AI-DRIVEN CREDIT RISK ASSESSMENT FOR SMES: A FRAMEWORK FOR FINANCIAL INCLUSION AND RESPONSIBLE INNOVATION

Abstract

The global financial landscape is undergoing a structural redefinition powered by artificial intelligence (AI) and machine learning (ML). Small and medium-sized enterprises (SMEs)—the backbone of emerging economies— continue to face severe credit restrictions due to obsolete risk models dependent on collateral and historical data. This research introduces an integrated, AI-driven credit risk assessment framework specifically designed to foster financial inclusion through the strategic utilization of alternative data, advanced analytics, and principles of responsible innovation

The research investigates the limitations of conventional models, reviews global case studies of AI adoption in SME financing, and introduces a conceptual model tailored for Pakistan’s financial ecosystem. Methodologically, it combines theoretical synthesis with policy analysis, drawing on comparative insights from India, Kenya, and China. Findings suggest that AI-enabled systems can improve predictive accuracy, reduce default risk, and foster inclusive lending practices when implemented under robust governance and ethical oversight. The study concludes by outlining a roadmap for regulators and financial institutions to embed AI responsibly into credit infrastructures, ensuring equitable access to finance for SMEs while safeguarding transparency, accountability, and data privacy.