A Semi-supervised Graph Attentive Network for Financial Fraud Detection

Understand

With the rapid growth of financial services, fraud detection has been a very important problem to guarantee a healthy environment for both users and providers.

• Conventional solutions for fraud detection mainly use some rule-based methods or distract some features manually to perform prediction.
• However, in financial services, users have rich interactions and they themselves always show multifaceted information.
• These data form a large multiview network, which is not fully exploited by conventional methods.