Dataset

This dataset was created by VINAY CHAKRAVARTHI

Released under Apache 2.0

Contents

Our impact valuation data allows investors to measure, value and benchmark impacts of business activities across Natural, Human and Financial Capital KPIs.

Presented in the form of economic values, GIST's approach gives investors a common yardstick by which to understand materiality fully and accurately, so that they can manage risks, identify hidden alpha, and make informed decisions to stay ahead of the curve.

Investors can use our ESG data to screen potential investments, manage and track ESG performance across their portfolios, and clearly communicate materiality across all ESG dimensions.

Why use GIST's impact valuation data?

1. Measure all impacts of a company on shareholders and society - not just carbon / environmental impacts GIST calculates a company's impact across all four capitals - Natural, Human, Social and Financial, covering 18 main KPIs and 350+ sub-KPIs. Analysts are looking for as much data as possible on hidden alpha - and GIST provides coverage across all material impacts of a company's activities that might present a future risk - or an opportunity.

2. Compare easily across different metrics GIST uses scientific and economic modelling to provide accurate calculations of the impacts of a company in economic terms - providing a $ value of the impact on stakeholders and society. Analysts find themselves trying to make sense of fundamentally different metrics - parts per million of air pollution, tonnes of GHG emissions, gallons of water consumed, m2 land use change. GIST allows apples-to-apples comparison by converting all these different impacts into $ values (which are geography-specific), so you can understand the relative size of a company's air pollution impacts against its water consumption impacts, for example.

3. Benchmark performance across a portfolio, and within and across sectors Most sustainability scores, ratings and rankings evaluate companies within their sectors. This creates artificial distinctions and makes it difficult for analysts to measure how a company is performing in absolute terms (compared to relative grading). GIST calculates absolute impact, measured in $ values, to provide a simple, straightforward analysis that can be applied within sectors, and across sectors, to compare all the companies in a portfolio against each other accurately and make informed decisions.

4. Identify and manage material risks More traditional views of ‘risk’ have typically focused on the direct risk to a company’s P&L, and its ‘produced’ or ‘financial’ capital. These are risks that come from environmental dependencies (e.g. logistics companies threatened by storms/cyclones, agricultural companies threatened by crop failure, etc.) GIST takes a broader view and also measure risks that come from impacts of a company - not just what affects a company’s P&L directly, but what affects assets of society (natural, social, human capital) and is therefore an externality at risk of eventually being internalized - through regulation or otherwise. Assets in the oil and gas industry that have been a stranded as a result of regulatory and legal action are a good example of this risk becoming reality.

5. Understand how impact changes based on location GIST uses a granular, location-specific approach which means that with location data for activities (e.g., air pollution, waste), we can calculate the impact on shareholders and society based on local context - environmental, ecological, health, socioeconomic and demographic, so we can make more accurate estimates for example for a city in Ghana vs. a city in Sweden. As disclosure is expected to increase dramatically in the next 2 years, GIST's methodology is equipped with a level of resolution that can provide insights that are constantly increasing in precision.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F8734253%2F84d76e9b100f0eaee4b913d74c0aab45%2FScreenshot%202024-03-10%20at%203.46.10PM.png?generation=1710099996246003&alt=media" alt=""> Caption: Visualization of Microsoft (MSFT) ESG Data

Dataset Overview

This dataset contains ESG (Environmental, Social, and Governance) scores and ratings for a large number of publicly traded companies across various industries. The data is provided at a company level, with each row representing one company.

The key fields include: - Basic company information: ticker symbol, company name, currency, exchange, industry, logo URL, website URL - Environmental scores and rating: environment_score, environment_grade, environment_level - Social scores and rating: social_score, social_grade, social_level - Governance scores and rating: governance_score, governance_grade, governance_level - Overall ESG scores and rating: total_score, total_grade, total_level - Last processing date of the ESG data - CIK identifier

The environmental, social, governance and total scores are numeric values, while the corresponding grades are letter ratings (like AAA, BB etc.) and levels are categorical (like High, Medium, Low).

This dataset can be analyzed to understand the distribution of ESG scores and ratings across different companies, sectors and industries. It could be combined with financial datasets to explore relationships between ESG performance and key metrics like profitability, valuation, and stock returns. The data can provide valuable insights for investors, asset managers, financial analysts, corporate strategists, policymakers and sustainability researchers.

By sharing this data publicly, the provider likely aims to bring greater transparency to corporate ESG practices, enable better integration of ESG considerations into investment decisions, and create incentives for companies to improve their ESG performance over time. Wide availability of robust ESG data is critical to driving progress on major societal goals like combating climate change and enhancing social equity.

See ESG Compare (http://esgcompare.org) for an interactive demo!

It can be difficult finding timely ESG data for multiple companies at a time unless you pay for an expensive subscription. This dataset includes ESG ratings and stock market information for approximately 700 companies. When comparing ESG ratings, it's important to compare a company with their industry or sector peers rather than across industries. The reason is that there are different material issues and metrics that are considered more pertinent depending on the industry. For example, ESG ley issues and metrics for a railroad company will be different than for a bank).

