金融交易数据驱动的图谱网络智能化欺诈侦测

针对当前金融领域营销场景中商户与持卡人团伙化的交易欺诈行为难以侦测、挖掘的不足的问题，该文基于交易流水数据，构建了持卡人-商户的智能化交易图谱网络，建立了图拓扑特征体系框架和机器学习的异常检测算法，对当前营销欺诈团伙化网络进行了智能化侦测.基于相关样本数据提出的模型效果比传统模型具有较大提升，对欺诈团伙证据链挖掘和画像分析提供了有效方法.

Financial Transaction Data Based Intelligent Fraud Graph Network Detection

Nowadays, fraud risk has been changing from individual fraud to group fraud, leading to jump rise of financial payment. How to identify and detect the group fraud is becoming a challenge in risk management. To deal with the group fraud transaction, this article builds a transaction graph network based on financial transaction data, and founds a topological graph feature extraction framework and anomaly detection model. Experiment on sample data shows that the proposed model obtains better results comparing with the previous individual feature analysis models, and gives reasonable explanation and evidence for the fraud detection.