{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T18:34:57Z","timestamp":1783708497706,"version":"3.55.0"},"reference-count":24,"publisher":"American Accounting Association","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,6,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n               <jats:p>Fraud detection is one of the key components of an internal control system that is designed to provide reasonable assurance regarding reliable financial statements, effective and efficient operations, compliance with applicable laws and regulations, and safeguarding of assets (AICPA 2002; Committee of Sponsoring Organizations of the Treadway Commission 1992). Practically, however, it is challenging to determine what should be investigated among myriads of a company's transactions, most of which are normal and\/or free from material error. Limited human resources and cost constraints are major barriers to fraud detection in practice. This study proposes a multi-step fraud detection model that screens transactions at various levels, which leads to a manageable number of transactions that internal auditors can examine. To that end, a broad screening criterion is applied at the highest level, while more detailed criteria are used at the lowest level. This study provides an example of development of a practicable fraud detection model.<\/jats:p>","DOI":"10.2308\/isys-50699","type":"journal-article","created":{"date-parts":[[2014,1,3]],"date-time":"2014-01-03T16:06:12Z","timestamp":1388765172000},"page":"145-165","source":"Crossref","is-referenced-by-count":17,"title":["Development of an Anomaly Detection Model for a Bank's Transitory Account System"],"prefix":"10.2308","volume":"28","author":[{"given":"Yongbum","family":"Kim","sequence":"first","affiliation":[{"name":"Ramapo College of New Jersey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Kogan","sequence":"additional","affiliation":[{"name":"Rutgers, The State University of New Jersey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1112","published-online":{"date-parts":[[2014,1,1]]},"reference":[{"key":"2024082915384843900_i1558-7959-28-1-145-AmericanInstituteofCertifiedPublicAccountantsAICPA1","unstructured":"American Institute of Certified Public Accountants (AICPA). 2002. Consideration of Fraud in a Financial Statement Audit. Statement on Auditing Standards No. 99. New York, NY: American Institute of Certified Public Accountants."},{"key":"2024082915384843900_i1558-7959-28-1-145-AssociationofCertifiedFraudExaminersACFE1","unstructured":"Association of Certified Fraud Examiners (ACFE). 2002. Report to the Nation on Occupational Fraud and Abuse. Austin, TX: ACFE."},{"key":"2024082915384843900_i1558-7959-28-1-145-AssociationofCertifiedFraudExaminersACFE2","unstructured":"Association of Certified Fraud Examiners (ACFE). 2004. Report to the Nation on Occupational Fraud and Abuse. Available at: http:\/\/www.acfe.com\/uploadedFiles\/ACFE_Website\/Content\/documents\/2004RttN.pdf"},{"key":"2024082915384843900_i1558-7959-28-1-145-AssociationofCertifiedFraudExaminersACFE3","unstructured":"Association of Certified Fraud Examiners (ACFE). 2007. Report to the Nation on Occupational Fraud and Abuse. Austin, TX: ACFE."},{"key":"2024082915384843900_i1558-7959-28-1-145-AssociationofCertifiedFraudExaminersACFE4","unstructured":"Association of Certified Fraud Examiners (ACFE). 2009. Occupational Fraud: A Study of the Impact of an Economic Recession. Austin, TX: ACFE."},{"key":"2024082915384843900_i1558-7959-28-1-145-AssociationofCertifiedFraudExaminersACFE5","unstructured":"Association of Certified Fraud Examiners (ACFE). 2010. Occupational Fraud: A Study of the Impact of an Economic Recession. Austin, TX: ACFE."},{"key":"2024082915384843900_i1558-7959-28-1-145-Bolton1","unstructured":"Bolton, R. J., and D. J.Hand. \n          2001. Unsupervised profiling methods for fraud detection. In Credit Scoring and Credit Control VII. Edinburgh, U.K.: Oxford University Press."