This dataset includes companies that are categorized in the "Industrials" sector, per the Global Industry Classification System (GICs). It includes ESG ratings by 4 different ESG ratings providers, if that data is available for a particular company. It also includes stock market data pulled from the first week of April 2024 - that includes 52-week high and low prices, volume, etc.

Example of chart made using this dataset:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F7790751%2F8bbc5b936efdf14d6b338678bd6466f7%2Ftrucking-april2024%20-%20Copy.png?generation=1714329261083713&alt=media" alt="">

Key columns and descriptors

Unique_id: the number used by ESGAnalytics to uniquely distinguish each company

Symbol: Stock symbol

Exchange: stock index where the company is listed (one company may be listed on multiple exchanges in the real world)

gicSector: sector classification (this is higher on the hierarchy than subindustry per the GIC

gicSubindustry: subindustry classification, the next level down in the GIC hierarchy

ESG ratings columns

Company_ESG_pulse: the main ESG ratings of this dataset; 1 is lowest investor risk and -1 means highest investor risk

ESG_beta: how much the pulse rating affects the stock market price of the company, per ESGAnalytics

SNP: the S&P Global ESG rating for the company (scale of 1-100 with 100 being the LOWEST investment risk)

Sustainalytics: the Sustainalytics ESG rating for a company with ratings 0-10 meaning negligible investment risk; 10-20 low risk; 20-30 medium risk; 30-40 high risk; 40+ severe risk

MSCI: the MSCI ESG rating for the company with ratings of CCC,B, BB meaning an industry laggard; BB, BBB, A meaning average; AA, AAA meaning industry leader

Update_data-ESG_scores: this is the date when the SNP, Sustainalytics, and MSCI scores were pulled; ESGAnalytics ratings were pulled April 2024 (as they are updated in real-time while the others are updated annually)

Stock market columns

Volume, Market Cap, 52w_highest price (52w means 52-week), 52w_lowest price, 52w_change price, 52w_average volumne were pulled the first week of April 2024.

For more details about the ESG ratings, please see my Medium post on ESG data providers.

The data is available via ESGAnalytics.io and Finazon.io use licenses (per my subscriptions with them).

Similar to others on kaggle who have shared ESG datasets, my objective is to help make ESG data more accessible and understandable so that more people are versed in what ESG is and how different companies rate.

Please let me know any comments or if there are other ESG-related datasets that you are interested in. Thank you!

This dataset is used to evaluate bias by ESG rating agencies and how their methodologies can translate to the valuation of companies. For example larger companies tend to have higher ESG ratings, which in turn will increase their stock prices however this gives ESG rating agencies unchecked power to influence financial markets based on how they manipulate or formulate their ratings.

ESG Data Quality Management for Banks Market Outlook

According to our latest research, the global ESG Data Quality Management for Banks market size reached USD 1.37 billion in 2024, reflecting a robust and accelerating demand for high-integrity ESG data in the banking sector. The market is expected to grow at a CAGR of 17.2% from 2025 to 2033, reaching an estimated USD 5.12 billion by 2033. This growth is primarily driven by stringent regulatory requirements, increasing stakeholder pressure for transparency, and the need for reliable ESG metrics to inform risk management and investment decisions.

One of the core growth drivers for the ESG Data Quality Management for Banks market is the intensifying regulatory landscape. Governments and regulatory bodies across the globe are mandating stricter ESG disclosure norms, compelling banks to invest in sophisticated data management solutions to ensure compliance. The European Union’s Sustainable Finance Disclosure Regulation (SFDR) and the US Securities and Exchange Commission’s (SEC) proposed climate-related disclosure rules are prime examples of such regulatory frameworks. These regulations not only require banks to collect, verify, and report ESG data but also emphasize the quality and reliability of this information. As a result, banks are increasingly adopting advanced ESG data quality management platforms to streamline data collection, validation, and reporting processes, thereby mitigating compliance risks and enhancing their reputation among stakeholders.

Another significant growth factor is the rising importance of ESG factors in risk management and investment analysis. Banks are recognizing that ESG risks, such as climate change, social unrest, and governance failures, can have profound financial implications. To effectively identify, assess, and mitigate these risks, banks require high-quality ESG data that is accurate, timely, and auditable. The integration of ESG data quality management solutions enables banks to develop more robust risk models, improve credit assessments, and make informed lending and investment decisions. Furthermore, investors and clients are increasingly demanding transparency regarding banks’ ESG performance, further driving the adoption of data quality management tools that can provide granular, verifiable, and actionable ESG insights.

