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Loan Repayment Default Prediction Using Supervised Machine Learning Techniques on Financial Data

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The model achieves high accuracy rates of 97.47% in predicting loan repayments using KNN with cross-validation.
KNN is tested on two datasets, achieving 88.21% accuracy on the second dataset with different nearest neighbor configurations.
Logistic regression provides competitive results, identifying correct classifications of up to 96.93% using a 70% training set.
Various training percentages (40%, 50%, 60%, 70%) and cross-validation values enhance the robustness of the predictions.

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Supervised machine learning methods predict loan repayment outcomes using financial data, suggesting effective risk assessment.

Raad et al. (2025) studied this question.

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