AI-powered credit risk assessment in development finance: Opportunities and ethical challenges in emerging markets

Boafo, John Akwetey and Avevor, Maud and Danzerl, Noble Osei Poku (2025) AI-powered credit risk assessment in development finance: Opportunities and ethical challenges in emerging markets. World Journal of Advanced Research and Reviews, 26 (3). 068-074. ISSN 2581-9615

This discussion paper critically reviews the use of artificial intelligence (AI) in credit risk assessment in development finance institutions (DFIs) in emerging markets. The main goal is to assess the opportunities and ethical challenges of AI driven models for financial inclusion. Using secondary data synthesis, case studies and global policy frameworks, the paper examines how machine learning and alternative data sources can improve predictive accuracy, increase credit access and improve DFI operations. It also points out systemic risks such as algorithmic bias, data privacy violation, lack of transparency and technological dependency. The study suggests that responsible AI adoption requires inclusive data strategies, explainable AI frameworks, regulatory harmonization, local capacity building and improved digital literacy. The paper presents a roadmap for using AI as a tool to create equitable and resilient financial ecosystems in low- and middle-income countries by aligning AI deployment with Sustainable Development Goals and ethical governance.