In today’s fast-paced and increasingly digital world, effectively combating financial crime and achieving regulatory compliance demands smarter, faster, and more dynamic tools and solutions. Legacy rules-based systems lack holistic and connected views of parties, accounts, and transactions due to fragmented data, inabilities to harness that data, and high false-positive rates. Graph algorithms combined with machine learning offer a more modern, intelligent, and streamlined approach in fighting, monitoring, and investigating illicit activity. Financial organizations can improve their understanding of risks and optimize AML performance with higher quality alerts that find suspicious activity missed by other solutions. Investigators can visualize the network of parties, accounts, and transactions to make more informed decisions.