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September 10, 2025

Business Risk Prediction and Management Based on Artificial Intelligence by Applying Machine Learning Algorithms to Increase Business Flexibility and Social Stability: Banking Credit Risk Approach

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The Random Forest method achieved the highest prediction accuracy among the tested models.
Performance was evaluated using metrics like accuracy, precision, recall, and F1 score.
Five machine learning models were tested using a dataset of historical loans.
Improved predictive accuracy aids banks in more accurately assessing loan risk factors.

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This analysis demonstrates machine learning's impact on improving credit risk assessment, suggesting better accuracy and stability.

Manel Ben Salem (2025) studied this question.

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