Business Understanding : This is consumer finance company which specialises in lending various types of loans to urban customers. When the company receives a loan application, the company has to make a decision for loan approval based on the applicant’s profile
The data given contains the information about past loan applicants and whether they ‘defaulted’ or not.
The aim is to identify patterns which indicate if a person is likely to default, which may be used for taking actions such as denying the loan,
reducing the amount of loan, lending (to risky applicants) at a higher interest rate, etc.
This project use EDA methodology for getting insights to data to find the relationships between various variables to derive conclusions and provide recommendation
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This project use EDA methodology for getting insights to data to find the relationships between various variables to derive conclusions and provide recommendation. With this project I am trying to develop a basic understanding of risk analytics in Lending Club service and understand how data is used to minimise the risk of losing money while lending to customers.
The dataset used is from lending club existing customers from year 2007 to 2011.
- Seaborn
- Pandas
- Matplotlib
- Plotly
Created by @Abhi-Awasthi