Artificial Intelligence in Banking as a Driver of Financial Inclusion for Reducing Poverty and Inequality - A Conceptual Framework

Abstract

Over the last decade, the banking sector has experienced a push to transform traditional system into a digitised and efficient system, which is driven by advances in Artificial Intelligence (AI) and data-driven technologies like Machine Learning. Traditional, rule-based banking systems are increasingly being replaced by intelligent and automated solutions that enhance efficiency, scalability, and outreach. Among these transformations, the use of AI in banking has emerged as an important mechanism for promoting financial inclusion, with significant implications for poverty reduction and inequality mitigation. This chapter study the role of AI-powered banking systems in offering access to formal financial services for underserved and marginalized population. Drawing on an extensive review of contemporary academic literature, the study conceptually analyses how the AI-powered applications in banking, such as machine learning-based credit scoring, fraud detection systems, digital onboarding, NLP chatbots, and personalized financial analytics—contribute to improved access, usage, quality, and affordability of financial services. The chapter further explores how enhanced financial inclusion acts as a mediating mechanism through which AI-enabled banking contributes to broader socioeconomic outcomes, particularly poverty reduction and reduced inequalities. In addition, the chapter critically discusses ethical, regulatory, and governance challenges related AI adoption in banking, including issues of algorithmic biasness, data privacy, transparency, and accountability. Most of the focus is placed on the importance of responsible and explainable AI frameworks to ensure that technological advancements do not reinforce existing social and economic disparities. Building on these insights, the chapter proposes a comprehensive conceptual framework that integrates AI-enabled banking capabilities, financial inclusion dimensions, and development outcomes within a sustainability-oriented perspective. This study adopts a conceptual and literature-based analytical approach, synthesizing insights from prior empirical studies and interdisciplinary research. By positioning AI in banking as a strategic driver of inclusive and sustainable development, the chapter contributes to the growing discussions on digital finance and provides valuable theoretical and policy-relevant insights for researchers, practitioners, and policymakers.

Keywords: Artificial Intelligence, Banking, Financial Inclusion, Poverty Reduction, Inequality, FinTech, Sustainable Finance, Responsible AI