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English(EN) TMR-GGNN: Credit Card Fraud Detection based on Time-Aware Multi-Relational Guided Graph Neural Network

新型图神经网络助力信用卡欺诈检测

作者 PulseAugur 编辑部 · [2 个来源] ·

一篇新研究论文介绍了一种用于信用卡欺诈检测的新型框架 TMR-GGNN，该框架利用时间感知、多关系图神经网络。该方法模拟了客户、商户、设备和 IP 之间随时间变化的复杂交互，并结合了时间注意力机制来衡量交易的相关性。该框架还采用对比学习和复合损失函数来提高对罕见欺诈案例的泛化能力并减少假阴性，从而应对数据不平衡和不断变化的欺诈模式等挑战。 AI

影响 这项研究通过改进对不平衡数据和不断变化的欺诈模式的处理，可能带来更有效的信用卡欺诈检测系统。

排序理由 该集群包含一篇详细介绍信用卡欺诈检测新方法的论文。

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新型图神经网络助力信用卡欺诈检测

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该集群包含一篇详细介绍信用卡欺诈检测新方法的论文。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Rohit Tewari, Shubhankar Shilpi, Navin Chhibber, Devendra Singh Parmar, Sunil Khemka, Piyush Ranjan ·

    TMR-GGNN：基于时序感知多关系引导图神经网络的信用卡欺诈检测

    arXiv:2606.18444v1 Announce Type: cross Abstract: In recent years, credit card fraud detection has faced significant challenges due to highly imbalanced data, evolving fraud patterns, and complex relational structures among transaction entities. To address these issues, this rese…

  2. Databricks Blog TIER_1 English(EN) ·

    支付欺诈检测：银行和企业如何阻止欺诈交易

    Payment fraud detection has become one of the most data-intensive challenges in financial services...

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