Literature on Various Anti-Money Laundering Techniques
R. Krishna Bharathi1, G. Kavitha2, Mary Linda I3
1R.Krishna Bharathi, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
2G.Kavitha, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
3Mary Linda I, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
Manuscript received on 13 September 2019 | Revised Manuscript received on 22 September 2019 | Manuscript Published on 10 October 2019 | PP: 198-200 | Volume-8 Issue-6S2, August 2019 | Retrieval Number: F10510886S219/19©BEIESP | DOI: 10.35940/ijeat.F1051.0886S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Laundering money is a method in which black money is converted into white cash. Anti-money laundering is a technique or procedure for finding such laundering operations. Although anti-money attempts began at an early point, the alternatives appear to be limited to a strategic level. Mostly criminal act offenders try to create the transactions look as innocent as possible. In order to explore a appropriate solution for suspect transaction detection, extensive study has been performed. But if the exchange is really suspect or not, there is no credible mechanism to verify and the method is also very tedious. This paper examines several methods and algorithms for the anti-money laundering system that have been suggested.
Keywords: Anti Money Laundering, AROMLD, Bitcoin, Bitmap Index-based Decision Tree.
Scope of the Article: Knowledge Engineering Tools and Techniques