Shrawan-Kumar / Lending-Club-Case-Study

Consumer Finance company which specializes in lending various types of loans to urban customers. When the company receives a loan application, the company has to make a decision for loan approval based on the applicant’s profile.

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Lending-Club-Case-Study:

A Data Analytics Project Identifies Loan Defaulter

Problem statement : To analyse risk in banking and financial services and understand how data is used to minimise the risk of losing money while lending to customers. Two types of risks are associated with the bank’s decision:

● If the applicant is likely to repay the loan, then not approving the loan results in a loss of business to the company.

● If the applicant is not likely to repay the loan, i.e. he/she is likely to default, then approving the loan may lead to a financial loss for the company.

Business Objective : To identify the risky loan applicants at the time of loan application so that 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.

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Consumer Finance company which specializes in lending various types of loans to urban customers. When the company receives a loan application, the company has to make a decision for loan approval based on the applicant’s profile.


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