This dataset 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 dataset only represents loans actually made, i.e. do not mistake this data for loan applications!
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.
- homeownership
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
individualorjoint.- 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 … 3 NJ MORTGAGE 90000 Verified
#> 2 "warehouse offi… 10 HI RENT 40000 Not Verified
#> 3 "assembly" 3 WI RENT 40000 Source Verified
#> 4 "customer servi… 1 PA RENT 30000 Not Verified
#> 5 "security super… 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
#> # ℹ 9,990 more rows
#> # ℹ 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>, …