Download the dataset below to solve this Data Science case study on Credit Score Classification. Dataset Source: Kaggle)
Credit Score Classification: Case Study
The credit score of a person determines the creditworthiness of the person. It helps financial companies determine if you can repay the loan or credit you are applying for.
Here is a dataset based on the credit score classification submitted by Rohan Paris on Kaggle. Below are all the features in the dataset:
- ID: Unique ID of the record
- Customer_ID: Unique ID of the customer
- Month: Month of the year
- Name: The name of the person
- Age: The age of the person
- SSN: Social Security Number of the person
- Occupation: The occupation of the person
- Annual_Income: The Annual Income of the person
- Monthly_Inhand_Salary: Monthly in-hand salary of the person
- Num_Bank_Accounts: The number of bank accounts of the person
- Num_Credit_Card: Number of credit cards the person is having
- Interest_Rate: The interest rate on the credit card of the person
- Num_of_Loan: The number of loans taken by the person from the bank
- Type_of_Loan: The types of loans taken by the person from the bank
- Delay_from_due_date: The average number of days delayed by the person from the date of payment
- Num_of_Delayed_Payment: Number of payments delayed by the person
- Changed_Credit_Card: The percentage change in the credit card limit of the person
- Num_Credit_Inquiries: The number of credit card inquiries by the person
- Credit_Mix: Classification of Credit Mix of the customer
- Outstanding_Debt: The outstanding balance of the person
- Credit_Utilization_Ratio: The credit utilization ratio of the credit card of the customer
- Credit_History_Age: The age of the credit history of the person
- Payment_of_Min_Amount: Yes if the person paid the minimum amount to be paid only, otherwise no.
- Total_EMI_per_month: The total EMI per month of the person
- Amount_invested_monthly: The monthly amount invested by the person
- Payment_Behaviour: The payment behaviour of the person
- Monthly_Balance: The monthly balance left in the account of the person
- Credit_Score: The credit score of the person
The Credit_Score column is the target variable in this problem. You are required to find relationships based on how banks classify credit scores and train a model to classify the credit score of a person.
