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CDGAT: A graph attention network method for credit card defaulters prediction
Wu, Jun; Zhao, XiongFei; Yuan, Hang; Si, Yain-Whar
2022-07
Source PublicationApplied Intelligence
Abstract

Recognizing potential defaulters is a crucial problem for fi nancial
institutions. Therefore, many credit scoring methods have been proposed in
the past to address this issue. However, these methods rarely consider the interaction among customers such as bank transfer and remittance. With rapid
growth in the number of customers adopting online banking services, such interaction information plays a signi cant role in assessing their credit score. In
this paper, we propose a novel scalable credit scoring approach called CDGAT
(Graph attention network for credit card defaulters) for predicting potential
credit card defaulters. In CDGAT, a customer's credit score is calculated based
on transaction embedding and neighborhood embedding. To obtain the neighborhood embedding, CDGAT rst utilizes the Amount-bias Sampling (AbS)
strategy to extract a subgraph for each customer. Next, CDGAT directly aggregates neighbors' features according to their in uence weights. The experimental results on the dataset from Industrial and Commercial Bank of China (Macau) Limited (ICBC (Macau)) show that CDGAT signi cantly outperforms the baseline methods. Furthermore, experimental results reveal that the proposed method is also superior to several state-of-the-art Graph Convolutional Neural Network models in terms of scalability and performance.

KeywordCredit Scoring Defaulters Prediction Graph Convolutional Neural Network Node Classi cation Neighbors Sampling
Indexed BySCIE
Language英語English
Fulltext Access
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorWu, Jun; Si, Yain-Whar
Affiliation1.University of Macau
2.Industrial and Commercial Bank of China (Macau) Limited
3.Industrial and Commercial Bank of China (Macau) Limited
4.University of Macau
Recommended Citation
GB/T 7714
Wu, Jun,Zhao, XiongFei,Yuan, Hang,et al. CDGAT: A graph attention network method for credit card defaulters prediction[J]. Applied Intelligence,2022.
APA Wu, Jun,Zhao, XiongFei,Yuan, Hang,&Si, Yain-Whar.(2022).CDGAT: A graph attention network method for credit card defaulters prediction.Applied Intelligence.
MLA Wu, Jun,et al."CDGAT: A graph attention network method for credit card defaulters prediction".Applied Intelligence (2022).
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