Identifying the signs of fraudulent accounts using data mining techniques
Abstract: In today’s technological society there are various new means to commit fraud due to the advancement of media and communication networks. One typical fraud is the ATM phone scams. The commonality of ATM phone scams is basically to attract victims to use financial institutions or ATMs to tra...
| Publicado en: | Computers in Human Behavior Vol. 28; no. 3; pp. 1002 - 1014 |
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| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
Elsevier B.V.
May2012
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=71908233&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 71908233 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07475632 JC4 jtl: Computers in Human Behavior issn: 07475632 maglogo: N pubinfo: dt: May2012 vid: 28 iid: 3 pid: 2410 pub: Elsevier B.V. artinfo: ui: 71908233 10.1016/j.chb.2012.01.002 ppf: 1002 ppct: 12 formats: tig: atl: Identifying the signs of fraudulent accounts using data mining techniques aug: au: Li, Shing-Han Yen, David C. Lu, Wen-Hui Wang, Chiang affil: Department of Information Management, Tatung University, 40 ChungShan North Road, 3rd Section, Taipei 104, Taiwan Department of Decision Sciences and Management Information Systems, Miami University, Oxford, OH 45056, United States Department of Computer Science and Engineering, Tatung University, 40 ChungShan North Road, 3rd Section, Taipei 104, Taiwan su: Fraud Information technology Banking industry Internet Automated teller machines Electronic funds transfers Data mining Financial institutions Transaction systems (Computer systems) Bayesian analysis Fraud prevention sug: subj: Fraud Information technology Banking industry Internet Computer and peripheral equipment manufacturing All other building equipment contractors Other Building Equipment Contractors Computer Terminal and Other Computer Peripheral Equipment Manufacturing Office and store machinery and equipment merchant wholesalers Office Equipment Merchant Wholesalers Other financial transactions processing and clearing house activities Savings Institutions Personal and commercial banking industry Commercial Banking Other Depository Credit Intermediation Financial Transactions Processing, Reserve, and Clearinghouse Activities Consumer Lending Internet Publishing and Broadcasting and Web Search Portals Wired Telecommunications Carriers Data Processing, Hosting, and Related Services Automated teller machines Electronic funds transfers Data mining Financial institutions Transaction systems (Computer systems) Bayesian analysis Fraud prevention keyword: ATM phone scams Dummy account Fraud detection Fraudulent account ATM phone scams Dummy account Fraud detection Fraudulent account ab: Abstract: In today’s technological society there are various new means to commit fraud due to the advancement of media and communication networks. One typical fraud is the ATM phone scams. The commonality of ATM phone scams is basically to attract victims to use financial institutions or ATMs to transfer their money into fraudulent accounts. Regardless of the types of fraud used, fraudsters can only collect victims’ money through fraudulent accounts. Therefore, it is very important to identify the signs of such fraudulent accounts and to detect fraudulent accounts based on these signs, in order to reduce victims’ losses. This study applied Bayesian Classification and Association Rule to identify the signs of fraudulent accounts and the patterns of fraudulent transactions. Detection rules were developed based on the identified signs and applied to the design of a fraudulent account detection system. Empirical verification supported that this fraudulent account detection system can successfully identify fraudulent accounts in early stages and is able to provide reference for financial institutions. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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