},{"issue":"3","key":"2024082915384843900_i1558-7959-28-1-145-Bolton2","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1214\/ss\/1042727940","article-title":"Statistical fraud detection: A review","volume":"17","author":"Bolton","year":"2002","journal-title":"Statistical Science"},{"key":"2024082915384843900_i1558-7959-28-1-145-Campbell1","article-title":"Adding significant value with internal controls","author":"Campbell","year":"2006","journal-title":"The CPA Journal"},{"issue":"3","key":"2024082915384843900_i1558-7959-28-1-145-Chandola1","doi-asserted-by":"crossref","DOI":"10.1145\/1541880.1541882","article-title":"Anomaly detection: A survey","volume":"41","author":"Chandola","year":"2009","journal-title":"ACM Computing Surveys"},{"key":"2024082915384843900_i1558-7959-28-1-145-Committee1","unstructured":"Committee of Sponsoring Organizations of the Treadway Commission (COSO). 1992. Internal Control\u2014Integrated Framework. New York, NY: American Institute of Certified Public Accountants."},{"key":"2024082915384843900_i1558-7959-28-1-145-Jans1","first-page":"1","article-title":"A framework for internal fraud risk reduction at IT integrating business processes: The IFR framework","volume":"9","author":"Jans","year":"2009","journal-title":"The International Journal of Digital Accounting Research"},{"issue":"1","key":"2024082915384843900_i1558-7959-28-1-145-Kim1","doi-asserted-by":"crossref","first-page":"95","DOI":"10.2308\/jeta-50411","article-title":"A model to detect potentially fraudulent\/abnormal wires of an insurance company: An unsupervised rule-based approach","volume":"9","author":"Kim","year":"2012","journal-title":"Journal of Emerging Technologies in Accounting"},{"key":"2024082915384843900_i1558-7959-28-1-145-Kou1","unstructured":"Kou, Y., \n            \n              C. Lu, and S. Sirwongwattana. \n          2004. Survey of Fraud Detection Techniques: Networking, Sensing, and Control. Proceedings of the IEEE International Conference on Knowledge Discovery and Data Mining. Available at: http:\/\/metalab.uniten.edu.my\/\u223cabdrahim\/ntl\/Survey%20of%20Fraud%20Detection%20Techniques.pdf"},{"key":"2024082915384843900_i1558-7959-28-1-145-lLectricLawLibrary1","unstructured":"\u2018Lectric Law Library. 2014. Fraud, to Defraud. Available at: http:\/\/www.lectlaw.com\/def\/f079.htm"},{"key":"2024082915384843900_i1558-7959-28-1-145-Little1","doi-asserted-by":"crossref","unstructured":"Little, B. B., \n            \n              Johnston\n              W. L. Jr., \n            \n              A. C. Lovell, \n            \n              R. M. Rejesus, and S. A. Steed. \n          2002. Collusion in the U.S. Crop Insurance Program: Applied Data Mining. Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Edmonton, AB, Canada, July 23\u201325.","DOI":"10.1145\/775047.775135"},{"issue":"4","key":"2024082915384843900_i1558-7959-28-1-145-McEnroe1","doi-asserted-by":"crossref","first-page":"345","DOI":"10.2308\/acch.2001.15.4.345","article-title":"Auditors' and investors' perceptions of the \u201cexpectation gap.\u201d","volume":"15","author":"McEnroe","year":"2001","journal-title":"Accounting Horizons"},{"key":"2024082915384843900_i1558-7959-28-1-145-Phua1","unstructured":"Phua, C., \n            \n              V. Lee, \n            \n              K. Smith, and R. Gayler. \n          2005. A Comprehensive Survey of Data Mining-Based Fraud Detection Research. Available at: http:\/\/arxiv.org\/ftp\/arxiv\/papers\/1009\/1009.6119.pdf"},{"key":"2024082915384843900_i1558-7959-28-1-145-PublicCompanyAccountingOversightBoardPCAOB1","unstructured":"Public Company Accounting Oversight Board (PCAOB). 1972.Responsibilities and Functions of the Independent Auditor. Auditing Standard No. 110. 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Here's how businesses can protect themselves and their customers","author":"Sherman","year":"2002","journal-title":"Newsweek"},{"key":"2024082915384843900_i1558-7959-28-1-145-U.S.HouseofRepresentatives1","unstructured":"U.S. House of Representatives. 2002. The Sarbanes-Oxley Act of 2002. Public Law 107-204 [H. R. 3763]. Washington, DC: GPO."},{"key":"2024082915384843900_i1558-7959-28-1-145-Winn1","unstructured":"Winn, T. J., Jr. \n          \n          2004. Fraud Detection \u2013 A Primer for SAS\u00ae Programmers. 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