Modelling graph dynamics in fraud detection with "Attention"

1 code implementation • 22 Apr 2022 • Susie Xi Rao, Clémence Lanfranchi, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Mo Cheng, Yinan Shan, Yang Zhao, Ce Zhang

At online retail platforms, detecting fraudulent accounts and transactions is crucial to improve customer experience, minimize loss, and avoid unauthorized transactions.

Fraud Detection

Graph Neural Networks in Real-Time Fraud Detection with Lambda Architecture

no code implementations • 9 Oct 2021 • Mingxuan Lu, Zhichao Han, Zitao Zhang, Yang Zhao, Yinan Shan

Transaction checkout fraud detection is an essential risk control components for E-commerce marketplaces.

Fraud Detection graph construction

Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks

no code implementations • 20 Dec 2020 • Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Mo Cheng, Yinan Shan, Yang Zhao, Ce Zhang

Massive account registration has raised concerns on risk management in e-commerce companies, especially when registration increases rapidly within a short time frame.

Frame

xFraud: Explainable Fraud Transaction Detection

1 code implementation • 24 Nov 2020 • Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Zhiyao Chen, Yinan Shan, Yang Zhao, Ce Zhang

At online retail platforms, it is crucial to actively detect the risks of transactions to improve customer experience and minimize financial loss.

Graph Embedding

DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition

no code implementations • 10 Oct 2019 • Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang

Despite the wide application of Graph Convolutional Network (GCN), one major limitation is that it does not benefit from the increasing depth and suffers from the oversmoothing problem.