The loan applications which come in to bank branches are processed manually. The decision whether to grant a loan or not is subjective and due to a lot of applications coming in, it is getting harder for them to decide the loan grant status.
They want to build an automated machine learning solution which will look at different factors and decide whether to grant loan or not to the respective individual.
We will build a classification model to predict if an applicant should get a loan or not. We will look at various factors of the applicant like credit score, past history and from those we will try to predict the loan granting status. We will also cleanse the data and fill in the missing values so that our ML model performs as expected. Thus we will be giving out a probability score along with Loan Granted or Loan Refused output from the model.
Language: Python
Libraries: Pandas, numpy, Smote, sklearn, H2o