Enhancing Transaction Monitoring Controls to Detect Money Laundering Using Machine Learning
Authors: Oztas, B., Cetinkaya, D., Adedoyin, F. and Budka, M.
Conference: 18th IEEE International Conference on E-Business Engineering (ICEBE)
Dates: 14-16 October 2022
https://eprints.bournemouth.ac.uk/37921/
Source: Manual
Enhancing Transaction Monitoring Controls to Detect Money Laundering Using Machine Learning
Authors: Oztas, B., Cetinkaya, D., Adedoyin, F. and Budka, M.
Conference: IEEE International Conference on E-Business Engineering (ICEBE) 2022
Pages: 1-3
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.
https://eprints.bournemouth.ac.uk/37921/
https://conferences.computer.org/icebe/2022/index.html
Source: BURO EPrints