Improving Classification Performance of Money Laundering Transactions Using Typological Features
Author:
Affiliation:
1. Mae Fah Luang University,School of Information Technology,Chiang Rai,Thailand
2. Mae Fah Luang University,Center of Excellence in AI and Emerging Technologies School of Information Technology,Chiang Rai,Thailand
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10412852/10412856/10413155.pdf?arnumber=10413155
Reference20 articles.
1. Independent In-depth evaluation of The Global Programme against Money Laundering, Proceeds of Crime and the Financing of Terrorism;Arora;UNITED NATIONS,2017
2. Deep Learning and Explainable Artificial Intelligence Techniques Applied for Detecting Money Laundering–A Critical Review
3. Machine learning techniques for anti-money laundering (AML) solutions in suspicious transaction detection: a review
4. Detection of Money Laundering Transaction Network Structures and Typologies using Machine Learning Techniques;Visser,2020
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