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Overcoming Transaction Screening Challenges with Advanced Technology

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18 July 2022
Neil Katkov

Improving Efficiency and Accuracy with Machine Learning and Natural Language Processing

Abstract

Anti-money laundering operations are challenged by regulatory risk due to false negatives (missed suspicious cases) as well as inefficiencies due to high false positive rates. The sanctions function is a particular pain point in terms of both operational burden and exposure to regulatory actions.

The regulatory risk around sanctions has driven banks to build up large teams of sanctions analysts—numbering in the hundreds or even thousands at tier 1 banks—to work these alerts. In this way, the false positives problem has led to significant increases in operational costs, particularly over the past five years.

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