Financial institutions are struggling to keep pace with malicious, global criminal networks that constantly devise new and more complex ways to launder funds through legitimate financial systems. Legacy, rules-only anti–money laundering (AML) systems are at their breaking point and are no longer sufficient to combat increasingly sophisticated international money laundering networks.
“The best place to hide is in plain sight, and money launderers know that especially well. They deploy tactics that are difficult to detect without a holistic view of wider networks and relationships. They have broken rules-only AML systems.”
Financial institutions must fight money launderers in their own territory and operate beyond the constraints of rules-only AML systems. By leveraging graph analytics, banks can reveal complex webs of money laundering practices that might be overlooked by legacy systems. Now is the dawn of a new era when banks can boost security against invasive criminal activity to better protect their organizations, reputations, and customers.
Graph analytics is a mathematical model that investigates information in graph format, plotting data points as nodes and sketching relationships among those data points as edges. With the ability to assess connections, no matter how complex or distant, this technology helps banks piece together patterns that were unidentifiable until recently.
Many industries use this technology to gain previously undiscoverable insights and adhere to AML rules. Chief compliance officers stand to benefit from graph analytics as the solution can be extremely effective against malicious networks of money launderers and can strengthen compliance management systems.
“The fight against money laundering has reached a tipping point as effective AML mitigation is becoming more challenging in an ever-evolving regulatory and business ecosystem. With heavy reliance on rules-based detection and highly manual investigative processes, the financial services industry is rapidly embracing graph analytics technology. By visually connecting customers and parties, related accounts and payments, and other data, graph analytics can deliver more-holistic customer profiles, uncover hidden risks, and optimize financial crime detection and investigations while simultaneously easing the burden on staffing and elevating the customer experience.”
Oracle Financial Crime and Compliance Management incorporated graph analytics in 2018, based on research from Oracle Labs. Bolstered by our leadership in data, querying, processing, and visualizations, this technology strengthens institutions’ compliance with AML rules.
“With graphs, data can be managed in more intuitive ways, closer to how people organize their thoughts on a whiteboard. Our system takes advantage of parallel processing and the huge amounts of memory available in modern servers. This allows us to directly model the relationships among all our data.”
Learn more about how our suite of anti–money laundering software solutions can protect the integrity of your financial institution and improve compliance management effectiveness.