The inherent high default risk in Peer-to-Peer(P2P)lending necessitates robust credit risk assessment for sustainable online financial operations.This study addresses this need by developing a default prediction model...The inherent high default risk in Peer-to-Peer(P2P)lending necessitates robust credit risk assessment for sustainable online financial operations.This study addresses this need by developing a default prediction model for P2P borrowers using public data from the Renrendai platform in China.With approximately one million loan records,we built up a back-propagation neural network model and achieved over 85%prediction accuracy.The model was refined through two steps:generating Receiver Operating Characteristic and introducing a novel indicator,SPACE,to identify the optimal threshold interval for the final model.This research presents an enhanced credit evaluation model,offering practical implications for P2P lending risk management.展开更多
文摘The inherent high default risk in Peer-to-Peer(P2P)lending necessitates robust credit risk assessment for sustainable online financial operations.This study addresses this need by developing a default prediction model for P2P borrowers using public data from the Renrendai platform in China.With approximately one million loan records,we built up a back-propagation neural network model and achieved over 85%prediction accuracy.The model was refined through two steps:generating Receiver Operating Characteristic and introducing a novel indicator,SPACE,to identify the optimal threshold interval for the final model.This research presents an enhanced credit evaluation model,offering practical implications for P2P lending risk management.
