This project was developed for Hackathon Bank Indonesia 2024, utilizing network graph analytics to detect fraudulent activities and syndicate behavior.
Fraud detection requires identifying hidden connections between entities. This project applies Heterogeneous Graph Transformer (HGT) models to analyze transaction networks, detect anomalies, and uncover syndicate activities.
- Graph-based fraud detection using network analytics
- HGT model implementation for analyzing complex relationships
- Automated pattern recognition to identify suspicious entities
- HGTmodel_Syndicate-Indication-using-Network-Graph-Analytics.py – HGT model implementation
- RAFM Working Group Proposal (PDF) – Proposal submitted for Hackathon Bank Indonesia 2024
This project demonstrates the potential of graph AI in financial fraud detection.