AI-Driven Solutions in Microfinance Banking: Enhancing Credit Scoring, Loan Management, and Risk Mitigation in Financially Vulnerable Markets

Research examines artificial intelligence AI effects on microfinance by studying its functions to improve credit accessibility together with risk evaluation and fraud prevention. The investigation seeks to comprehend AI-based financial systems for both loan application strengths and risk reduction together with their inclusionary effects on marginalized customer groups. A combination of methods in research includes literature reviews with case studies taken from different areas across the world to evaluate the effectiveness of AI in microfinance operations. AI-based credit scoring boosts loan processing rates as well as security levels and cuts down fraudulent activities more effectively than human-run systems. AI-risk assessment models deliver better accuracy which leads financial institutions to offer better inclusion to customers while decreasing default rates.The prevailing issues along with algorithmic bias combined with data privacy matters and regulatory difficulties constrain the general use of artificial intelligence across microfinance institutions. The study calls for both improvable AI systems which demonstrate their mechanisms transparently and additional robust regulations to handle ethical issues. Research going forward needs to examine how AI technology affects financial stability together with borrower conduct as well as the social-economic consequences of AI-powered microfinance programs. The study strengthens studies about AI's financial revolution by demonstrating the importance of both innovative advancements and regulatory oversight for creating worthwhile returns with reduced dangers.