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A financial institution wants to accurately predict the probability of loanee/borrower defaulting on a vehicle loan in the first EMI on the due date.

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auc-roc-curve confusion-matrix datacleaning datapreprocessing decision-tree-classifier eda feature-engineering feature-selection featureextraction gradient-boosting logistic-regression ols-regression random-forest-classifier selectkbest sgdclassifier smote-sampling xgboost-algorithm

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Vehicle_loan_defaulter

  • 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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