Abstract
This paper talks about the disruptive influence of artificial intelligence (AI) on the world's credit markets, focusing on how it has the potential to transform lending through enhanced risk analysis, accelerated decision-making, and improved financial inclusion. The traditional credit scoring models have long excluded underserved segments, but AI-driven platforms use alternative data and advanced machine learning to bridge such gaps. By investigating literature, policy debates, and case studies of both developed and emerging economies, the study discusses the opportunities and risks of AI lending. Among the striking themes are algorithmic bias, data privacy, systemic risk, regulatory dilemmas, and the balance between efficiency and consumer protection. Evidence suggests that AI lending can profitably serve thin-file borrowers and expand inclusion but that its long-term success depends on explainable models, good governance, and global regulatory harmonization. The paper concludes by speculating that the future of AI lending will lie in finding a balance between risk management, speed of credit delivery, and inclusive access to finance.
Keywords
AI Lending, Credit Markets, Financial Inclusion, Alternative Data, Explainable AI, Algorithmic Bias, Risk Management, Fintech, Digital Credit, Regulatory Governance
Citations
IRE Journals:
Temitope Hundeyin "AI-Driven Lending Platforms: Balancing Risk, Speed, And Inclusion in Global Credit Markets" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 2352-2357
IEEE:
Temitope Hundeyin
"AI-Driven Lending Platforms: Balancing Risk, Speed, And Inclusion in Global Credit Markets" Iconic Research And Engineering Journals, 9(6)
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