Explainable Feature Engineering for Multi-class Money Laundering Classification

This paper provides insight into typical money laundering typologies used in the financial crime domain and provides a concrete set of methods through the use of which fraudulent transactions may be classified using traditional machine learning algorithms and proving the efficacy of tree-based model...

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Bibliographic Details
Main Authors: Petre-Cornel GRIGORESCU, Antoaneta AMZA
Format: Article
Language:English
Published: Inforec Association 2025-01-01
Series:Informatică economică
Subjects:
Online Access:https://www.revistaie.ase.ro/content/113/06%20-%20grigorescu,%20amza.pdf
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