Technological advancements also play a pivotal role in the growth trajectory of the ESG Data Quality Management for Banks market. With the advent of artificial intelligence, machine learning, and big data analytics, banks can now automate the collection, cleansing, and analysis of large volumes of ESG data from diverse sources. These technologies enhance data accuracy, reduce manual intervention, and provide real-time insights, enabling banks to respond swiftly to evolving ESG risks and opportunities. Additionally, the proliferation of cloud-based ESG data management platforms offers scalability, flexibility, and cost-effectiveness, making it easier for banks of all sizes to implement and scale their ESG data quality initiatives.

From a regional perspective, Europe currently leads the ESG Data Quality Management for Banks market, driven by its progressive regulatory environment and strong emphasis on sustainable finance. North America follows closely, with increasing regulatory scrutiny and growing investor demand for ESG transparency propelling market growth. The Asia Pacific region is poised for the fastest growth, fueled by rapid digitalization in the banking sector and emerging ESG regulations in key markets such as China, Japan, and Australia. Latin America and the Middle East & Africa, while still nascent, are witnessing rising awareness of ESG issues and gradually strengthening regulatory frameworks, which are expected to contribute to market expansion over the forecast period.

Component Analysis

The Component segment of the ESG Data Quality Management for Banks market is primarily bifurcated into Software and

The World Bank's ESG Data Draft dataset provides information on 17 key sustainability themes spanning environmental, social, and governance categories. In order to shift financial flows so that they are better aligned with global goals, the World Bank Group (WBG) is working to provide financial markets with improved data and analytics that shed light on countries’ sustainability performance. Along with new information and tools, the World Bank will also develop research on the correlation between countries’ sustainability performance and the risk and return profiles of relevant investments.

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.

ESG Data Lineage and Traceability Tools Market Outlook

According to our latest research, the global ESG Data Lineage and Traceability Tools market size reached USD 1.31 billion in 2024, driven by the increasing regulatory requirements and growing demand for transparent ESG (Environmental, Social, and Governance) data management. The market is expected to expand at a robust CAGR of 20.8% during the forecast period, reaching a projected value of USD 8.69 billion by 2033. Accelerated digital transformation across industries, coupled with heightened stakeholder scrutiny and evolving compliance standards, are serving as key growth catalysts for the ESG Data Lineage and Traceability Tools market.

The surge in demand for ESG Data Lineage and Traceability Tools is primarily fueled by the intensification of regulatory frameworks globally. Governments and regulatory bodies are increasingly mandating organizations to provide transparent, auditable, and verifiable ESG disclosures. This has prompted enterprises to invest in sophisticated solutions that offer end-to-end visibility into the origin, transformation, and flow of ESG data. The ability of these tools to automate data collection, validation, and reporting processes is enabling organizations to minimize compliance risks and avoid costly penalties. Furthermore, the integration of artificial intelligence and machine learning in these tools enhances data accuracy and facilitates proactive risk management, making them indispensable in today’s compliance-driven environment.

Another significant growth driver is the increasing stakeholder emphasis on sustainability and responsible business conduct. Investors, customers, and partners are demanding more granular and reliable ESG information to inform their decision-making processes. ESG Data Lineage and Traceability Tools empower organizations to demonstrate accountability and build trust by providing a transparent audit trail of ESG metrics and initiatives. This transparency not only strengthens corporate reputation but also opens doors to new investment opportunities and partnerships. As organizations recognize the strategic value of ESG data, the adoption of these tools is expected to accelerate across various sectors, particularly in industries with complex supply chains and high environmental impact.

Technological advancements are also playing a pivotal role in shaping the ESG Data Lineage and Traceability Tools market. The proliferation of cloud computing, big data analytics, and blockchain technology is enabling the development of scalable and secure solutions that can handle vast volumes of ESG data from diverse sources. These innovations facilitate real-time monitoring, advanced analytics, and seamless integration with existing enterprise systems, further enhancing the utility and appeal of ESG data management platforms. The convergence of these technologies is expected to drive continuous innovation and create new growth avenues for market participants over the coming years.

From a regional perspective, North America currently leads the ESG Data Lineage and Traceability Tools market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The strong presence of regulatory mandates, coupled with the early adoption of advanced technologies, has positioned these regions at the forefront of market growth. However, Asia Pacific is anticipated to witness the highest CAGR throughout the forecast period, driven by increasing ESG awareness, rapid industrialization, and evolving regulatory landscapes in emerging economies. Latin America and the Middle East & Africa are also expected to register steady growth as organizations in these regions ramp up their ESG initiatives in response to global sustainability trends.

Component Analysis

The ESG Data Lineage and Traceability Tools market is segmented by component into Software and Services, both of which play critical roles in the ecosystem. The Software segment compris

Environmental, Social, and Governance (ESG) initiatives are no longer optional—they’re business-critical. Accurate, timely, and transparent environmental data plays a key role in meeting stakeholder expectations, improving sustainability performance, and complying with regulatory frameworks like CSRD, SFDR, and the SEC’s climate disclosure rules. Ambios offers high-resolution ESG Data from a decentralized network of over 3,000+ first-party sensors operating across 20 countries. Our data is built for precision, transparency, and traceability—enabling organizations to confidently measure and report on their environmental impact.

