Tools
ToolsOztas, B., Cetinkaya, D., Adedoyin, F. and Budka, M., 2022. Enhancing Transaction Monitoring Controls to Detect Money Laundering Using Machine Learning. In: IEEE International Conference on E-Business Engineering (ICEBE) 2022, 14-16 October 2022, Bournemouth, UK, 1-3.
Full text available as:
|
PDF
Oztas_et_al_ExtendedAbstract_ICEBE22.pdf - Accepted Version Available under License Creative Commons Attribution No Derivatives. 294kB | |
|
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
Official URL: https://conferences.computer.org/icebe/2022/index....
Abstract
Money laundering has become a great economic problem with huge consequences on society and financial institutions in the last decade. Current anti-money laundering (AML) procedures within the industry are either inefficient due to criminals’ increasingly sophisticated approaches or technological advancements. This paper provides an extended abstract to identify and analyze the machine learning methods to detect money laundering through transaction monitoring in the literature. Moreover, the paper identifies research gaps and based on the observed limitations, suggests future research directions and areas in need of improvements.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Hybrid conference |
| Uncontrolled Keywords: | Anti-money laundering; artificial intelligence; money laundering; machine learning; suspicious transactions; transaction monitoring |
| Group: | Faculty of Science & Technology |
| ID Code: | 37921 |
| Deposited By: | Symplectic RT2 |
| Deposited On: | 20 Dec 2022 09:14 |
| Last Modified: | 20 Dec 2022 09:14 |
Downloads
Downloads per month over past year
| Repository Staff Only - |