Research on credit card fraud detection system based on federated learning
Authors: 
WenGuang Ma, Zelong Yin, Jinyan Zhou, ChongChong Jia, HaiPing Yang, JinLong Wang, Bin LiAuthors Info & Claims
WenGuang Ma, Zelong Yin, Jinyan Zhou, ChongChong Jia, HaiPing Yang, JinLong Wang, Bin LiAuthors Info & ClaimsPages 242 - 245
Abstract
Since the reform and opening up, my country's economic growth has been strong, and it has achieved brilliant achievements in the past few decades. With the digital transformation of the economy, credit card fraud has become a more prominent problem. Due to the confidentiality of personal transaction data and the small amount of data from a single bank, it is difficult for financial institutions to jointly build fraud detection models, which greatly increases the economic risks of financial institutions. Therefore, this paper builds a credit card fraud detection system based on federated learning. Under the premise of protecting data privacy, it realizes multi-institutional collaboration through distributed machine learning technology and improves the risk management capabilities of financial institutions.
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Published In
April 2024
379 pages
ISBN:9798400709777
DOI:10.1145/3653644
Copyright © 2024 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 20 September 2024
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FAIML 2024
FAIML 2024: 2024 3rd International Conference on Frontiers of Artificial Intelligence and Machine Learning
April 26 - 28, 2024
Yichang, China
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