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 systems have limited the ability for financial organizations to obtain holistic and connected views of parties, accounts, and transactions due to messy and fragmented data, inabilities in harnessing that data, and high numbers of false-positive alerts.
Graph algorithms combined with machine learning offer a more modern, intelligent, and streamlined approach in fighting, monitoring, and investigating illicit activity. These technologies enable a path to connected intelligence and elevated analytics.
Watch this webinar to:
- Discover how graph technology can dynamically connect parties, accounts, and transactions across disparate data sources, elevating financial crime detection, investigation, and intelligence.
- Learn how connections, patterns, and anomalies can drive productive investigations, inform the prioritization, hibernation, escalation of work and alert activity, and lead to better decision-making.
- Uncover techniques to integrate graph algorithms for machine learning into current financial crime strategies, processes, and systems.
