the rapid evolution of sustainable finance regulations and frameworks across major economies. Governments and regulatory bodies are consistently updating their guidelines to ensure greater transparency, accountability, and impact measurement in the issuance of green, social, and sustainability bonds. This regulatory momentum has created an urgent need for advanced advisory tools that can assist issuers and investors in navigating complex compliance requirements, structuring bond frameworks, and verifying adherence to global standards such as the ICMA Green Bond Principles and the EU Taxonomy. As a result, the market is witnessing increased adoption of both software and services that streamline the due diligence, reporting, and verification processes, ensuring credibility and investor confidence in sustainable bond issuances.

Another key driver is the growing emphasis on climate action and social responsibility among institutional investors and corporate issuers. The heightened awareness of climate change risks and the imperative for inclusive growth have prompted organizations to integrate sustainability into their core financing strategies. Sustainable bonds, including green, social, and sustainability-linked bonds, have become essential instruments for channeling capital towards projects with positive environmental and social outcomes. Advisory tools play a critical role in helping stakeholders design effective frameworks, assess project eligibility, and monitor impact, thereby accelerating the mainstreaming of sustainable finance. Furthermore, the increasing sophistication of these tools, powered by AI, data analytics, and cloud-based platforms, is enhancing their value proposition and driving market penetration across diverse sectors.

A third factor contributing to market growth is the surge in cross-border sustainable bond issuances and the globalization of ESG investment practices. As international investors seek to diversify their portfolios and align with global sustainability goals, there is a rising demand for standardized frameworks and interoperable advisory solutions. This trend is particularly pronounced in emerging markets, where issuers are seeking to access international capital by adhering to recognized sustainability standards. Advisory tools that offer multi-jurisdictional compliance, real-time reporting, and integration with global ESG databases are gaining traction, facilitating seamless issuance and investment processes. The convergence of technology, regulatory harmonization, and investor appetite is thus propelling the sustainable bond framework advisory tools market to new heights.

From a regional perspective, Europe continues to dominate the sustainable bond framework advisory tools market, accounting for the largest share in 2024 due to its advanced regulatory environment and proactive adoption of sustainable finance initiatives. North America follows closely, driven by increasing ESG integration among corporates and institutional investors. The Asia Pacific region is emerging as a high-growth market, with rapid expansion in green and social bond issuances, particularly in China, Japan, and Southeast Asia. Latin America and the Middle East & Africa are also witnessing steady growth, supported by government-led sustainable development programs and international collaboration. Overall, the regional outlook underscores the global nature of the market, with opportunities and challenges varying according to local regulatory landscapes, market maturity, and investor preferences.

ESG Reporting Automation AI Market Outlook

According to our latest research, the global ESG Reporting Automation AI market size reached USD 1.45 billion in 2024, reflecting robust adoption across industries. With a compound annual growth rate (CAGR) of 21.8% projected from 2025 to 2033, the market is forecasted to reach USD 10.13 billion by 2033. This impressive growth is primarily driven by the increasing regulatory pressures for transparent ESG disclosures, the rising complexity of sustainability data, and the urgent need for scalable, accurate, and real-time reporting solutions powered by artificial intelligence.

The most significant growth factor for the ESG Reporting Automation AI market is the global intensification of ESG regulations and frameworks. Governments and regulatory bodies across North America, Europe, and Asia Pacific have established stringent guidelines for ESG reporting, compelling organizations to adopt advanced automation solutions to ensure compliance. As the volume and complexity of ESG data expand, manual processes become unsustainable, leading enterprises to invest in AI-driven platforms that automate data collection, validation, and reporting. This shift not only ensures accuracy and compliance but also enables organizations to proactively manage reputational risks and meet investor expectations for transparency and accountability.

Another critical driver is the increasing stakeholder demand for credible, timely, and actionable ESG insights. Investors, customers, and partners are placing greater emphasis on sustainability and ethical governance, making ESG performance a fundamental criterion in decision-making. AI-powered automation tools are transforming how organizations aggregate, analyze, and disseminate ESG data, providing granular insights that support strategic planning and operational improvements. The integration of machine learning and natural language processing further enhances the ability to interpret unstructured data, identify emerging risks, and generate comprehensive reports tailored to diverse stakeholder requirements, thereby fostering trust and competitive differentiation.

The rapid digital transformation across industries is also fueling the adoption of ESG Reporting Automation AI solutions. As organizations accelerate their journey towards digital maturity, the convergence of cloud computing, big data analytics, and AI is enabling scalable, secure, and cost-effective ESG reporting infrastructures. Companies are leveraging these technologies to streamline workflows, reduce manual errors, and achieve real-time visibility into their sustainability performance. Furthermore, the proliferation of industry-specific ESG standards necessitates flexible and customizable AI solutions that can adapt to evolving regulatory landscapes and organizational priorities, propelling market expansion across both developed and emerging economies.

