设计semi-supervised GNN,利用有标签、无标签数据。(通过设计不同$Loss$实现) 使用Hieranchical Attention,增加模型可解释性 在花呗的异构数据上很work。 2. Background 背景信息 任务:欺诈检测,Fraud Detection 可视作分类任务,由于异常点的采集,标注极其耗费人力物力,数据集常为少量有标签数据(labeled data),及大...
The next section walks through an end-to-end credit card fraud detection workflow. This workflow uses TabFormer, a card transaction fraud dataset, and trains a R-GCN (relational graph convolutional network) model on a variation of the link prediction task in order to generate ...
In order to evaluate the efficiency of our proposed method, we compared the performance of QGNNs to Classical Graph Neural Networks using a real-world financial fraud detection dataset. The results of our experiments showed that QGNNs achieved an AUC of 0.85, which outperformed classical GNNs. ...
The first example of financial LLMs is BloombergGPT [Wu et al., 2023], which was trained on a mixed dataset of financial and general sources. Despite its impressive capabilities, access limitations exist, and the prohibitive training cost has motivated the need for low-cost domain adaptation. ...
Collect a rich dataset to drive smarter decisions with reduced false declines Comply with local regulations such as PSD2 and SCA Learn About ActiverAccess Service Implementers and Developers End-to-end testing facility for any 3DS solution built with EMVCo certified components ...
Collect a rich dataset to drive smarter decisions with reduced false declines Comply with local regulations such as PSD2 and SCA Learn About ActiverAccess Service Implementers and Developers End-to-end testing facility for any 3DS solution built with EMVCo certified components ...
Financial fraud negatively impacts organizational administrative processes, particularly affecting owners and/or investors seeking to maximize their profits. Addressing this issue, this study presents a literature review on financial fraud detection thro
Consequently, we mainly conduct these regressions to test their role played in fraud identification and observe their moderating effects. The rest of the paper is organized as follows. In section 2 we describe our dataset, in section 3 we present our results, in section 4 we resolve any ...
As such, the need for fraud detection systems to detect fraudulent acts after they have already been committed and the potential cost savings of doing so is more evident than ever. Anomaly detection techniques have been intensively studied for this purpose by researchers over the last couple of ...
结果发现,frauder和其out neibour的node features存在相对于normal 用户更大的差异,这个其实也make sense吧,物以类聚,人以群分,正常人填写的紧急联系人可能是和自己比较亲近的人,关系好的同事,朋友之类的,收入,年龄啊之类的可能差不多,而frauder的紧急联系人可能就不太一样了,毕竟你要去构造一群frauder 账户,...