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Why graph analytics, you ask?

There's many reasons why anti-money laundering (AML) teams should pay attention to graph analytics. For starters, money laundering schemes are only going to continue evolving and becoming more complex. After all, money launderers excel at blending in. Without the right technology, it can be difficult to identify money laundering rings and signal suspicious activity. That's why traditional methods of investigation just aren't cutting it - and it's costing organizations billions of dollars per year. 

 

We took a closer look into some of the problems of today's AML compliance technology, how it impacts anti-money laundering efforts, and how graph analytics can provide a path forward for a more effective detection and investigation of AML cases

 

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Want to learn more?

Head over to our blog for more information on how graph analytics and AML are a match made in heaven!

You can also check out the next blog in our series for more examples of AML uses cases for graph analytics and reach out to us if you have any questions or would like to discuss your own use case! 

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