A consumer finance company which carries out various types of lending activities in urban customers. There are various risks associated with lending activities, and in order to secure the company's business as well as to find prospectus customers a quite diligent analysis is to be undergone with the data's available from past loan approvals which may have been defaulted and non-defaulted. A data analysis on what a consumer finance company should look forward in the application of advances to reduce the chances of defaulters.
- The individuals having employment tenure greater than 10 years have high risk of defaulting
- It is observed that the customers who have been graded B,C,D are more of a defaulters when compared to other graded people.
- The individuals who rented or have a mortgage have higher probability of defaulting.
- The loans with purpose of debt consolidation has a highest risk of default.
- The loans with short tenures have higher risk of default.
- Not verified loans are more likely to be charged off.
- It is observed that for the charged off loan the rate of interest is more on comparison to the fully paid loan.
- pandas
- matplotlib
- seaborn
Created by Mohak Pingle and Pooja U