Neo4j is being used by leading financial institutions to model and monitor data about customers, accounts, devices, locations, and other attributes to identify fraudulent activity from fraud rings using synthetic and stolen identities. Traditional relational database technologies are not suitable for this task due to their complexity and scalability issues. Graph databases, like Neo4j, provide an ideal tool for overcoming these hurdles with intuitive query languages like Cypher that enable real-time detection of fraud rings by navigating connections in memory. A Fortune 500 financial services company has seen significant improvements in reducing fraudulent transactions annually after adopting Neo4j's real-time graph analysis and simple data visualization capabilities. The company can now analyze customer information and related data more efficiently, allowing analysts to make fast and accurate decisions, thereby strengthening their position against less-prepared competition.