-100% first-party sensor data -Real-time and historical coverage across urban and rural environments -Key ESG metrics, including air quality (AQI), PM2.5, PM10, CO, NO₂, O₃, temperature, and humidity -Structured for integration with ESG platforms and sustainability dashboards -Supports climate risk modeling, regulatory disclosures, and performance benchmarking

Ambios uses a DePIN-based infrastructure (Decentralized Physical Infrastructure Network) to ensure data integrity, provenance, and scalability. With automated data delivery and customizable access formats), our ESG dataset empowers enterprises to meet evolving environmental mandates and drive data-backed sustainability action. Whether reporting emissions, conducting climate risk assessments, or building impact frameworks, Ambios ESG Data gives you the environmental layer your reporting demands.

ESG Data Marketplaces Market Outlook

According to our latest research, the global ESG Data Marketplaces market size reached USD 2.3 billion in 2024, reflecting increasing demand for high-quality environmental, social, and governance data across industries. The market is poised for robust expansion, with a projected CAGR of 18.7% from 2025 to 2033. By 2033, the ESG Data Marketplaces market size is forecasted to reach approximately USD 12.7 billion. This significant growth is driven by the escalating need for transparent ESG reporting, regulatory compliance, and the integration of sustainability metrics into investment and corporate decision-making processes.

A primary growth factor for the ESG Data Marketplaces market is the global surge in ESG investing. Institutional and retail investors are increasingly demanding reliable and granular ESG data to guide their investment strategies, as sustainability considerations become integral to portfolio management. The proliferation of sustainable finance regulations, such as the European Union’s Sustainable Finance Disclosure Regulation (SFDR) and the Task Force on Climate-related Financial Disclosures (TCFD), has compelled asset managers and corporations to seek comprehensive ESG datasets. As a result, ESG Data Marketplaces have become essential in aggregating, standardizing, and distributing this critical information, fueling their adoption across financial institutions and corporate entities alike.

Another key driver is the evolving corporate landscape, where organizations are under mounting pressure from stakeholders, including customers, employees, and regulators, to demonstrate their ESG commitments. Companies are now leveraging ESG Data Marketplaces to benchmark their performance, identify gaps, and report on sustainability initiatives with accuracy and transparency. The rise in voluntary and mandatory ESG disclosures is pushing corporates to invest in sophisticated data platforms that offer real-time analytics, customizable reporting, and integration with existing enterprise resource planning (ERP) systems. This trend is further amplified by the increasing use of artificial intelligence and machine learning in ESG analytics, which enhances the predictive power and actionable insights derived from ESG data.

Technological advancements and the growing adoption of cloud-based solutions are also accelerating the expansion of the ESG Data Marketplaces market. Cloud deployment offers scalability, flexibility, and cost-effectiveness, enabling users to access vast repositories of ESG data from any location. Additionally, the integration of APIs and data interoperability standards is improving data accessibility and usability, fostering a more collaborative ESG ecosystem. These technological innovations are not only reducing the barriers to entry for smaller organizations but are also supporting the development of niche ESG data services tailored to specific industries and regulatory requirements.

From a regional perspective, North America and Europe currently dominate the ESG Data Marketplaces market, owing to advanced regulatory frameworks, strong investor activism, and high adoption rates among financial institutions. However, the Asia Pacific region is exhibiting the fastest growth, driven by increasing sustainability initiatives, government mandates, and the rapid expansion of capital markets. Countries such as Japan, China, and Australia are witnessing a surge in ESG data demand, as local companies seek to align with global best practices and attract international investors. Meanwhile, emerging markets in Latin America and Middle East & Africa are gradually embracing ESG data solutions, albeit at a slower pace, as awareness and regulatory support continue to build.

Component Analysis

The ESG Data Marketplaces market is segmented by component into Platform and Services. Platforms represent the backbo

ESG Data Management for Supply Chain Market Outlook

According to our latest research, the global ESG Data Management for Supply Chain market size reached USD 1.78 billion in 2024, reflecting robust adoption across industries striving for sustainable operations. The market is expected to grow at a CAGR of 18.2% over the forecast period, with a projected value of USD 8.16 billion by 2033. This remarkable expansion is primarily driven by increasing regulatory mandates, stakeholder pressure for transparency, and the growing realization of ESG risks and opportunities within complex supply chains.

One of the most significant growth factors propelling the ESG Data Management for Supply Chain market is the tightening regulatory landscape worldwide. Governments and regulatory bodies are enforcing stricter ESG reporting requirements, compelling organizations to enhance their data management capabilities. The European Union’s Corporate Sustainability Reporting Directive (CSRD), the US SEC’s climate disclosure rules, and similar mandates in Asia Pacific are driving enterprises to adopt advanced ESG data management solutions. These regulations not only require comprehensive, accurate, and auditable ESG data but also extend their purview to supply chain partners, making end-to-end visibility and traceability essential. As a result, organizations are investing in robust software and services to ensure compliance, mitigate risks, and maintain their social license to operate.

