Build fraud detection systems using AWS Entity Resolution and Amazon Neptune Analytics

This article demonstrates how to build fraud detection systems for Card Not Present (CNP) transactions by combining AWS Entity Resolution with Amazon Neptune Analytics graph algorithms.

• AWS Entity Resolution matches and standardizes customer records across sources
• Neptune Analytics stores resolved entities and transactions as graph nodes and edges
• Graph algorithms like Louvain detect fraudulent clusters and suspicious patterns
• Weakly connected components identify related entities sharing PII attributes
• Risk scoring analyzes concentration of bad actors within customer groups
• Solution uses SageMaker notebooks for investigation and visualization
• Supports discovery of sophisticated fraud rings and indirect relationships

The solution enables financial institutions to efficiently detect CNP fraud by analyzing complex entity relationships and transaction patterns through graph-based analytics.