Artificial Intelligence As A Catalyst For Green Banking Performance: A Conceptual Framework For Sustainable Banking

The increasing emphasis on environmental sustainability has encouraged financial institutions to adopt green banking practices that support environmentally responsible operations and sustainable finance objectives. Simultaneously, advances in Artificial Intelligence (AI) have transformed the banking sector by enhancing operational efficiency, decision-making capabilities, risk management, and customer service. Despite growing scholarly interest in both AI and green banking, existing research has largely examined these domains independently, resulting in limited understanding of how AI contributes to green banking performance. This study addresses this gap by developing a conceptual framework that explains the role of AI as a catalyst for enhancing green banking performance. Drawing upon literature related to artificial intelligence, green banking, sustainable finance, ESG governance, and digital transformation, the study proposes a four-dimensional framework consisting of AI Capabilities, Green Banking Enablers, Green Banking Performance, and Sustainable Banking Ecosystem. The framework suggests that AI capabilities such as machine learning, predictive analytics, natural language processing, and intelligent automation facilitate environmentally responsible banking practices through paperless banking, resource optimization, sustainable lending, environmental risk assessment, and ESG monitoring. These mechanisms contribute to improved green banking performance and support the development of a sustainable banking ecosystem. The study contributes to the literature by integrating AI and green banking within a unified theoretical perspective and identifying future research directions for scholars and practitioners. The findings highlight the strategic importance of AI in supporting sustainable banking transformation and advancing environmental sustainability objectives within the financial sector.