Governments have been steadily strengthening AML rules to prevent money laundering activities. Financial institutions are now required to follow strict AML programs, to practice constant monitoring for suspicious activities, and to report on any suspected cases of money laundering. There is increased regulatory pressure, and compliance failures might be penalized with large penalties.
Analysts within financial institutions rely on risk-based AML analysis frameworks to monitor their customers and their financial transactions. But professionalized criminals deploy sophisticated tactics to hide their wrongdoings. They use shell corporations, tax havens, and complex financial fraud schemes to prevent identification or tracking of money flows. To thwart such criminal strategies, finding information about a specific suspicious entity is not enough. Financial crime units must investigate the connections between individuals, accounts, companies, locations, to trace complex transactions. This is why network analysis and visualization technologies have proven to be efficient tools to support AML analysis processes.
We explore below how to use a graph-based investigation platform such as Linkurious Enterprise to monitor high-risk customers through various layers of data.