safe-graph/graph-fraud-detection-papers
A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources
This is a curated collection of research papers and resources focused on detecting fraud, anomalies, and outliers using advanced techniques like graph analysis and transformer models. It helps financial analysts, cybersecurity experts, and risk managers discover the latest methods to identify unusual patterns in transaction data, network activity, or user behavior. The output is a structured list of academic papers and tools, providing insights into cutting-edge detection strategies.
1,794 stars. Actively maintained with 2 commits in the last 30 days.
Use this if you are a researcher or practitioner in fraud detection, cybersecurity, or financial risk management looking for a comprehensive overview of the latest academic work in graph-based and transformer-based anomaly detection.
Not ideal if you are looking for ready-to-use software tools or code implementations for immediate deployment, as this resource primarily focuses on academic papers.
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Jan 31, 2026
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