Research Paper#Fraud Detection, Graph Neural Networks, Ride-Hailing🔬 ResearchAnalyzed: Jan 3, 2026 16:05
GNNs for Fraud Detection in Ride Hailing
Analysis
This paper surveys the application of Graph Neural Networks (GNNs) for fraud detection in ride-hailing platforms. It's important because fraud is a significant problem in these platforms, and GNNs are well-suited to analyze the relational data inherent in ride-hailing transactions. The paper highlights existing work, addresses challenges like class imbalance and camouflage, and identifies areas for future research, making it a valuable resource for researchers and practitioners in this domain.
Key Takeaways
- •Provides a survey of GNN applications for fraud detection in ride-hailing.
- •Addresses challenges like class imbalance and fraudulent camouflage.
- •Identifies gaps and areas for future research in the field.
Reference
“The paper highlights the effectiveness of various GNN models in detecting fraud and addresses challenges like class imbalance and fraudulent camouflage.”