https://github.com/raksh710/loan_default_prediction

A major chunk of bank revenue is generated by credit cards. Customers who fail to pay their credit card dues on time could potentially cost banks a lot of revenue. Issuing credit cards to customers who have a higher likelihood of not paying their dues on time involves a higher risk for the bank. Issuing these customers' cards with a higher interest rate would work in favor of the bank. Inorder to make a informed decision about which customer is high risk and which one is low risk, the firm would benefit from a predition model which would accurately predict if the customer would default or not. Prediction can be done based on factors like job, education, balance, loans, and house ownership. Finding out which are the most common factors that defaulters have will also help the bank to be cautious before issuing a credit card to customers who fall into one of those categories.
https://github.com/raksh710/loan_default_prediction

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A major chunk of bank revenue is generated by credit cards. Customers who fail to pay their credit card dues on time could potentially cost banks a lot of revenue. Issuing credit cards to customers who have a higher likelihood of not paying their dues on time involves a higher risk for the bank. Issuing these customers' cards with a higher interest rate would work in favor of the bank. Inorder to make a informed decision about which customer is high risk and which one is low risk, the firm would benefit from a predition model which would accurately predict if the customer would default or not. Prediction can be done based on factors like job, education, balance, loans, and house ownership. Finding out which are the most common factors that defaulters have will also help the bank to be cautious before issuing a credit card to customers who fall into one of those categories.

• Host: GitHub
• URL: https://github.com/raksh710/loan_default_prediction
• Owner: Raksh710
• Created: 2021-12-11T18:13:41.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2021-12-11T18:19:38.000Z (about 3 years ago)
• Last Synced: 2024-11-10T11:42:15.198Z (about 2 months ago)
• Language: HTML
• Size: 638 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Loan_Default_Prdiction

A major chunk of bank revenue is generated by credit cards. Customers who fail to pay their credit card dues on time could potentially cost banks a lot of revenue.   Issuing credit cards to customers who have a higher likelihood of not paying their dues on time involves a higher risk for the bank. Issuing these customers' cards with a higher interest rate would work in favor of the bank. Inorder to make a informed decision about which customer is high risk and which one is low risk, the firm would benefit from a predition model which would accurately predict if the customer would default or not. Prediction can be done based on factors like job, education, balance, loans, and house ownership.  Finding out which are the most common factors that defaulters have will also help the bank to be cautious before issuing a credit card to customers who fall into one of those categories.