TVS_Loan_Default

Personal Loan product is an unsecured loan therefore it is vital to assess the risk of the customers by checking their credit worthiness. This must be done to prevent loan defaults. The objective is to build a Risk model using the dataset which will assess the risk of a customer defaulting after cross-selling the Personal Loan. Column Descriptions: V1: Customer ID V2: If a customer has bounced in first EMI (1 : Bounced, 0 : Not bounced) V3: Number of times bounced in recent 12 months V4: Maximum MOB (Month of business with TVS Credit) V5: Number of times bounced while repaying the loan V6: EMI V7: Loan Amount V8: Tenure V9: Dealer codes from where customer has purchased the Two wheeler V10: Product code of Two wheeler (MC : Motorcycle , MO : Moped, SC : Scooter) V11: No of advance EMI paid V12: Rate of interest V13: Gender (Male/Female) V14: Employment type (HOUSEWIFE : housewife, SELF : Self-employed, SAL : Salaried, PENS : Pensioner, STUDENT : Student) V15: Resident type of customer V16: Date of birth V17: Age at which customer has taken the loan V18: Number of loans V19: Number of secured loans V20: Number of unsecured loans V21: Maximum amount sanctioned in the Live loans V22: Number of new loans in last 3 months V23: Total sanctioned amount in the secured Loans which are Live V24: Total sanctioned amount in the unsecured Loans which are Live V25: Maximum amount sanctioned for any Two wheeler loan V26: Time since last Personal loan taken (in months) V27: Time since first consumer durables loan taken (in months) V28: Number of times 30 days past due in last 6 months V29: Number of times 60 days past due in last 6 months V30: Number of times 90 days past due in last 3 months V31: Tier ; (Customers geographical location) V32: Target variable ( 1: Defaulters / 0: Non-Defaulters)