Another key driver is the increasing demand from stakeholders, including investors, customers, and business partners, for transparency and accountability in ESG performance. Investors are integrating ESG criteria into their decision-making processes, often requiring detailed disclosures on supply chain sustainability. Consumers are also becoming more conscious of the ethical and environmental impact of their purchases, favoring brands that demonstrate responsible sourcing and supply chain practices. This shift in stakeholder expectations is compelling organizations to prioritize ESG data management, not just as a compliance exercise, but as a strategic differentiator. Enhanced ESG data management enables companies to identify risks, capture opportunities, and build resilient, sustainable supply chains that can withstand disruptions.

Technological advancements are further accelerating the adoption of ESG Data Management for Supply Chain solutions. The integration of artificial intelligence, machine learning, blockchain, and IoT technologies is revolutionizing the way organizations collect, analyze, and report ESG data across their supply chains. These technologies facilitate real-time monitoring, automated data collection, and advanced analytics, enabling organizations to gain deeper insights into supplier performance and ESG risks. Furthermore, cloud-based platforms are making ESG data management more accessible and scalable, particularly for small and medium enterprises. As technology continues to evolve, it is expected to play a pivotal role in shaping the future of ESG data management in supply chains.

Regionally, North America and Europe are leading the adoption of ESG Data Management for Supply Chain solutions, driven by stringent regulations and high stakeholder awareness. However, Asia Pacific is emerging as a high-growth market, fueled by rapid industrialization, increasing regulatory focus, and growing participation in global supply chains. Latin America and the Middle East & Africa are also witnessing increased adoption, particularly among multinational corporations seeking to standardize ESG practices across their global operations. The regional dynamics underscore the global nature of ESG challenges and the need for scalable, adaptable data management solutions.

Component Analysis

The ESG Data Management for Supply Chain market is segmented by component into software and services, each playing a distinct yet complementary role in driving market growth. The software segment encompasses platforms and applica

ESG footprint of Synthetic UK Individuals and Businesses

Contains information on various energy usages, housing, and their associated costs on 4000 synthetic UK individuals. It can be used to analyze the trends towards sustainability at the individual level.

This sample data is part of the statistically accurate representation of the UK economy that can be found at https://nayaone.com/digital-twin/. Our mission is democratization and quality data governance in areas where the lack of data is a major hurdle for innovation and progress. To learn more, contact us: contact@nayaone.com

Content

Attributes

Businesses

• borough_county: Districts in the UK (some are counties some are towns)
• primary_sector: SIC - 2007 numerical codes
• entity_trade_name: Trading name of the company
• annual_turnover: Annual turnover split into 4 bands
• entity_status: Active org = 1, Dissolved = 0
• country_of_primary_operation: All UK
• Coal_Consumption_By_Sector(toe): Total coal consumption by company
• Electricity_Consumption_By_Structure(toe): total electricity consumption by the company according th the structure type and location
• Gas_Consumption_By_Structure(toe): total gas consumption by the company according the structure type and location
• Geographic Code: Geocode according th the county of company
• Local Authority: County of the company
• NG_Consumption_By_Sector(toe): Natural gas consumption by compcompany according the structure type and location
• Petrol_Consumption_By_Sector(toe): Petrol consumption by the company according the structure type and location
• Region: UK region where company is lcompany is located
• SIC Group: Industrial classification of company group
• Section: Industrial classification of the company section
• Sector: Sector of the company work
• Structure_Type: Structure type of the company

Individual

• individual_ID: Key
• name: First name + Surname
• sex: Individual's gender
• geography: Geography
• postcode: Postcode
• ethic_group: The ethnic group classification presented is the recommended framework from the 'Harmonised Concepts and Questions for Social Data Sources Primary Standards' for presentation of UK outputs on ethnic group
• nationality: Nationality of the individual
• marital_and_civil_partnership_status: Marital and civil partnership status classifies an individual according to their legal marital or registered same-sex civil
• occupation: The person's occupation relates to their main job and is derived from either their job title or details of the activities involved in their job
• Diesel car: Number of dissel car
• Diesel consumption: Diesel consumption per individual
• Electricity consumption: electricity consumption per individual
• Family type: Type of the family individual living in
• Gas Availability: Gas connection availibility
• Gas consumption: Gas consumption of the individual
• House ID: House ID, per family
• House members: Number of house members in house
• Individual type: Type of the Individual
• Motor cycle: Number of Motor cycle present
• Number of bedrooms: Totol number of bedrooms in the house
• Other fuel car: Number of other fuel cars
• Petrol car: Number of petrol cars
• Petrol consumption: Petrol consumption per indivdual
• Region: UK region where family or house is located

Snapshot img

Investor ESG Software Market Size 2025-2029

The investor ESG software market size is forecast to increase by USD 976 million, at a CAGR of 15.7% between 2024 and 2029.

