Enhancing Transaction Monitoring Controls to Detect Money Laundering Using Machine Learning-Reference-Cited by-同舟云学术

Enhancing Transaction Monitoring Controls to Detect Money Laundering Using Machine Learning

Published:2022-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on e-Business Engineering (ICEBE)
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Author:

Oztas Berkan¹,Cetinkaya Deniz¹,Adedoyin Festus¹,Budka Marcin¹

Affiliation:

1. Bournemouth University,Department of Computing and Informatics,Bournemouth,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10035029/10034982/10035068.pdf?arnumber=10035068

Reference21 articles.

1. Isolation Forest

2. Profiling Money Laundering with Neural Networks: a Case Study on Environmental Crime Detection

3. Application of Cluster-Based Local Outlier Factor Algorithm in Anti-Money Laundering

4. Counter terrorism finance by detecting money laundering hidden networks using unsupervised machine learning algorithm;muhammed shokry;In IADIS International Conference on ICT Society and Human Beings,2020

5. A review of money laundering literature: the state of research in key areas

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1. Anti-money laundering and customer due diligence: empirical evidence from South Africa;Journal of Money Laundering Control;2023-12-06

2. Enhancing Anti-Money Laundering: Development of a Synthetic Transaction Monitoring Dataset;2023 IEEE International Conference on e-Business Engineering (ICEBE);2023-11-04

3. Perspectives from Experts on Developing Transaction Monitoring Methods for Anti-Money Laundering;2023 IEEE International Conference on e-Business Engineering (ICEBE);2023-11-04