This paper explores innovative credit management and risk reduction strategies enabled by artificial intelligence (AI) and financial technology (fintech) in the context of microfinance institutions (MFIs) and small and medium-sized enterprises (SMEs). It highlights the limitations of traditional credit management practices, such as reliance on limited data and inefficiencies in risk assessment, which often exclude underserved populations. Lenders can enhance decision-making, improve operational efficiency, and mitigate default risks by leveraging AI-driven credit scoring, fintech platforms, and blockchain technology. Borrowers benefit from increased access to credit, personalized financial products, and improved financial literacy. Despite these advancements, challenges such as high implementation costs, data privacy concerns, and regulatory gaps remain significant barriers. This paper emphasizes the need for collaboration among financial institutions, policymakers, and technology developers to address these challenges and fully realize the transformative potential of AI and fintech in creating an inclusive and resilient financial ecosystem.
Credit management, Risk reduction, Artificial intelligence, Fintech, Microfinance institutions
IRE Journals:
Hope Ehiaghe Omokhoa , Chinekwu Somtochukwu Odionu , Chima Azubuike , Aumbur Kwaghter Sule
"Innovative Credit Management and Risk Reduction Strategies: AI and Fintech Approaches for Microfinance and SMEs" Iconic Research And Engineering Journals Volume 8 Issue 6 2024 Page 686-695
IEEE:
Hope Ehiaghe Omokhoa , Chinekwu Somtochukwu Odionu , Chima Azubuike , Aumbur Kwaghter Sule
"Innovative Credit Management and Risk Reduction Strategies: AI and Fintech Approaches for Microfinance and SMEs" Iconic Research And Engineering Journals, 8(6)