Nowadays, there are numerous risks related to bank loans both for the banks and the borrowers, who get the loans. The risk analysis about bank loans needs understanding about the risk and the risk level. Banks need to analyze their customers for loan eligibility so that they can specifically target those customers.
Banks wanted to automate the loan eligibility process (real time) based on customer details such as Gender, Marital Status, Age, Occupation, Income, debts and others, provided in their online application form. As the number of transactions in banking sector is rapidly growing and huge data volumes are available, the customers’ behavior can be easily analyzed and the risks around loan can be reduced. So, it is very important to predict the loan type and loan amount based on the banks’ data.
Data Description Customer loan dataset has samples of about 100+ unique customer details, where each customer is represented in a unique row.
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