ESG Data Guide 2023

Harnessing the power of AI and big data

Environmental Finance: What are FactSet’s AI solutions in the space?

Hendrik BartelHendrik Bartel: Truvalue Labs, a FactSet company, focuses on harnessing AI and big data to provide financial professionals with actionable information on how companies are behaving pertaining to issues like carbon emissions, labour relations, data security, and product quality, to name a few. We leverage complex algorithms that sift through millions of data points (e.g., articles, blogs, social media posts, and legal filings) to help our users uncover ESG information hidden in over 100,000 sources of unstructured, third-party data in 13 languages.

The powerful AI behind our products results in over 300,000 signals generated monthly, as well as four key scores across 26 ESG categories and 16 United Nations Sustainable Development goals (SDGs). Our AI-driven analysis is distinguished by the fact that to avoid greenwashing it mines sources but does not consider companies’ own ESG statements.

Furthermore, analysis is produced in real time, thus enabling subscribers to gauge direction of travel for positive or negative ESG investments.

EF: Is AI the answer to ESG data challenges?

HB: No, AI is not the answer. AI and machine learning are computer science methodologies that allow us to understand context between disparate datasets or allow us to extract structured data from unstructured documents. AI is a set of technologies that can be applied to problems, allowing us to find new solutions.

Yes, AI is a tool in the toolbox but in this case, not the “be all, end all.”

EF: How exactly can AI allow investors to better understand ESG data and analyse risks and opportunities?

HB: Technology gives us the ability to build a more objective data process. It is also highly scalable and allows us to uncover insights in real time. The use of AI and machine learning benefits the capital markets industry by providing more efficient ways to mine massive amounts of unstructured data and enabling us to deliver the most important and financially material insights to our customers.

EF: Which tasks can be automated?

HB: There is a long list of very granular tasks that can be automated but, to summarise, FactSet is building and delivering the most efficient, scalable and highly integrated front-to-back ESG data and solutions suite. AI and machine learning technologies allow us to be more efficient and scalable when it comes to extracting data from unstructured sources. It also allows us to find connections between different data points, and even in datasets where we wouldn’t have found connections before. This gives us the ability to make disparate data more valuable and uncover the insights hidden within it.

EF: How are the parameters of such programs set and how can bias or issues be both identified and avoided?

HB: This is something we have thought about for a long time. I would be more inclined to call a manual collection and analysis process more biased and subjective, as this has been established in numerous academic papers when comparing the assessments of multiple traditional ESG providers with each other.

Using modern computing technology allows us to build an objective pipeline from data collection to data analysis, with the ability for humans to step into the process at any point in time for random sampling. These random samples and a careful topic curation process allow us to iteratively improve on data quality and on the breadth of topics we cover.

EF: What are sentiment analysis, natural language processing (NLP) and deep learning and how can they help in this context?

HB: Sentiment analysis allows the machine to infer the overall sentiment or mood of an entire document, phrase, paragraph, and so forth. This is done by a complex calculation of words being used in a sentence or document, distance between words, and more. This technology is helpful for downstream processing and general understanding of a document. It is also a branch of NLP.

NLP is a field of computational linguistics – it is technology that programs computers to understand large amounts of text similar to how a human would understand it.

Deep learning is a branch of machine learning, which in itself is a branch of AI. Deep learning uses multiple layers of neural networks, whereas machine learning uses a single layer neural network. This technique is used to understand the context and connectivity between different datasets.

Guide entries by FactSet Research Systems Inc.

Verification (Third Party)

Carbon Emissions Scope 3 footprint

Modern Slavery footprint

Species extinction-risk footprint

TIDE

iSA, iS, impak Score™, SFDR+i

Rainforest Alliance & Conservation International

Mettle Capital ESG Risk platform

MIS Second Party Opinion

nZero

Seafood Database

Second Party Opinion

ESG Rating, Reporting and Advisory

Climate and environment data hub

Sustainability Copilot

ESGSignals®

Sanctify ESG

Asset-level Indicators

Asset-based Analytics

Asset-based Company Indicators – Essential and Advanced

Bloomberg Sustainable Finance Solutions

India ESG datasets [BRSR taxonomy available]

9fin ESG

CLIMATE RISK IMPACT SCREENING (CRIS) for Climate Physical Risk

CARBON IMPACT ANALYTICS (CIA) For climate transition risk

CDP 2022 GHG Raw Emissions Dataset

CDP 2022 Full GHG Modelled Emissions Dataset

CDP 2022 Risks and Opportunities Dataset

CDP 2022 Scores

CDP 2022 TCFD-Aligned Climate Change Dataset

CDP 2022 Temperature Ratings

ChemScore

Global Landscape of Climate Finance

ESG Portfolio Check

Sustainable Finance Ai Suite (ESG, EU Taxonomy, Supply Chain Risk)

ESG Lead

Horizon

EF Data

Equileap Gender Equality Data

Ethical Screening Portal

OneTrack

Coller FAIRR Protein Producer Index

ESG research, data and reporting solutions

Forests & Finance

Forest 500

GLYNT

Greenomy EU Taxonomy/SFDR/EET Solution

Corporate Ratings

ETF Fund Ratings

Issuer ESG and SDG Benchmarking

Municipal Bond Data and Ratings

US Retirement Plans, including 401(k) and 403(b)

Integrated Biodiversity Assessment Tool

CBF – Corporate Biodiversity Footprint

SB2A – Science-Based 2°C Alignment

Global Impact Database

FinanceMap

LobbyMap

ESG Impact Rating

Green Bond Transparency Platform (GBTP)

