Credit Scoring and Financial Risk Modeling
Research on machine-learning approaches to credit scoring and financial risk, with a focus on relevance to African financial contexts.
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Overview
This research explores how data-driven models can support credit-risk assessment, examining model performance, fairness considerations, and explainability in credit decisions.
Our Approach
Apply supervised machine learning to credit risk data, comparing model architectures and evaluation methodologies while considering fairness and interpretability requirements.
Limitations & Considerations
Research project output. Exact publication details, dataset permissions, and model specifications must be confirmed before detailed public presentation. Not a deployed financial product.
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