The market exhibits steady growth, driven by the increasing volumes of corporate data. This data influx necessitates advanced software solutions to effectively manage Environmental, Social, and Governance (ESG) information. An emerging trend in this market is the integration of analytics capabilities into investor ESG software. While this offers significant potential for enhanced data insights and improved decision-making, it also necessitates high initial capital investments. A key challenge in the market is ensuring data accuracy and reliability, as ESG data can be complex and difficult to obtain and verify.
Additionally, the integration of various data sources and maintaining data security are significant obstacles that companies must address to effectively leverage investor ESG software. Companies seeking to capitalize on market opportunities and navigate challenges effectively should focus on data accuracy, invest in advanced analytics capabilities, and prioritize data security measures.

What will be the Size of the Investor ESG Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The Environmental, Social, and Governance (ESG) software market continues to evolve, with dynamic market activities unfolding across various sectors. ESG performance indicators, carbon footprint analysis, and social audits are integrated into software solutions, enabling seamless scenario planning and social impact measurement. Reputational risk, long-term value creation, and environmental risk assessment are assessed through data integration and analytics. Sustainable business practices and stakeholder engagement are prioritized, with ESG data management and materiality assessment ensuring transparency and ethical conduct. Risk mitigation strategies, including risk scoring and governance audits, are employed to minimize potential threats. Cloud computing, regulatory compliance, and API integration facilitate data security, privacy, and reporting automation.

Impact investing, due diligence, and investment decisions are informed by ESG data and analytics. Machine learning and artificial intelligence (AI) are utilized for greenwashing detection and performance measurement. Software-as-a-Service (SaaS) offerings enable supply chain traceability, risk management, and reporting frameworks. User experience (UX) and user interface (UI) designs prioritize accessibility and ease of use. Legal compliance and workflow automation streamline operations and enhance operational efficiency. ESG integration is a continuous process, with ongoing market activities shaping the landscape. ESG software solutions adapt to evolving stakeholder expectations and regulatory requirements, ensuring sustainable business practices and stakeholder engagement.

How is this Investor ESG Software Industry segmented?

The investor esg software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Software
  Services


Deployment

  On-premises
  Cloud


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Component Insights

The software segment is estimated to witness significant growth during the forecast period.

The investor Environmental, Social, and Governance (ESG) software market is experiencing significant growth in 2024, driven by the software industry's innovative solutions. These software offerings facilitate the collection, analysis, and reporting of ESG performance indicators, such as carbon footprint analysis, social audits, and financial performance. By integrating ESG data with financial data, investors can make more informed decisions that align with ethical and environmental standards. ESG software solutions also provide risk mitigation strategies, due diligence, and regulatory compliance features, addressing concerns related to reputational risk, long-term value creation, and environmental risk assessment. Furthermore, software-as-a-service (SaaS) platforms enable real-time data access, data security, and privacy, enhancing the user experience (UX) for investors.

Impact investing, governance risk management, and supply chain traceability are essential aspects of ESG investing, and software solutions offer advanced features for these areas. Predictive analytics, scenario planning, social impact measurement, a

As of 2025, Hewlett Packard Enterprise Company was placed in the number-*** spot by the JUST Capital annual survey. This survey reviews America’s largest publicly traded companies in relation to environmental, social, and corporate governance (ESG) responsibility. The survey operated with a sample group of over ***** respondents, revising five major categories, each carrying a different weight. Upon gathering the public opinion of leading publicly traded firms, data was evaluated in relevance to the weighted importance of each ESG category. HP INC. took the ******-place spot in the overall company rankings, receiving *** points in the highest-weighted category, "communities." Evolving investor criteria When reviewing ESG drivers, institutional investors placed significant weight on ESG ratings when making investment choices. While regional taxonomy alignment had minimal impact, ESG ratings emerged as the top factor influencing investment decisions. This shift has indicated a growing sophistication in how investors evaluate companies' sustainability efforts. Interestingly, many investors have developed their own ESG rating criteria when evaluating financial securities, such as ETFs, demonstrating a desire for more tailored and nuanced assessments of corporate responsibility. Consumer preferences driving change The impact of ESG factors has extended beyond the investment world, significantly influencing consumer behavior, particularly among younger demographics. For instance, over ** percent of Gen Z Hispanics in the U.S. consider eco-friendly packaging a key factor in their purchasing decisions. This trend, along with concerns about animal welfare, natural products, and fair labor practices, highlights the growing importance of ESG considerations in shaping market demand. As consumers and investors increasingly prioritize these factors, companies will likely face pressure to improve their ESG performance to remain competitive.

ESG Data Ingestion AI Market Outlook

According to our latest research, the global ESG Data Ingestion AI market size reached USD 2.18 billion in 2024, reflecting a robust demand for advanced solutions in environmental, social, and governance (ESG) data management. The market is expected to grow at a CAGR of 21.7% during the forecast period, reaching USD 15.22 billion by 2033. This remarkable growth is driven by increasing regulatory pressures, the need for transparent ESG reporting, and the integration of AI technologies to automate and enhance data ingestion processes across industries.