The integration of ESG Data Ingestion AI is revolutionizing the way organizations handle sustainability information. By employing advanced algorithms and machine learning techniques, companies can efficiently gather and process vast amounts of ESG data from diverse sources, including internal databases, external reports, and real-time feeds. This capability not only streamlines the data collection process but also enhances the accuracy and reliability of ESG reporting. As a result, businesses can respond more swiftly to regulatory changes and stakeholder demands, ensuring that their sustainability disclosures are both comprehensive and up-to-date. The use of AI in data ingestion also facilitates the identification of trends and patterns that might otherwise go unnoticed, providing valuable insights for strategic decision-making and risk management.

Regionally, North America remains the dominant market for ESG Reporting Automation AI, driven by early regulatory adoption, high digitalization rates, and a mature ecosystem of technology providers. Europe closely follows, buoyed by the European UnionÂ’s ambitious sustainability agenda and mandatory ESG disclosures under the Corporate Sustainability Reporting Directive (CSRD). Asia Pacific is witnessing the fastest growth, underpinned by increasing ESG awareness among corporates and governments, rapid technological advancements, and the rise of sustainable finance initiatives. While Lati

Dataset

This dataset was created by Analyst Futures

Released under Database: Open Database, Contents: © Original Authors

Contents

This dataset is the population of the public companies from the Brazilian Stock Market (B3, 2023). The authors use the list of 100 more liquidity companies on B3. Once the authors collected the 100 most liquid companies, based on the trade shares during the period of 5 years (2017 to 2021), the authors analysed the database and eliminated all the companies with missing data during the period of 5 years. In the end of the depuration process, the authors have 93 publicly traded companies collected from the Economatica database system from the year 2017 to 2021, performing a dataset of 465 observations for 5 years. The authors observed 81 companies linked to at least one ESG-related index and 12 companies without connection to ESG. The companies used were only the ones that have all data available in all years.

We employ this dataset to examine the evolving risk-taking behavior of family firms and the role of ESG integration in mitigating excessive risk-taking. Precisely, we test the following hypotheses: H1: Family firms tend to take greater risks than non-family firms. H2: ESG integration has a greater impact on reducing risk-taking behavior in family firms than in non-family firms.

Our sample comprises non-financial A-share firms listed on the Shanghai Stock Exchange (SSE) and Shenzhen Stock Exchange (SZSE) from 2010 to 2020. The observation year starts from 2010 due to limited voluntary disclosure of social responsibility reports prior to that. We exclude (1) financial firms and (2) special treatment (ST and *ST) firms with suspension or delisting risk to control for variations in risk characteristics, (3) firms with fewer than three years of observations for risk-taking estimation, and (4) observations with missing values. The final sample includes 3,830 firms, totaling 26,151 firm-year observations: 2,409 family firms (14,928 firm-year observations) and 1,421 non-family firms (11,223 firm-year observations). We collect firm-level financial data from the China Stock Market and Accounting Research (CSMAR) database, while ESG data are from Sino-Securities Index Information Service (Shanghai) Co., Ltd. To control for potential bias due to extreme values, we winsorize the observed continuous variables at 1% and 99%.

Our results show that ESG adoption significantly reduces risk-taking in family firms by improving internal control quality, governance transparency, and reducing financial constraint, thereby strengthening overall corporate resilience. Robustness tests confirm these findings, while heterogeneity analysis reveals variations across firm life cycles, ownership structures, and industry contexts. Overall, ESG serves as a crucial governance mechanism, balancing strategic risk-taking with long-term sustainability in family firms.

Explore the booming Life Cycle Assessment (LCA) database market, driven by sustainability mandates and environmental awareness. Discover market size, CAGR, key drivers, restraints, and regional growth.

This layer is intended for researchers, students, policy makers, and the general public for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production. This layer will provide a basemap for layers related to socio-political analysis, statistical enumeration and analysis, or to support graphical overlays and analysis with other spatial data. More advanced user applications may focus on demographics, urban and rural land use planning, socio-economic analysis and related areas (including defining boundaries, managing assets and facilities, integrating attribute databases with geographic features, spatial analysis, and presentation output.)

United States Environmental Policy Stringency Index data was reported at 3.028 NA in 2020. This records an increase from the previous number of 2.917 NA for 2019. United States Environmental Policy Stringency Index data is updated yearly, averaging 1.250 NA from Dec 1990 (Median) to 2020, with 31 observations. The data reached an all-time high of 3.028 NA in 2020 and a record low of 0.833 NA in 1991. United States Environmental Policy Stringency Index data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ESG: Environmental: Environmental Policy Stringency Index: OECD Member: Annual.