LoanDefaultPrediction

The research aims to compute the probability of a loan being defaulted based on the applicants’ current information and prior credit history; hence ensuring that banks don’t approve loans that are unlikely to be paid back in entirety. The main objective of the research is to build a robust binary classification model which can accurately predict loan default. Consequently, the research tries to identify the most significant contributors to a loan’s status, the variables that impact a customer’s probability of defaulting on a loan payment by any number of days on at least one of the installments of a loan, the features that customers who default on a loan payment have in common, and the effect a customer’s previous credit history of loan default on a loan approval decision