Investverte

Corporate Governance Information Search

JPX ESG Indices

LGX DataHub

Climate Data by Moody’s

ESG Data by Moody’s

Nasdaq Sustainable Bond Network

Nasdaq ESG Data Hub

Nasdaq ESG Data Portal

Nasdaq ESG Footprint

Informe Anual OFISO

ESG Solutions

Resolution Database

Second Party Opinions

SDI Asset Owner Platform

ESG Disclosures and Sustainability Report Assurance

Second-Party Opinions on Sustainable Bonds and Loans

Supply Chain ESG Risk Platform

UN SDG Impact Assurance

SIGWATCH

Sugi

SustainaBase

Sustainable Fitch ESG Ratings

Geospatial ESG Solutions

Sovereign ESG Ratings

MARK

White Stag Investing Investment Research in Water, Oceans and Biodiversity

ClimateWatch

Forest Atlases

Global Forest Watch

Global Forest Watch Pro

LandMark

PREPdata

Resource Watch

WRI Aqueduct

Carbon Footprinting and Science-based Targets Support

Second Party Opinion - Thematic Bonds and Loans & Impact Assessment

TCFD Advisory and Support

Carbon & Climate Data

Carbon Footprint Report

Climate Impact Report

Net Zero Solutions

Climate Scenario Analysis and Implied Temperature Score

Climate Physical Risk

Transition Risk

Climate Advisory Services

Potential Avoided Emissions Data

Energy & Extractives Screening

Norm-Based Research

Country Screening

Sector-Based Screening

Country Controversy Assessment

Director Data

Executive Compensation Analytics

Voting Analytics

Governance QualityScore

E&S Disclosure QualityScore

ESG Muni QualityScore

Carbon Risk Rating

ESG Corporate Rating

ESG Country Rating

SDG Solutions Assessment

SDG Impact Rating

ESG Fund Rating

Water Risk Rating

Biodiversity Impact Assessment Tool

ESG Index Solutions

EU Taxonomy Alignment Solution

SFDR Principle Adverse Impacts Solution

Regulatory Sustainable Investment Solution

ESG Portfolio Analysis

ESG Raw Data

Global Sanctions Screening

Responsible Investment Policy Development

EVA (Economic Value Added)

Climate Voting Policy

Custom Climate Voting Factors

Bespoke Research & Advisory Solutions

ESG Scorecard

Controversial Weapons Research

CIARA – Carbon Impact Analytics for Real Assets

CDP 2022 Forest Corporate Response Dataset

CDP 2022 Water Security Corporate Response Dataset

Net Zero Finance Tracker

Sustainable Economy Intelligence

ESG Ratings & Analysis

SDG Analysis

Net Zero Analysis

Fund Due Diligence and SDR Labelling Reports

Ethical Research

Sustainable Funds Portal

ESG RATINGS

Coller FAIRR Climate Risk Tool

ESG Solutions

Fund EET Data

Fathom’s Product Stack

ENCORE

Trase Finance

Dependency scores

Climate Positive Impact

Positive Impact Biodiversity

Carbon Footprint

Empirical ESG and Impact Data

Real Asset Analysis

ESG Newsroom

Norm-Based Engagement

Thematic Engagement

ESG Custom Rating

Cyber Risk Score

European ESG Template Solution

Environmental & Social Raw Data

Sustainability Insights Suite

ESG Reporting Platform for VC

ESG Solutions by MSCI

Climate and Net-Zero Solutions by MSCI

Biodiversity Solutions by MSCI

Sustainability Solutions for Corporates and Advisors

KaleidoScope

Rating Watch

Vision

ESG GPS X-Ray

A-Cubed

ESG GPS ratings

Data for Nature Insights

Fund EcoMarket

State Street Risk Analytics Platform

TSC Water Security Index

SDG Impact for Public Companies

Universal Impact

Climate Ready Farms

Energy Access Explorer

MapBuilder

Ocean Watch

Water, Peace and Security - Global Early Warning Tool 

Global Water Watch

WRI Open Data Portal

Systems Change Lab

Open Timber Portal 

ESG Clarified

WWF Risk Filter Suite

ICE Climate Physical Risk Data

ICE Climate Transition Analytics Tool

ICE ESG Company Data

European ESG Template (EET) solution

ICE Emissions & Targets Data

ICE ESG Geo-Analyzer Tool

ICE Impact Bond Classification Service

SFDR Principal Adverse Impact (PAI) Data

Task-force for Climate-related Financial Disclosure (TCFD) Data

ICE UN Sustainable Development Goals (SDGs) Data – Municipal Bonds

News Aggregator/Controversies Monitoring Tool

ESG Research and Data Services

SPOTT

CDP 2022 Climate Change Corporate Response Dataset

Green Bond Database

Social and Sustainability Bond Database

DEEP Value©

Benchmark ESG Disclosure Dataset

ASSET Tool

Modern Slavery Scorecard

LSEG Sustainable Finance and Investment Solutions

imug rating ESG-Investments

Briink AI ESG Copilot

ESG Relevance Scores

Climate Wisdom by Riskthinking.ai

ESG, Climate & Nature

Global Integrated Energy Model

Clean Energy Procurement Service

Corporate Emissions Solution

Intentionality and Stewardship Data (Wealth)

Climate Data for Companies and Funds

Second Party Opinions

Product Involvement and Impact Metrics for Companies and Funds

Low Carbon Transition Ratings

EU Action Plan Solutions

ESG Risk Ratings

Physical Climate Risk Metrics

FactSet's ESG Investing Solutions

Physical Risk Analytics

Clarity AI Sustainability Tech Kit

AssetWisdom™ by Riskthinking.ai

BIODIVERSITY IMPACT ANALYTICS POWERED BY THE GLOBAL BIODIVERSITY SCORE™ (BIA-GBS) for the biodiversity impact and dependencies of companies

NEC metric “Net Environmental Contribution”