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William Asiedu

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Open access Jul 2026

Optimizing Credit Risk Assessment in Ghanaian Micro-Lending Institutions: A Comparative Analysis of Random Forest, Extra Tree Classifier, and Ensemble Machine Learning Models

It is concluded that integrating ML models can substantially improve the accuracy, consistency, and reliability of credit risk evaluations, thereby reducing default rates and supporting financial inclusion in Ghana's microfinance sector.

P. Addo, Samuel Kofi Akpatsa, Emmanuel Mensah et al. · 0 citations

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