SBS in ACAMS Today: Using Data Analytics to Identify AML Risk

28 Feb 2018
Date submitted
28 Feb 2018
Resource type
Other
File type
pdf PDF file (8.26M)
Data is the lifeblood of financial institutions and other organizations. It is used to run processes, manage financials, predict risk, prove compliance, target customers and influence decisions. In anti-money laundering (AML) and compliance, the data required to identify and combat financial crime is complex. It is also difficult to gather because data is often stored across a patchwork of legacy systems, new systems and siloed business-specific applications.
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