Why do we need Graph Features and Graph Neural Networks for Fraud Detection? See some reasons below:
- Class Imbalance, Label Scarcity & Fidelity (Fraud cases are rare events)
- Fraud Camouflage - handle context & feature inconsistency (i.e. fraudsters connecting to regular entities)
- Investigation and Exploration (visual way to connect the dots)
- Anomaly Detection - handle point, structural and contextual outliers
- Graph Embeddings - combined with NLP, could be used for scalable fuzzy search and entity resolution
- Explainability & fairness - adding the context and structure for interpretation, rebalancing the data to remove bias.
That is why Facebook, Amazon, Tencent, Alibaba and eBay are using Graph for Fraud Detection.