Lending Club
Lending Club is an online company that provides platform for peer-to-peer lending that matches
borrowers with investors. The company services people who need small personal loans
(approximately $1,000 - $4,000). Borrowers receive the full amount of the issued loan minus the
origination fee, which is paid to the company. Investors purchase notes backed by the personal
loans and pay Lending Club a service fee. The company shares data about all loans issued through
its platform during certain time periods.
Dataset
The dataset (LendingClub40k.csv) contains information of 40,000 loan records and 27
variables as shown in the table below:
id
loan amnt
funded amnt
term
Attribute
int rate
installment
grade
emp_length
emp title
home_ownership
annual inc
verification_stat
us
MIS 740
Spring 2024
issue d
Description
A unique Lending Club assigned ID for the loan listing.
The listed amount of the loan applied for by the borrower. If at some point in
time, the credit department reduces the loan amount, then it will be reflected
in this value.
The total amount committed to that loan at that point in time.
The number of payments on the loan. Values are in months and can be either
36 or 60.
Interest Rate on the loan
The monthly payment owed by the borrower if the loan originates.
Lending Club assigned loan grade
Employment length in years. Possible values are between 0 and 10 where 0
means less than one year and 10 means ten or more years.
The job title supplied by the Borrower when applying for the loan.
The home ownership status provided by the borrower during registration or
obtained from the credit report (RENT, OWN, MORTGAGE, OTHER).
The self-reported annual income provided by the borrower during registration.
Indicates if income was verified by Lending Club-not verified, or if the income
source was verified
The month which the loan was funded loan status
pymnt_plan
desc
purpose
zip_code
addrState
dti
delinq2Yrs
fico_range_high
fico_range_low
inq_last_6mths
pub_rec
revol bal
revol util
●
Current status of the loan
●
Indicates if a payment plan has been put in place for the loan
Loan description provided by the borrower
A category provided by the borrower for the loan request.
The first 3 numbers of the zip code provided by the borrower in the loan
application.
The state provided by the borrower in the loan application
A ratio calculated using the borrower's total monthly debt payments on the
total debt obligations, excluding mortgage and the requested Lending Club
loan, divided by the borrower's self-reported monthly income.
Part 1: Data preparation (Use R or RapidMiner)
Determine the role of each variable (dependent variable, independent variable, excluded
from analysis, etc.). You should keep as many variables in the dataset as possible.
Provide the descriptive statistics of the variables in the dataset.
The number of 30+ days past-due incidences of delinquency in the borrower's
credit file for the past 2 years
The upper boundary range the borrower's FICO at loan origination belongs to.
The lower boundary range the borrower's FICO at loan origination belongs to.
The number of inquiries in past 6 months (excluding auto and mortgage
inquiries)
Number of derogatory public records
Total credit revolving balance
Revolving line utilization rate, or the amount of credit the borrower is using
relative to all available revolving credit.
Report the detailed process of your data cleaning and preparation, e.g., how you deal with
the missing values, outliers, data anomalies, imputation, discretization, why you perform
certain data cleanings, and why you use certain parameters.
Perform statistical tests for outliers.
Based on the variables selected from the previous step, perform missing value imputation
on at least three variables.
Perform missing value imputation using machine learning algorithm.
Report the results and provide your interpretation/conclusion related to anomalies in the
dataset.
Provide screenshots of the R script and/or RapidMiner process.
