Yalong Xie1, Aiping Li1,*, Biyin Hu2, Liqun Gao1, Hongkui Tu1
CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2707-2726, 2023, DOI:10.32604/cmc.2023.037039
- 08 October 2023
Abstract Credit Card Fraud Detection (CCFD) is an essential technology for banking institutions to control fraud risks and
safeguard their reputation. Class imbalance and insufficient representation of feature data relating to credit card
transactions are two prevalent issues in the current study field of CCFD, which significantly impact classification
models’ performance. To address these issues, this research proposes a novel CCFD model based on Multifeature Fusion and Generative Adversarial Networks (MFGAN). The MFGAN model consists of two modules:
a multi-feature fusion module for integrating static and dynamic behavior data of cardholders into a unified highdimensional feature… More >
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