The bank's credit department needs to determine which customer characteristics and in what way affect the timely repayment of loans. The input data consists of statistics on the creditworthiness of bank clients. The research results will be taken into account when building a credit scoring model.
Based on statistics on the creditworthiness of clients, I examined the impact of factors such as marital status, income level, loan purpose, and the number of children on the timely repayment of loans. I identified and processed missing data, adjusted data types to match the stored information, removed duplicates, and categorized the data. One dataframe was decomposed into three.
I determined the profile of the most reliable and the least reliable borrowers.
Toolkit: Pandas, Python, Data Preprocessing