Introduction:

Lending Club enables borrowers to create unsecured personal loans. The standard loan period is three years. Investors can search and browse the loan listings on Lending Club website and select loans that they want to invest in based on the information supplied about the borrower, amount of loan, loan grade, and loan purpose. Investors make money from interest. Lending Club makes money by charging borrowers an origination fee and investors a service fee.

In this project one has to put themself in the shoes of a loan issuer and manage credit risk by using the past data and deciding whom to give the loan to in the future. The text files contain complete loan data for all loans issued by XYZ Corp. through 2007-2015. The data contains the indicator of default, payment information, credit history, etc.

Loan Default Prediction

Project by Pushkar Raj

Loading the text data

# Setting the path to my local directory where my dataset is placed

import os
os.chdir('E:\\Finale Project\\Python Project')
print (os.getcwd())

E:\Finale Project\Python Project

# Importing necessary libraries
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns
from sklearn import preprocessing,metrics 
%matplotlib inline
from IPython.display import Image
from matplotlib import rcParams
rcParams['figure.figsize'] = 11,6