A group project for the Hamoye Datascience Internship 2021. In this project, credit card approval data was analysed and a machine learning model was developed to predict the approval of credit card request.
The dataset for this project was gotten from UCI Machine Learning Repository
Credit score cards are a common risk control method in the financial industry. It uses personal information, and data submitted by credit card applicants to predict the probability of future defaults and credit card borrowings. The bank or lending company is able to decide whether to issue a credit card to the applicant or not. Credit scores can objectively quantify the magnitude of risk. The project focuses on predicting whether an applicant is qualified to receive a loan or not.
The prediction application can be found here.