Graph databases play a key role in fraud detection within intricate, complex networks, helping security teams keep pace with modern fraud techniques that are becoming increasingly more sophisticated. Graph databases can identify patterns and relationships in big data, reducing the level of complexity so that detection algorithms can effectively discover fraud attempts within a network.
Below, we will analyze how graph databases are revolutionizing fraud detection algorithms, highlighting key relationships that traditional data models cannot. Using real-world examples, this article will provide a comprehensive overview of how interconnected data can expose fraudulent activity such as money laundering.
