🚀 Building a Graph-Based Fraud Detection System with Neo4j A single transaction may look normal....🚀 Building a Graph-Based Fraud Detection System with Neo4j A single transaction may look normal....
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🚀 Building a Graph-Based Fraud Detection System with Neo4j
A single transaction may look normal. Its connections can tell a different story.
I’m building a learning project using Neo4j and Cypher to explore relationships between customers, accounts, transactions, and devices—and flag patterns worth investigating.
🔍 Patterns I’m exploring:
• Multiple customers sharing the same device • Unusually large transactions • Rapid transactions within a short period • Multiple accounts sending money to one account • Circular transfers between connected accounts
The focus is explainability: showing the relationships behind each flag so the suspicious activity is easier to understand.
Through this project, I’m strengthening my graph data modelling, Cypher queries, and rule-based detection skills.
Next: FastAPI integration, transaction risk scores, fraud alerts, and an interactive monitoring dashboard.
🛠️ Currently a learning prototype, with more updates coming as I build.
What would you investigate first: shared devices or circular transfers?
#Neo4j #GraphDatabase #FraudDetection #Cypher #BackendDevelopment #LearningInPublic
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