Used tensorflow's neural network model to predict whether or not a person pays back a loan on the basis of his historical data and personal details of around 4 lakh people, like employment details, address, loan amount, etc.

LENDING CLUB is a US peer-to-peer lending company, headquartered in San Francisco, California. It was the first peer-to-peer lender to register its offerings as securities with the Securities and Exchange Commission (SEC), and to offer loan trading on a secondary market. LendingClub is the world's largest peer-to-peer lending platform.

Our Goal: Given historical data on loans given out with information on whether or not the borrower defaulted (charge-off), I built a model that can predict wether or nor a borrower will pay back their loan. This way in the future when we get a new potential customer we can assess whether or not they are likely to pay back the loan.

Done a lot of exploratory data analysis, feature engineering, data cleaning and created a dense neural network using dropout layers, and plotted out the loss on training data and testing data to prevent overfitting of data and finding optimal solution.