Neo4j Aura Graph Analytics Demo: Fraud Detection in P2P Networks

In this technical walkthrough, we demonstrate how to use Neo4j Aura Graph Analytics to detect fraud in a peer-to-peer payment graph. You'll see how to construct a graph from user transaction data, enrich it with shared identifiers, and use community detection and weakly connected components algorithms to identify suspicious account clusters.

You’ll learn how to

• Model real-world payment networks as knowledge graphs for fraud detection
• Use entity resolution techniques to enrich graph data and surface hidden relationships
• Leverage the Neo4j Aura Graph Analytics serverless architecture and cost-efficient model

If you're building fraud detection systems and exploring the use of graph analytics, this video offers a practical, end-to-end example using real-world patterns and production-ready tooling.