Skip to content

This project builds a model to predict if Lending Club loans will be fully paid or charged off. Using completed loan data, it includes credit history and loan grades but excludes FICO scores and rejected loans due to limited data. Methodologies and results are documented for accuracy and fairness.

Notifications You must be signed in to change notification settings

cheshtadhingra/LendingClub

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

71 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

LendingClub

Background Information

The Lending Club is a peer-to-peer lending network offering loans.It provides extensive loan data online, enabling investors to make informed investment decisions. This data, includes borrower demographics, credit history, loan specifics (e.g., purpose, requested amount, funded amount, interest rate, and loan grade).

Project Aim

The primary goal of this project is to develop a model that predicts whether a Lending Club-approved loan will be fully paid or charged off. Such predictions are invaluable to investors for making informed investment choices. The model should be:

  1. Accurate: Effectively predicting loan outcomes.
  2. Non-discriminatory: Ensuring fairness concerning demographic features like race and home address.

Only completed loans are included in the model to ensure outcome certainty, excluding those still in progress or in default.

Data

The data used for this project is sourced from the Lending Club's website (https://www.lendingclub.com/). Due to limited information on rejected loans (e.g., risk score, debt-to-income ratio, zip code, and employment length), they were excluded from the model.

Borrower FICO scores were not incorporated as access is restricted to approved investors. Nonetheless, the dataset includes various credit risk-related features, such as the number of delinquencies in the past two years, average current balance, and total credit revolving balance. Additionally, the Lending Club's loan grades, which factor in the FICO score and other variables, are included.

Methodology and Results

Detailed methodologies for data exploration, cleaning, processing, modeling, and fairness adjustments are documented on the relevant dataset pages. A summary of results and future considerations can be found on the Discussions page.

About

This project builds a model to predict if Lending Club loans will be fully paid or charged off. Using completed loan data, it includes credit history and loan grades but excludes FICO scores and rejected loans due to limited data. Methodologies and results are documented for accuracy and fairness.

Topics

Resources

Stars

Watchers

Forks

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •