Row 5966

Row ID: 5966 | Dataset Entry | Axioma AXP Content Repository

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Looking for guidance on evaluating a currently in-use binary classification model for loan repayment.

I don't have the data the model is trained on, only the data for the instances where the loan was denied or the loan was originated and then whether the borrower defaulted or not.

How would I go about evaluating the performance of this model?

I’m thinking about using default rate and then adding to that the misclassified loan denials.

Would the only way to get the misclassified loan denials be to build a binary classification model, then validate it, after which to predict the repayment from all the denied instances that were never granted, and inference based on the created models performance how many of those are actually misclassified?

In addition, if you have any suggestions on books/articles on credit scoring models, please link them.

FieldValue
text Looking for guidance on evaluating a currently in-use binary classification model for loan repayment. I don't have the data the model is trained on, only the data for the instances where the loan was denied or the loan was originated and then whether the borrower defaulted or not. How would I go about evaluating the performance of this model? I’m thinking about using default rate and then adding to that the misclassified loan denials. Would the only way to get the misclassified loan denials …
label r/datascience
dataType post
communityName r/datascience
datetime 2024-05-06
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url_encoded Z0FBQUFBQm5Lak9HYmd3cjdGOXhiMEc3OVZ3akFUU0tOMW5zRUdmOXV2RTRnOWItTF9oWUZoeFA0UUpVZzNwQnlBeVU0MVY2bG1sZ0ZiYTNtWk5aaE1KTVRScFYyUUI3clBfT2dGMVJVeElJaGxhNHNaUm1qVE9aYmNtV1FsV3ZzcWFPbnNlWlFRRU12TU9nNUh5aDJzbW1sWTZabnRNRm9QV2t1TEI2R0tNTlFuNnJPYkdHOFdsdkpvaFZCcVdJMXpnSHJaN0RhaTBvc2E3Z0wxUGJIMGU0a3dwVFVVOWJqZz09

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{
  "text": "Looking for guidance on evaluating a currently in-use binary classification model for loan repayment.\n\nI don't have the data the model is trained on, only the data for the instances where the loan was denied or the loan was originated and then whether the borrower defaulted or not.\n\nHow would I go about evaluating the performance of this model?\n\nI’m thinking about using default rate and then adding to that the misclassified loan denials.\n\nWould the only way to get the misclassified loan denials be to build a binary classification model, then validate it, after which to predict the repayment from all the denied instances that were never granted, and inference based on the created models performance how many of those are actually misclassified?\n\nIn addition, if you have any suggestions on books/articles on credit scoring models, please link them.",
  "label": "r/datascience",
  "dataType": "post",
  "communityName": "r/datascience",
  "datetime": "2024-05-06",
  "username_encoded": "Z0FBQUFBQm5LakwyYUFVNEdEa1ZFMXBwXzFaR3VNb1YxWFo4c0dFMTZtaTh4Zl9OWEczem9hV1NJbkxaX1JuLTlPb2g1TkFhS042b3h1NW5MbGJjLVNxVHhXb0xMclFmRTdTTjA0VFhEaFBuelZQTkROeVh6NHc9",
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}
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