Financial crime encompasses various forms of wrongdoing, including money laundering, terrorism funding, corruption, tax evasion, and insurance fraud. Perpetrators use fake identities, middlemen, complex financial schemes, and other tactics to hide their tracks. Law enforcement agencies, financial institutions, and fraud detection professionals aim to uncover evidence of wrongdoing by utilizing graph technologies like Linkurious and Neo4j. These tools offer a holistic view of entities involved in financial crime and their relationships, enabling the identification of suspicious connections in real-time. Graph-powered anti-money laundering solutions, such as Linkurious Enterprise, integrate with Neo4j to store and query complex connected data, providing an additional layer of high-level services including authentication services, user access management, graph visualization, and full-text search. These solutions enable financial institutions to identify patterns, conduct advanced investigations, and visualize data using Cypher queries and graph browsers. By leveraging these tools, organizations can effectively combat financial crime and stay ahead of emerging threats.