A European bank was asked to perform a look-back analysis on historical transactions by the Central Bank. Given the complexity of identifying such cases, it was reckoned that the rule based analysis may be over-simplistic and not yield many suspicious cases.
The bank sought our team’s help to provide advanced analytical capabilities including network analysis and anomaly detection to uncover complex patterns and potentially more relevant cases related to fraud red flags. We proposed a hybrid detection model, complimenting their existing AML systems, to the bank for the solve problem. This approach enabled the Bank to meet some of the more complex requirements defined by Central Bank that cannot be covered within the functionality of the existing AML solutions. Our engagement helped the bank to reduce false positives from 80% to 20%, and increase detection of false negatives by 75%.
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