This document discusses how Neo4j can be used for fraud detection by analyzing transaction data as a graph. It begins by describing common types of fraud and fraudsters. Traditional fraud detection uses discrete, endpoint-centric analysis but has weaknesses in detecting complex fraud patterns. Neo4j allows for connected analysis of relationships that can reveal fraud rings and other complex patterns in real-time. The document demonstrates Neo4j's fraud detection capabilities with a live transaction graph demo and discusses how Neo4j fits into a typical fraud detection architecture by providing a 360-degree view of relationships across different data sources.