One of the primary growth factors for the ESG Data Ingestion AI market is the intensifying regulatory landscape. Governments and regulatory bodies worldwide are mandating stricter ESG disclosures and sustainability reporting, compelling organizations to adopt sophisticated data management solutions. AI-driven data ingestion platforms are proving to be essential in collecting, validating, and integrating vast volumes of ESG data from heterogeneous sources. With the growing complexity of ESG frameworks and the proliferation of data points, manual processes are no longer viable, making AI-powered ingestion solutions indispensable for ensuring data accuracy, consistency, and compliance.

Another significant driver is the rising demand for real-time and actionable ESG insights among investors and corporate stakeholders. Institutional investors are increasingly incorporating ESG criteria into their investment decisions, necessitating accurate, timely, and comprehensive ESG data. AI-powered data ingestion not only accelerates the data collection process but also enhances data quality through automated anomaly detection and normalization. This enables organizations to provide transparent disclosures, demonstrate their ESG commitment, and gain a competitive edge in attracting capital and maintaining stakeholder trust. Additionally, the proliferation of alternative data sources, such as satellite imagery, social media, and IoT sensors, further amplifies the need for advanced AI-driven ingestion technologies.

Technological advancements in AI and machine learning are also playing a pivotal role in the market's expansion. The integration of natural language processing (NLP), computer vision, and advanced analytics into ESG data ingestion platforms allows for the extraction and structuring of unstructured and semi-structured data from diverse sources. This capability is particularly valuable in sectors such as banking, healthcare, and energy, where ESG data is often dispersed across multiple formats and repositories. As organizations seek to streamline their ESG workflows and derive actionable insights, the adoption of AI-powered ingestion solutions is expected to accelerate further, fostering innovation and driving market growth.

From a regional perspective, North America currently dominates the ESG Data Ingestion AI market, accounting for the largest share in 2024. This leadership position is attributed to the region's advanced technology infrastructure, proactive regulatory environment, and strong presence of leading market players. Europe follows closely, driven by stringent ESG regulations and a mature investment ecosystem. The Asia Pacific region is witnessing the fastest growth, propelled by rapid digital transformation, increasing ESG awareness, and government initiatives promoting sustainability and responsible business practices. Latin America and the Middle East & Africa are emerging markets, gradually adopting ESG data ingestion technologies as regulatory frameworks evolve and corporate sustainability gains traction.

Component Analysis

The ESG Data Ingestion AI market by component is segmented into Software, Hardware, and Services, each playing a critical role in enabling organizations to streamline their ESG data management processes. The software segment holds the largest market share, primarily due to the growing demand for AI-powered platforms that automate the ing

ESG DATA PRODUCT DESCRIPTION

Market-leading ESG dataset tracking corporate waste management performance across 4,000+ global companies. Our data provides granular breakdowns of hazardous and non-hazardous waste streams, alongside comprehensive coverage of disposal methods and recovery rates. Through rigorous standardization of waste categories and treatment methods, we enable precise cross-company comparisons and sectoral benchmarking.

ESG DATA PRODUCT CHARACTERISTICS

• Company Coverage:              4,000+ companies • Geographical Coverage:       Global • Sectorial Coverage:                All sectors • Data Historical Range:           2021 - 2024 • Median Data History:             2 years • Data Traceability Rate:           100% • Data Frequency:                     Annual • Average Reporting Lag:         3 months • Data Format:                            Most Recent/Point-in-Time

UNIQUE DATA VALUE PROPOSITION

Uncompromised Standardization

When company waste data do not align with standard waste reporting frameworks, our team of environmental engineers meticulously maps the reported data to the correct waste categories and disposal methods. This guarantees uniformity and comparability across our dataset, bridging the gap created by diverse reporting formats.

Precision in Every Figure

Our advanced cross-source data precision matching algorithm ensures that the most accurate data is always delivered. For instance, an exact figure like 1,542,450 tCO2e is prioritized over a rounded figure like 1,500,000 tCO2e, reflecting our dedication to precision and detail.

Accuracy in Every Metric

Our advanced cross-source data precision matching algorithm ensures that the most accurate data is always delivered. For instance, an exact figure like 15,245 metric tons of waste is prioritized over a rounded figure like 15,000 metric tons, reflecting our dedication to precision and detail.

Unbiased Data Integrity

Our approach is grounded in delivering waste data exactly as reported by companies, without making inferences or estimates for undisclosed data. This strict adherence to factual reporting ensures the integrity of the data you receive, providing an unaltered and accurate view of corporate waste management.

End-to-End Data Traceability

Every data point we provide is directly traceable to its original source, down to the page numbers and exact coordinates within source documents. This level of detail ensures you have access to the most reliable and verifiable waste data available, equipping you with data you can trust completely.

