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Home > SAS > Developing Scenario Segmentation and Anomaly Detection Models
 

Developing Scenario Segmentation and Anomaly Detection Models

White Paper Published By: SAS
SAS
Published:  Oct 18, 2017
Type:  White Paper
Length:  12 pages

With enhanced regulatory pressure, banks must continuously evaluate their risks. To meet these demands, the AML industry has turned to analytical/statistical methodologies to reduce false-positive alerts, increase monitoring coverage and reduce the rapidly escalating financial cost of maintaining their AML programs. An effective AML transaction monitoring strategy includes segmenting the customer base by analyzing customer activity and risk characteristics in order to monitor them more effectively. This paper explains how to blend both quantitative and qualitative methods to tune scenarios to identify the activity that poses the most risk to the bank.



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