Loan-Default-Prediction L&T Financial Services & Analytics Vidhya presents ‘DataScience FinHack’. where I have predicted whether the customer will be defaulter in the first EMI payment using different algorithms from machine learning Problem Statement Vehicle Loan Default Prediction Financial institutions incur significant losses due to the default of vehicle loans. This has led to the tightening up of vehicle loan underwriting and increased vehicle loan rejection rates. The need for a better credit risk scoring model is also raised by these institutions. This warrants a study to estimate the determinants of vehicle loan default. A financial institution has hired you to accurately predict the probability of loanee/borrower defaulting on a vehicle loan in the first EMI (Equated Monthly Instalments) on the due date. Following Information regarding the loan and loanee are provided in the datasets: Loanee Information (Demographic data like age, income, Identity proof etc.) Loan Information (Disbursal details, amount, EMI, loan to value ratio etc.) Bureau data & history (Bureau score, number of active accounts, the status of other loans, credit history etc.) Doing so will ensure that clients capable of repayment are not rejected and important determinants can be identified which can be further used for minimising the default rates. Data Description contains train.csv and train.csv contains the training data with details on loan as described in the data_dictionary contains a brief description on each variable provided in the training and test.csv contains details of all customers and loans for which the participants are to submit probability of default. submission.csv contains the submission format for the predictions against the test set. A single csv needs to be submitted as a solution Evaluation Metric Submissions are evaluated on area under the ROC curve between the predicted probability and the observed target. DATA DICTIONARY: Variable Name Description UniqueID Identifier for customers loan_default Payment default in the first EMI on due date disbursed_amount Amount of Loan disbursed asset_cost Cost of the Asset ltv Loan to Value of the asset branch_id Branch where the loan was disbursed supplier_id Vehicle Dealer where the loan was disbursed manufacturer_id Vehicle manufacturer(Hero, Honda, TVS etc.) Current_pincode Current pincode of the customer Date.of.Birth Date of birth of the customer Employment.Type Employment Type of the customer (Salaried/Self Employed) DisbursalDate Date of disbursement State_ID State of disbursement Employee_code_ID Employee of the organization who logged the disbursement MobileNo_Avl_Flag if Mobile no. was shared by the customer then flagged as 1 Aadhar_flag if aadhar was shared by the customer then flagged as 1 PAN_flag if pan was shared by the customer then flagged as 1 VoterID_flag if voter was shared by the customer then flagged as 1 Driving_flag if DL was shared by the customer then flagged as 1 Passport_flag if passport was shared by the customer then flagged as 1 PERFORM_CNS.SCORE Bureau Score PERFORM_CNS.SCORE.DESCRIPTION Bureau score description PRI.NO.OF.ACCTS count of total loans taken by the customer at the time of disbursement Primary accounts are those which the customer has taken for his personal use PRI.ACTIVE.ACCTS count of active loans taken by the customer at the time of disbursement PRI.OVERDUE.ACCTS count of default accounts at the time of disbursement PRI.CURRENT.BALANCE total Principal outstanding amount of the active loans at the time of disbursement PRI.SANCTIONED.AMOUNT total amount that was sanctioned for all the loans at the time of disbursement PRI.DISBURSED.AMOUNT total amount that was disbursed for all the loans at the time of disbursement SEC.NO.OF.ACCTS count of total loans taken by the customer at the time of disbursement Secondary accounts are those which the customer act as a co-applicant or gaurantor SEC.ACTIVE.ACCTS count of active loans taken by the customer at the time of disbursement SEC.OVERDUE.ACCTS count of default accounts at the time of disbursement SEC.CURRENT.BALANCE total Principal outstanding amount of the active loans at the time of disbursement SEC.SANCTIONED.AMOUNT total amount that was sanctioned for all the loans at the time of disbursement SEC.DISBURSED.AMOUNT total amount that was disbursed for all the loans at the time of disbursement PRIMARY.INSTAL.AMT EMI Amount of the primary loan SEC.INSTAL.AMT EMI Amount of the secondary loan NEW.ACCTS.IN.LAST.SIX.MONTHS New loans taken by the customer in last 6 months before the disbursment DELINQUENT.ACCTS.IN.LAST.SIX.MONTHS Loans defaulted in the last 6 months AVERAGE.ACCT.AGE Average loan tenure CREDIT.HISTORY.LENGTH Time since first loan NO.OF_INQUIRIES Enquries done by the customer for loans