A model for identifying relationships of suspicious customers in money laundering using social network functions

Abdul K. Shaikh, Amril Nazir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The impact on the development of the national economy is mostly dependent on the flow of money in the country. The suspicious transactions of money within financial institutions affect the national economic system and compromise the impression of country’s reputation. Identifying an individual suspicious transaction and individual suspicious customers within transactions are evident by using basic statistical rules. Other than such traditional rules, this paper proposes a model that discusses the identifications of association and relationships within transactions and customers using Social Networks Analysis (SNA). With the help of this model, groups and gang mafia can be identified who mainly play a vibrant role in money laundering activities.

Original languageEnglish
Title of host publicationProceedings of the World Congress on Engineering 2018, WCE 2018
EditorsLen Gelman, A. M. Korsunsky, David WL Hukins, Andrew Hunter, S. I. Ao
PublisherNewswood Limited
ISBN (Electronic)9789881404794
Publication statusPublished - Jan 1 2018
Event2018 World Congress on Engineering, WCE 2018 - London, United Kingdom
Duration: Jul 4 2018Jul 6 2018

Publication series

NameLecture Notes in Engineering and Computer Science
Volume2235
ISSN (Print)2078-0958

Conference

Conference2018 World Congress on Engineering, WCE 2018
CountryUnited Kingdom
CityLondon
Period7/4/187/6/18

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

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