femishajan / loancasestudy

LOAN CASE STUDY

General Information

This company is the largest online loan marketplace, facilitating personal loans, business loans, and financing of medical procedures. Borrowers can easily access lower interest rate loans through a fast online interface. Like most other lending companies, lending loans to ‘risky’ applicants is the largest source of financial loss (called credit loss). The credit loss is the amount of money lost by the lender when the borrower refuses to pay or runs away with the money owed. In other words, borrowers who default cause the largest amount of loss to the lenders. In this case, the customers labelled as 'charged-off' are the 'defaulters'. If one is able to identify these risky loan applicants, then such loans can be reduced thereby cutting down the amount of credit loss. Identification of such applicants using EDA is the aim of this case study.

Conclusions

• The higher loan amount has more number of defaulters.
• The loan grade is directly proportional to the number of defaulters.
• Business purpose loans need special attention before approval as the risk factor of loss is higher.
• People income matters the most when loan is given out because we should see if they can even pay it back. Therefore verification on annual income is needed.
• As we see here that numbers of defaults are higher in verified, we need to investigate the documents correctly before the loan is approved.

Technologies Used

• pandas
• python

Contact

Created by @femishajan