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Interpretable Machine Learning Models for Credit Risk Assessment in Financial Institutions

Year: 2024

Type: article

Abstract: Interpretable Machine Learning Models for Credit Risk Assessment in Financial Institutions Ugochukwu Ukeje1* Abstract Credit risk assessment remains a cornerstone of decision making in the financial sector, directly influencing loan approvals, capital allocation, and systemic risk management. As machine learning models increasingly replace traditional techniques like logistic regression to enhance predictive accuracy, concerns over their […]

Source: International Journal of Science Architecture Technology and Environment

DOI: 10.63680/ijsate0324081.09

Author: Ugochukwu Ukeje

Institution: Kennesaw State University

Language: English

Topic: Explainable Artificial Intelligence (XAI)

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4412758129

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