FRM Part I · FRM Exam Part I · Machine Learning and Prediction
A lender lowers the probability threshold used to classify a borrower as a predicted defaulter, from 0.50 to 0.30, using the same fitted model. Which outcome is the most likely effect?
Recall rises and the false positive rate rises. Lowering the threshold labels more borrowers as defaulters, so more true defaulters are captured but more good borrowers are wrongly flagged. Both move together along the ROC curve.
- ARecall rises and the false positive rate risesCorrect
- BRecall falls and the false positive rate falls
- CRecall rises and the false positive rate falls
- DPrecision necessarily rises and recall is unchanged
Explanation
A lower threshold labels more borrowers as defaulters. This catches more actual defaulters (recall up) but also wrongly flags more good borrowers (false positive rate up). Both cannot move in opposite directions along the same ROC curve when the threshold shifts one way.
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