- A financial institution wants to accurately predict the probability of loanee/borrower defaulting on a vehicle loan in the first EMI (Equated Monthly Instalments) on the due date. Following Information regarding the loan and loanee are provided in the datasets:
- Loanee Information (Demographic data like age, Identity proof etc.)
- Loan Information (Disbursal details, loan to value ratio etc.)
- Bureau data & history (Bureau score, number of active accounts, the status of other loans, credit history etc.)
- Doing so will ensure that clients capable of repayment are not rejected and important determinants can be identified which can be further used for minimizing the default rates.
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View Code? Open in Web Editor NEWA financial institution wants to accurately predict the probability of loanee/borrower defaulting on a vehicle loan in the first EMI on the due date.