Decade-Long Analysis of Sustainable Development Goals Compliance and Financial Performance Tiers in All Banking Companies Listed on Bursa Malaysia
Year: 2025
Type: article
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.
Authors: Universiti Sains Malaysia, Malaysia, Kien Seng Lok, Khai Wah Khaw, Universiti Sains Malaysia, Malaysia, XinYing Chew, Universiti Sains Malaysia, Malaysia, Wei Chien Ng, Universiti Sains Malaysia, Malaysia
Institution: Universiti Sains Malaysia
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4408099975