The best algorithm for predicting loan defaults was determined to be a Gradient Boosting Classifier.

The hyperparameters were fine-tuned using grid search and cross-validation to further improve accuracy.

The final model achieved an AUC-ROC of 0.85, precision of 0.77, and recall of 0.69.

These metrics indicate that the model has strong predictive power and can accurately identify customers who are likely to default on a loan.
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