Artificial intelligence and credit access among microfinance institutions in developing economies

This paper develops a conceptual framework to examine the effect of artificial intelligence (AI)–enabled credit scoring on credit access in microfinance institutions within emerging economies. Traditional credit assessment methods often exclude low-income individuals due to limited financial histories, thereby constraining financial inclusion. AI-enabled credit scoring leverages alternative data and machine learning techniques to evaluate creditworthiness more inclusively and efficiently. This paper argues that AI-driven credit scoring enhances credit access by reducing information asymmetry and improving risk assessment accuracy. It further identifies key mediating mechanisms and moderating conditions influencing this relationship. The study contributes to the literature by proposing a theoretically grounded model that links AI adoption in microfinance to financial inclusion outcomes and highlights critical policy considerations.