To minimize loss from the bank’s perspective, the bank needs a decision rule regarding whom to approve the loan and whom not to. An applicant’s demographic and socio-economic profiles are considered by loan managers before a decision is taken regarding his/her loan application. In this dataset, each entry represents a person who takes credit from a bank. Each person is classified as a good or bad credit risk according to the set of attributes.
This project aims to build a predictive model on this data to help the bank decide on whether to approve a loan to a prospective applicant.