Non-Financial Disclosure and Economic Performance of Top Italian Listed Banks

Abstract

This study aims to analyze the relationships between the economic performance of Italian listed banks and their GRI disclosure (GRID), understood as the level of disclosure of their non-financial reports according to the GRI standards. The study selected 6 among the Italian listed banks with the highest capitalization as of 31/12/2020 and analyzed the relationships between their economic performance and their GRID by applying three models: Linear Regression, Support Vector Machines, and Decision Trees. The research highlighted the existence of positive relationships between the economic performance of banks – measured in terms of capitalization, size and leverage – and their GRID, while the relationship with profitability is negative. Unlike the analyzes that see disclosure as a factor capable of improving economic performance, this research starts from the assumption that the best economic performance favors a wider disclosure. Furthermore, the study applies machine learning which represents a non-traditional methodology, not yet fully exploited in the field of sustainability reporting. JEL classification numbers: M21. Keywords: Non-Financial reporting, GRI standards, Banking sector, Economic performance, Machine learning.