Enriching the green economy through sustainable investments: An ESG-based credit rating model for green financing

Environmental, social, and governance (ESG) measures have grown significantly as sustainable investment has become a key driver of capital allocation. Sustainable investment is one of the main agendas for fulfilling sustainable development. Thus, financial institutions can significantly tackle socio-ecological concerns by recognising socially conscientious borrowers for long-term investments. They can invest in or lend to enterprises involved in sustainable development to construct a sustainable future. Unfortunately, financial institutions confront several obstacles in selecting such borrowers from a large pool of applicants. To accomplish the goal of sustainable investments, this study proposes an ESG-based credit rating model that considers a firm's ESG performance. The suggested model was built by applying the fuzzy Best Worst Method (BWM) and the newly developed fuzzy Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) Sorting. The fuzzy BWM was used to determine the weight of criteria, while the fuzzy TOPSIS-Sorting was used to evaluate firms against the identified criteria. A practical case has been demonstrated to show the utility of the proposed model. This study identifies the financial pillar as the most important, accounting for 43% of the overall importance, followed by the environmental pillar (24%), the social pillar (19%), and the governance pillar (14%). The suggested credit rating model has shown an accuracy rate of 84.31% and a true positive rate of 87.5%. Regarding policy implementations, financial institutions, regulators, and other authorities may employ it to assist sustainable investments in fulfilling sustainable development goals. Banks may use the suggested method to calculate the capital required under the internal rating-based approach of Basel norms. [Display omitted] •Financial institutions can address socio-environmental concerns through sustainable investments in fulfilling SDGs.•Integrating environmental, social and governance with financial measures may facilitate identifying sustainable borrowers.•An expert-driven credit rating model is proposed to address the issue by employing fuzzy-BWM and fuzzy-TOPSIS-Sorting.•The model shows an accuracy rate of 84.31% and can be used to identify sustainable borrowers toward sustainable investments.