Artificial Intelligence in Credit Decisioning: Regulatory Challenges of Algorithmic Lending and Financial Inclusion in Developing Economies by Faloore Samuel Ayomide

The global financial architecture is undergoing a structural transformation driven by the convergence of artificial intelligence (AI), mobile ubiquity, and algorithmic credit assessment. This report provides an exhaustive analysis of this paradigm shift, specifically examining the friction between rapid technological innovation and the nascent regulatory frameworks in developing economies. As of 2025, the digitization of finance has brought 40% of adults in developing economies into the formal savings net-a 16-percentage-point increase since 2021-and enabled 84% of adults in low-and middle-income countries (LMICs) to leverage mobile phones for economic activity. Yet, this expansion has precipitated a crisis of governance, characterized by algorithmic bias, predatory lending practices, and systemic opacity. This document dissects the technical mechanisms of modern credit scoring, moving beyond the superficial understanding of "AI" to explore the specific deployment of Gradient Boosted Decision Trees (GBDTs) like XGBoost and Deep Learning architectures such as Long Short-Term Memory (LSTM) networks in credit risk modeling. It contrasts these "black box" methodologies with the growing legal mandates for explainability found in jurisdictions like Brazil and India. Furthermore, it analyzes the gendered dimensions of this revolution, challenging the neutrality of algorithms by exposing how "digital footprints" can act as proxies for historical discrimination, while simultaneously highlighting how gender-disaggregated data is being used to prove the superior repayment performance of women borrowers. The core of the report is a comparative regulatory analysis of three critical regions: Sub-Saharan Africa, Emerging Asia, and Latin America. We detail the aggressive regulatory pivots seen in 2024 and 2025, from Kenya's transition to a "Non-Deposit Taking Credit Provider" regime and Nigeria's draconian enforcement against digital loan sharks, to India's sophisticated "Digital Lending Directions 2025" and Brazil's harmonization of Open Finance with AI regulation. The analysis suggests that the "Financial Inclusion Trilemma"-the struggle to balance access, fairness, and stability-is forcing a convergence toward a new global standard of "Algorithmic Accountability," where the license to operate is contingent not just on capital adequacy, but on the transparency and ethical configuration of the code itself.