Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning
By Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou
Rating
1660
Battle Count: 116
Relevance
7/10
Highly relevant for credit risk assessment in financial services, but not directly applicable to trading strategies
Implementation Complexity
8/10
Requires implementation of custom GNN architecture and motif-based graph construction
Reproducibility
4/5
Experiments conducted on public and industrial datasets with implementation details provided
About this paper
Methodology: MotifGNN. Problem types: Classification, Financial Default Prediction.
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