How to Detect Fraud in Peer-to-Peer Networks Using Aura Graph Analytics

Learn how to detect fraud in peer-to-peer (P2P) financial networks using Neo4j Aura Graph Analytics. In this short video, you’ll see real-world examples of how to uncover hidden fraud rings using graph analytics, weakly connected components, and entity resolution techniques.
⚡ With billions in transactions flowing through P2P networks, traditional tools fall short in surfacing complex relationships between users. Aura Graph Analytics offers a scalable, serverless solution to detect suspicious activity faster and more accurately.

What you’ll learn:

• How to identify fraud using shared credit cards and IDs
• How to use weakly connected components for fraud detection
• Real-time graph projection and algorithm execution in AuraDB
• Why graph analytics outperform traditional SQL-based approaches
• How to uncover hidden connections and resolve entities

Explore Neo4j Aura Graph Analytics → https://neo4j.com/product/aura-graph-analytics
Get started with Neo4j AuraDB → https://neo4j.com/cloud/aura
Access the code and dataset on GitHub → https://github.com/neo4j-product-examples/aura-graph-analytics

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