Graph databases are being used by companies to solve complex problems, such as fraud detection in financial services. Traditional methods of fraud detection often fail to minimize losses due to false positives and negatives, but graph technology offers a new approach through advanced contextual link analysis, which can uncover patterns that are difficult to detect using traditional representations. A Fortune 500 financial services company used Neo4j to solve this problem by reducing the time it took to process fraud detection queries, providing real-time results with connected data and data visualization, and enabling analysts to make faster, more accurate decisions. This has resulted in a significant reduction in wait times for non-fraudulent customers and a potential saving of thousands of dollars per day. Graph technology is essential for detecting elaborate fraud rings that traditional technologies are not designed to handle.