Zi-Wei Feng

Random Forest vs. XGBoost for Peer-to-Peer Loan Default Prediction: Evidence from LendingClub

This study compares Random Forest (RF) and Extreme Gradient Boosting (XGBoost) for predicting loan defaults on 25,000 LendingClub loans from 2015–2016, using 14 financial features and 5-fold cross-validation. Both models perform similarly: RF reaches an AUC-ROC of 0.717, XGBoost reaches 0.715. RF does better on precisi...