About Problem:
Credit scoring is a classification problem where the objective is to predict whether or not an individual will default on their credit.
Credit scoring is perhaps one of the most "classic" applications for predictive modeling, to predict whether or not credit extended to an applicant will likely result in profit or losses for the lending institution.
There are many variations and complexities regarding how exactly credit is extended to individuals, businesses, and other organizations for various purposes (purchasing equipment, real estate, consumer items, and so on), and using various methods of credit (credit card, loan, delayed payment plan). But in all cases, the lender provides money to an individual or institution and expects to be paid back in time with interest commensurate with the risk of default.
About Dataset:
age: Age of the Customers
ed: Education Level
employ: Work Experience
address: Address of the Customer
income: Yearly Income of the customer
debtinc: Debt to Income Ratio
creddebt: Credit to Debt ratio
othdebt: Other debts
default: Customer defaulted in the past (1= defaulted, 0= Never defaulted)
Dataset Kaggle Link: https://www.kaggle.com/datasets/atulmittal199174/credit-risk-analysis-for-extending-bank-loans
Bussiness Objectives:
Marketing Aspect Application Aspect Performance Aspect Bad Debt Management