An exploration of credit risk assessment on loan approval process using machine learning techniques.
- Author
- Doka, Juliet R.
- Title
- An exploration of credit risk assessment on loan approval process using machine learning techniques.
- Abstract
- A loan is a sum of money that can be obtained from financial institutions with the understanding that the borrower will repay the loan within a predetermined time frame and with interest. After accruing debt, the borrower is required to pay it back in full, typically with interest. The model will be trained to predict whether the applicant will be able to pay back the loan. There are certain features that have to be taken into consideration before approving the loan. Automating the procedure is the primary goal in order to process loan applications more quickly. Train and test data sets were used as the input. To determine the accuracy of the model, the training data was used, and to output the predictions, test data was used. To reach the scope of our goal, the researcher has used machine learning tools and algorithms as well as Python, Jupyter notebook and Django to develop the system.
- Date
- June 2025
- Publisher
- BUSE
- Keywords
- Credit Risk Assessment
- Loan Approval
- Supervisor
- Mr. H. Chikwiriro
- Item sets
- Department of Computer Science
- Media
-
Doka, Juliet R..pdf
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