ANALYTICS OF LENDING

Abstract: Data in our world is like a gold mine which has to be processed first to make something out of it; In our project data needs to be analysed so as produce good result. There are many companies where they pay their consumers for reviewing their product and these reviews plays a major role to analyse the factor which influences the review rating. Here, we have used EDA i.e., Exploratory Data Analysis where data interpretations can be done in row and column format. We have used python language for data analysis, it is object oriented, interpreted and interactive programming language and it is open source. Lending club receives a loan application, and it has to decide whether to approve the loan or reject it based on the application. Based on the decision there are two types of risks that can occur which will either result in loss of business or financial loss. Our research paper tried to find out the factors that can reduce the occurring of above factors. We have used EDA to understand how consumer attributes and loan attributes influence the tendency to default.

Keywords: Exploratory Data Analysis, Python, Jupyter, Numpy and Pandas