Projects

SESG: Integrated Platform for Enhanced Analysis of Environmental, Social, and Governance (ESG) Reports

A Platform for Analysing ESG Data in Non-Financial Reports

Funding: ICSC Innovation Funds

Enabling technology: Artificial Intelligence, LLM

Sustainable Development Goals

SESG aims to develop a platform for analysing ESG data contained in non-financial reports, with the goal of identifying common practices, assessing the robustness of the metrics used, and evaluating whether the reuse of certain indicators could distort ESG scores. The use of advanced analytics, natural language processing and large language models simplifies access to ESG reports, enabling comparative analysis and more informed decision-making.

The project is part of the Italian Research Center on High Performance Computing, Big Data and Quantum Computing, funded by the European Union through NextGenerationEU and by Italy’s National Recovery and Resilience Plan, Mission 4, Component 2.

Italian Research Center on High Performance Computing Big Data and Quantum Computing (ICSC), project funded by European Union – NextGenerationEU – and National Recovery and Resilience Plan (NRRP) – Mission 4 Component 2.

Objectives

The project aims to develop a platform supporting the analysis of non-financial transparency disclosures related to ESG data.

The system will make it possible to simulate and assess the consistency of indicator data using real-world scenarios. This responds to the need for a more accurate, measurable and structured approach to understanding and developing ESG reports.

Initial Challenge

ESG indices play an increasingly important role in assessing the impact of companies in relation to sustainability issues.

Organisations are increasingly expected to define and implement sustainability-related practices and objectives and to report transparently on the progress made. At the same time, the growing complexity and volume of ESG data require more sophisticated tools for their analysis, interpretation and practical application.

The project addresses this challenge by seeking to improve the reliability, comparability and usability of the information contained in non-financial reports.

Solution

ESG reporting will be enhanced through the development of a model capable of understanding and analysing all the elements involved in the preparation of ESG reports.

The solution will use new generative AI models and large language models to extract, interpret and compare relevant information. These technologies will support the development of an interactive dashboard based on the digital twin reference model developed within Spoke 9.

Benefits

The project will provide tools for assessing the ethical validity and impact of ESG metrics.

The resulting ESG data and analyses will support banks and financial service providers in evaluating corporate credit risk and assessing companies’ ability to adapt to climate-related risks.

The platform will also:

increase awareness and understanding of ESG metrics;
improve the evaluation of compliance with sustainability requirements;
support more reliable comparisons between companies and reports;
strengthen the use of ESG information in financial and strategic decision-making.