Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning

arXiv:2403.06482v1 Announce Type: cross
Abstract: User financial default prediction plays a critical role in credit risk forecasting and management. It aims at predicting the probability that the user will fail to make the repayments in the future. Previous methods mainly extract a set of user individual features regarding his own profiles and behaviors and build a binary-classification model to make default predictions. However, these methods cannot get satisfied results, especially for users with limited information. Although recent efforts suggest that …

abstract arxiv credit credit risk cs.lg curriculum curriculum learning extract features financial forecasting future graph graph neural network management motif network neural network prediction probability q-fin.rm risk role set type via will