Full-Scope Boundary Verification

We tag waste figures that do not cover a company's entire organizational or operational boundaries with an 'Incomplete Boundaries' attribute. This attribute enhances transparency and ensures the comparability of our data by keeping you informed of any potential limitations.

USE CASES

Asset Management

Utilize waste management data for comprehensive portfolio management, including SFDR and TNFD compliance reporting, sustainability benchmarking, risk analysis, thematic investment strategies focused on circular economy, and stewardship activities. The data enables assessment of waste-related risks, identification of sustainability leaders, and supports engagement with portfolio companies.

Financial Institutions & Banking

Leverage waste data for credit risk assessment, green lending, environmental due diligence, regulatory compliance, and supply chain finance. The data supports evaluation of borrower operational efficiency, structuring of sustainability-linked products, and development of circular economy financing solutions.

FinTech

Develop technology solutions incorporating waste management data, including ESG analytics platforms, sustainability reporting solutions, supply chain analytics tools, impact measurement platforms, and sustainable investment apps for retail investors, enabling comprehensive assessment and monitoring of corporate waste performance.

GreenTech & ClimateTech

Use waste data to power circular economy solutions, waste management software, environmental compliance platforms, and sustainability management software, enabling optimization of waste operations, regulatory compliance monitoring, and comprehensive environmental performance tracking.

Corporates

Employ waste data for performance benchmarking against industry peers, supply chain optimization, sustainability reporting, and procurement strategy development, enabling data-driven decision-making in waste management and circular economy initiatives.

Professional Services & Consulting

Utilize waste data for industry research and benchmarking, ESG advisory services, sustainability strategy development, and regulatory compliance advisory, helping clients improve environmental performance and meet regulatory requirements.

Research & Academia

Analyze waste management data for enviro...

As ESG investing has gone mainstream in the public equity space, the spotlight has turned to fixed income investments and sovereign bonds in particular. Investors increasingly recognize that ESG factors, such as corruption, climate protection, and human rights, could impact the long-term solvency of government bond issuers.

ISS ESG’s Country Controversy Assessment enables investors to assess a country’s exposure to various controversies, including alignment with international norms and conventions, to effectively manage potential ESG risks and opportunities. The assessment covers various ESG factors across the following themes:

• Authoritarian Regime • Biodiversity • Child Labour • Climate Protection • Coal Power • Corruption • Death Penalty • Discrimination • Euthanasia • Freedom of Association • Freedom of Speech & Press • Global Peace Index • Human Rights • Labour Rights • Military Budget • Money Laundering • Nuclear Power • Nuclear Weapons • Whaling

Coverage for the Country Controversy Assessment includes more than 800 sovereign issuers:

• Approximately 100% coverage of global sovereign debt issued • More than 120 countries as well as Hong Kong and the European Union • All member countries of the European Union and the OECD

Analysts gather the controversy-related information from credible and acknowledged external sources, such as indices and blacklists, and the ISS ESG Country Rating to deliver high-quality, relevant and actionable data.

Examples of sources:

• Amnesty International • Financial Action Task Force • Germanwatch • Stockholm International Peace Research Institute

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

As of October 6, 2025, the S&P 500 and the S&P 500 ESG index exhibited similar performance; both indexes were weighted to similar industries, as the S&P 500 followed the leading 500 companies in the United States. Throughout 2025, the S&P 500 ESG index steadily outperformed the S&P 500 by ***** points on average. During the coronavirus pandemic, the technology sector was one of the best-performing sectors in the market. The major differences between the two indexes were that the S&P 500 ESG index was skewed towards firms with higher environmental, social, and governance (ESG) scores and had a higher concentration of technology securities than the S&P 500 index. What is a market capitalization index? Both the S&P 500 and the S&P 500 ESG are market capitalization indexes, meaning the individual components (such as stocks and other securities) weighted to the indexes influence the overall value. Market trends such as inflation, interest rates, and international issues like the coronavirus pandemic and the popularity of ESG among professional investors affect the performance of stocks. When weighted components rise in value, this causes an increase in the overall value of the index they are weighted too. What trends are driving index performance? Recent economic and social trends have led to higher levels of ESG integration and maintenance among firms worldwide and higher prioritization from investors to include ESG-focused firms in their investment choices. From a global survey group, over ********* of the respondents were willing to prioritize ESG benefits over a higher return on their investment. These trends influenced the performance of securities on the market, leading to an increased value of individual weighted stocks, resulting in an overall increase in the index value.

InvestVerte is an independent ESG and corporate governance research, rating and analytics company which provides information to help investors around the world make the best investment decisions.

Created in 2020, InvestVerte is a young, innovative company which builds on firm foundations, adaptability and artificial intelligence. Nowadays, sustainability in business is essential; InvestVerte is here to help it’s customers evaluate companies and choose those that best match their needs. Composed of a dynamic team with more than 15 years of data, the company’s main advantage is its ability to adapt and respond to its customers’ requirements. Putting customer relationships at the forefront, the firm aims to develop itself through strong collaborations.