Abstract: An important step in financial institutions is the loan approval process, which establishes a borrower's loan eligibility. Machine learning has advanced recently. In order to increase efficiency and accuracy, loan approval systems are increasingly using algorithms. This paper provides a high-level overview of a machine learning-based loan approval system, covering data preprocessing, feature selection, model selection, and evaluation. The suggested system seeks to decrease manual work and reduce default risk while improving the accuracy of loan approval decisions. The system's excellent accuracy and efficiency, as shown by the results, make it a promising method for loan approval in financial institutions.

Keywords: Loan, Machine Learning, Prediction, Training, Testing

Downloads: | DOI: 10.17148/IJIREEICE.2023.11610