This data set represents thousands of loans made through the Lending Club platform, which is a platform that allows individuals to lend to other individuals. Of course, not all loans are created equal. Someone who is a essentially a sure bet to pay back a loan will have an easier time getting a loan with a low interest rate than someone who appears to be riskier. And for people who are very risky? They may not even get a loan offer, or they may not have accepted the loan offer due to a high interest rate. It is important to keep that last part in mind, since this data set only represents loans actually made, i.e. do not mistake this data for loan applications!

loans_full_schema

Format

A data frame with 10,000 observations on the following 55 variables.

emp_title

Job title.

emp_length

Number of years in the job, rounded down. If longer than 10 years, then this is represented by the value 10.

state

Two-letter state code.

home_ownership

The ownership status of the applicant's residence.

annual_income

Annual income.

verified_income

Type of verification of the applicant's income.

debt_to_income

Debt-to-income ratio.

annual_income_joint

If this is a joint application, then the annual income of the two parties applying.

verification_income_joint

Type of verification of the joint income.

debt_to_income_joint

Debt-to-income ratio for the two parties.

delinq_2y

Delinquencies on lines of credit in the last 2 years.

months_since_last_delinq

Months since the last delinquency.

earliest_credit_line

Year of the applicant's earliest line of credit

inquiries_last_12m

Inquiries into the applicant's credit during the last 12 months.

total_credit_lines

Total number of credit lines in this applicant's credit history.

open_credit_lines

Number of currently open lines of credit.

total_credit_limit

Total available credit, e.g. if only credit cards, then the total of all the credit limits. This excludes a mortgage.

total_credit_utilized

Total credit balance, excluding a mortgage.

num_collections_last_12m

Number of collections in the last 12 months. This excludes medical collections.

num_historical_failed_to_pay

The number of derogatory public records, which roughly means the number of times the applicant failed to pay.

months_since_90d_late

Months since the last time the applicant was 90 days late on a payment.

current_accounts_delinq

Number of accounts where the applicant is currently delinquent.

total_collection_amount_ever

The total amount that the applicant has had against them in collections.

current_installment_accounts

Number of installment accounts, which are (roughly) accounts with a fixed payment amount and period. A typical example might be a 36-month car loan.

accounts_opened_24m

Number of new lines of credit opened in the last 24 months.

months_since_last_credit_inquiry

Number of months since the last credit inquiry on this applicant.

num_satisfactory_accounts

Number of satisfactory accounts.

num_accounts_120d_past_due

Number of current accounts that are 120 days past due.

num_accounts_30d_past_due

Number of current accounts that are 30 days past due.

num_active_debit_accounts

Number of currently active bank cards.

total_debit_limit

Total of all bank card limits.

num_total_cc_accounts

Total number of credit card accounts in the applicant's history.

num_open_cc_accounts

Total number of currently open credit card accounts.

num_cc_carrying_balance

Number of credit cards that are carrying a balance.

num_mort_accounts

Number of mortgage accounts.

account_never_delinq_percent

Percent of all lines of credit where the applicant was never delinquent.

tax_liens

a numeric vector

public_record_bankrupt

Number of bankruptcies listed in the public record for this applicant.

loan_purpose

The category for the purpose of the loan.

application_type

The type of application: either individual or joint.

loan_amount

The amount of the loan the applicant received.

term

The number of months of the loan the applicant received.

interest_rate

Interest rate of the loan the applicant received.

installment

Monthly payment for the loan the applicant received.

grade

Grade associated with the loan.

sub_grade

Detailed grade associated with the loan.

issue_month

Month the loan was issued.

loan_status

Status of the loan.

initial_listing_status

Initial listing status of the loan. (I think this has to do with whether the lender provided the entire loan or if the loan is across multiple lenders.)

disbursement_method

Dispersement method of the loan.

balance

Current balance on the loan.

paid_total

Total that has been paid on the loan by the applicant.

paid_principal

The difference between the original loan amount and the current balance on the loan.

paid_interest

The amount of interest paid so far by the applicant.

paid_late_fees

Late fees paid by the applicant.

Source

This data comes from Lending Club (https://www.lendingclub.com/info/statistics.action), which provides a very large, open set of data on the people who received loans through their platform.

Examples


loans_full_schema
#> # A tibble: 10,000 × 55
#>    emp_title                 emp_length state homeownership annual_income verified_income
#>    <chr>                          <dbl> <fct> <fct>                 <dbl> <fct>          
#>  1 "global config engineer "          3 NJ    MORTGAGE              90000 Verified       
#>  2 "warehouse office clerk"          10 HI    RENT                  40000 Not Verified   
#>  3 "assembly"                         3 WI    RENT                  40000 Source Verified
#>  4 "customer service"                 1 PA    RENT                  30000 Not Verified   
#>  5 "security supervisor "            10 CA    RENT                  35000 Verified       
#>  6 ""                                NA KY    OWN                   34000 Not Verified   
#>  7 "hr "                             10 MI    MORTGAGE              35000 Source Verified
#>  8 "police"                          10 AZ    MORTGAGE             110000 Source Verified
#>  9 "parts"                           10 NV    MORTGAGE              65000 Source Verified
#> 10 "4th person"                       3 IL    RENT                  30000 Not Verified   
#> # … with 9,990 more rows, and 49 more variables: debt_to_income <dbl>,
#> #   annual_income_joint <dbl>, verification_income_joint <fct>,
#> #   debt_to_income_joint <dbl>, delinq_2y <int>,
#> #   months_since_last_delinq <int>, earliest_credit_line <dbl>,
#> #   inquiries_last_12m <int>, total_credit_lines <int>,
#> #   open_credit_lines <int>, total_credit_limit <int>,
#> #   total_credit_utilized <int>, num_collections_last_12m <int>, …