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The article discusses the challenges faced by Anti-Money Laundering (AML) systems, particularly the high rate of false positives that burden financial institutions. It highlights the potential of Artificial Intelligence (AI) strategies, including machine learning, deep learning, and Natural Language Processing, to significantly reduce false positives and enhance detection accuracy. The paper also addresses regulatory and ethical considerations, advocating for a balanced approach that leverages AI while ensu

Author
vofal27045
Language
EN

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