This study aims to explore the integration of digital technologies in sustainability reporting practices for small and medium-sized enterprises (SMEs) through the approach adopted by an Italian cooperative bank committed to ethical finance. It employs a dual evaluation framework combining traditional financial assessments with rigorous socio-environmental evaluations (VSA, Value and Sustainability Assessment) to ensure SMEs meet high social and environmental responsibility standards. The study employs a mixed method, joining a qualitative case study and a quantitative correlation analysis. Studying data from 3,431 socio-environmental questionnaires and semistructured interviews with key bank figures and their correlation. It highlights the role of Artificial Intelligence (AI)-driven Environmental, Social and Governance (ESG) rating systems and automated social reports in providing real-time socio-environmental performance assessments and aligning SMEs with Sustainable Development Goals (SDGs). The results demonstrate a correlation between higher ESG scores and a lower probability of default (PD), showcasing the financial benefits of ESG practices. Trained social assessors and digital tools enhance transparency, accountability and decision-making for SMEs. This study advances the literature on ESG integration and digital transformation by emphasizing the practical impact of AI tools on SMEs' sustainability reporting. It uniquely examines the link between ESG performance and financial stability.
Evaluating sustainability reporting in SMEs: insights from an ethical cooperative bank’s approach
Degregori, Ginevra;Brescia, Valerio
;Calandra, Davide;Secinaro, Silvana
2025-01-01
Abstract
This study aims to explore the integration of digital technologies in sustainability reporting practices for small and medium-sized enterprises (SMEs) through the approach adopted by an Italian cooperative bank committed to ethical finance. It employs a dual evaluation framework combining traditional financial assessments with rigorous socio-environmental evaluations (VSA, Value and Sustainability Assessment) to ensure SMEs meet high social and environmental responsibility standards. The study employs a mixed method, joining a qualitative case study and a quantitative correlation analysis. Studying data from 3,431 socio-environmental questionnaires and semistructured interviews with key bank figures and their correlation. It highlights the role of Artificial Intelligence (AI)-driven Environmental, Social and Governance (ESG) rating systems and automated social reports in providing real-time socio-environmental performance assessments and aligning SMEs with Sustainable Development Goals (SDGs). The results demonstrate a correlation between higher ESG scores and a lower probability of default (PD), showcasing the financial benefits of ESG practices. Trained social assessors and digital tools enhance transparency, accountability and decision-making for SMEs. This study advances the literature on ESG integration and digital transformation by emphasizing the practical impact of AI tools on SMEs' sustainability reporting. It uniquely examines the link between ESG performance and financial stability.File | Dimensione | Formato | |
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