In the battle against money laundering and fraud, data silos are the trenches where crimes often occur—and where it’s also possible for IT departments to get thrown off course in their AML efforts by mistakenly detecting crimes that don’t exist.


“Companies have lots of silos of data that are used for different purposes at the institution, and there’s a lot of chance for errors that lead to false positives and false leads,” says John Sabatini, a principal at Ernst & Young, who just finished a report on AML with Erin McAvoy.


Many banks are currently undergoing projects to centralize data management across the enterprise to cut costs, reduce energy use and improve customer-facing activities.
But the initiatives also provide a chance to cut down on inaccuracies. Sabatini says there are both corporate and tech strategies that can be deployed to mitigate these false positives, including the creation of a single corporate function to oversee AML, fraud and trade surveillance—a European business model that’s being used by a large U.S. card firm that Sabatini wouldn’t identify.


Also helpful are analytical tech platforms such as data visualization, which allows graphic representation of data sets on a dashboard or other device. Providers include firms such as Tableau, whose customer roster includes Bank of America, Barclays, Citigroup and Fifth Third; Panopticon, whose clients include JPMorgan Chase; and Dundas, whose customers include RBS, Credit Suisse, UBS and American Express. 


“Data visualization is really hot right now. These tools allow you to look deep into data bases and do checks to ensure quality,” says Sabatini, saying there’s been a substantial increase in data visualization platforms, though he didn’t quantify the growth.

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