Strategic Focus: Leveraging ESG Data Sources, Analytics And AI In ESG Solutions
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Executive Summary
Businesses are increasingly using ESG and sustainability data to inform a growing list of decisions related to capital spending, supplier selection, strategy development, product development, performance benchmarking and risk and opportunity management. Customers and investors are also using ESG data to make purchasing and investment decisions. This report presents an overview of the ESG and sustainability data landscape, evaluates data sources and offers considerations for users who are increasingly critically dependent on this information for decision-making. Sustainability, finance and technology executives can use this report as part of their ESG digital strategy development.
Table of contents
Leveraging ESG data sources, analytics and AI to drive transparencyThe ESG and sustainability data landscape
Evaluating ESG and sustainability data sources
Advancements driving ESG data transparency and quality
Applying AI to enhance data quality and enable informed decision-making
Table of figures
Figure 1. ESG information architecture and data sourcesFigure 2. Evaluating the transparency of ESG data sources
Figure 3. ESG ratings agencies and rankers: methodology transparency
Figure 4. Incorporating AI for ESG decision-making
Organisations mentioned
Arcadia, Benchmark Gensuite, Bloomberg, C3 AI, CDP, Center for Audit Quality, Compliance & Risks, Copperleaf, Databricks, Datamaran, DataRobot, EcoVadis, Enhesa, ERM, European Commission, European Securities and Markets Authority (ESMA), GIST Impact, Global Reporting Initiative (GRI), H&M, IBM, ISS, JUST Capital, Lythouse, Moody’s, MSCI, NASDAQ, Planon, Refinitiv, RepRisk, S&P Global, Snowflake, Sustainalytics, Task Force on Climate-related Financial Disclosures (TCFD), Tesla, UK Financial Conduct Authority (FCA), Urjanet, US Securities and Exchange Commission (SEC), VelocityEHS, Volkswagen, YuzeData, ZycusAbout the authors
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