Decade-Long Analysis of Sustainable Development Goals Compliance and Financial Performance Tiers in All Banking Companies Listed on Bursa Malaysia DOI: https://doi.org/10.33093/ijomfa.2025.6.1.2
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Abstract
This study examines the relationship between Sustainable Development Goals (SDGs) compliance and financial performance in Malaysian banks from 2013 to 2022. Using advanced machine learning techniques, including Support Vector Machines, Decision Trees, K-nearest Neighbours, Extra Trees, Gradient Boosting, and Random Forests, banks were classified into financial performance tiers. Gradient Boosting was the most effective, achieving 80% accuracy in categorising medium and low-performance tiers. Significant correlations were found between SDGs 10 and 15, as well as financial metrics like market capitalisation and asset turnover. These findings highlight the benefits of integrating specific SDGs into banking strategies and the need for supportive policy frameworks, contributing to a deeper understanding of sustainable banking practices.
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