International Journal of Computer Networks and Applications

Tamer Hossam Eldin Helmy ¹, Mohamed Zaki Abd-ElMegied ², Tarek S. Sobh ³, Khaled Mahmoud Shafea Badran ¹

Affiliations
1 System and Computer Engineering, Military Technical Collage, Cairo, EG
2 Systems and Computer Department, Al Azhar University, Cairo, EG
3 Information System Department, Egyptian Armed Forces, Cairo, EG

Abstract

Money laundering is a global problem that affects all countries to various degrees. Although, many countries take benefits from money laundering, by accepting the money from laundering but keeping the crime abroad, at the long run, "money laundering attracts crime". Criminals come to know a country, create networks and eventually also locate their criminal activities there. Most financial institutions have been implementing anti-money laundering solutions (AML) to fight investment fraud. The key pillar of a strong Anti-Money Laundering system for any financial institution depends mainly on a well-designed and effective monitoring system. The main purpose of the Anti-Money Laundering transactions monitoring system is to identify potential suspicious behaviors embedded in legitimate transactions. This paper presents a monitor framework that uses various techniques to enhance the monitoring capabilities. This framework is depending on rule base monitoring, behavior detection monitoring, cluster monitoring and link analysis based monitoring. The monitor detection processes are based on a money laundering deterministic finite automaton that has been obtained from their corresponding regular expressions.

Keywords

Anti Money Laundering System, Money Laundering Monitoring and Detecting, Cycle Detection Monitoring, Suspected Link Monitoring.

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