Customer loan approval prediction using logistic regression

Abstract

Banking Sector contains loan where it is a process of lending or borrowing a sum of money by one or more individuals, organizations, etc. from Banks. The Person who lends that money from respective financier incurs a debt, and he is responsible to pay back the money with the Interest decided by Bank within a certain period. Generally what Bank's look into before applying for a loan is Credit History, Credit loss and Income of Applicant. So basically,loans play a major role regarding Income for Bank. Due to rapid urban development people who are applying for loans got increased rapidly. Therefore, finding the applicant to whom loan can be approved become a complexed process. In this paper, we want to predict the loan eligibility based on details of the customer. Fields that required are Matrimonial Status, Income, Education, Loan Amount, Credit History and other income sources of Applicant dependants. To predict the status, we will use Logistic Regression to spot the eligible applicants so bank will engage with them for granting loans to those people who can payback in a given time.