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Cluster analysis for anomaly detection in accounting

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TitleInfo
Title
Cluster analysis for anomaly detection in accounting
Name (type = personal)
NamePart (type = family)
Thiprungsri
NamePart (type = given)
Sutapat
NamePart (type = date)
1977-
DisplayForm
SUTAPAT THIPRUNGSRI
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Vasarhelyi
NamePart (type = given)
Miklos
DisplayForm
Miklos Vasarhelyi
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Kogan
NamePart (type = given)
Alexander
DisplayForm
Alexander Kogan
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Alles
NamePart (type = given)
Michael
DisplayForm
Michael Alles
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Ye
NamePart (type = given)
Jianming
DisplayForm
Jianming Ye
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - Newark
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2012
DateOther (qualifier = exact); (type = degree)
2012-01
CopyrightDate (qualifier = exact)
2012
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Cluster Analysis is a useful technique for grouping data points such that points within a single group or cluster are similar, while points in different groups are different. The objective of this study is to examine the possibility of using clustering technology for auditing. Automating fraud filtering can be of great value to continuous audits. In the first paper, cluster analysis is used to group transactions from a transitory account of a large international bank. Transactions are clustered based on the open comments field. Major types of transactions are discovered. These results provide a new knowledge about the nature of transactions that flow into transitory accounts. In the second paper, cluster analysis is applied to wire payments within an insurance company. Different anomaly detection techniques are examined. No wire transfer is flagged by all techniques. These results do not necessarily indicate that there is no real anomaly in the dataset, but that different assumptions, parameters or settings should be examined. In the third paper, cluster analysis is applied to group life insurance claims. Individual claims which have significantly different characteristic from other members in the same cluster as well as clusters which comprise of less than 2% of the population are identified as possible anomalies. Moreover, rule-based detection techniques are used to assist internal auditors in selecting claims for further investigation. Cluster analysis and rule-based detection can be combined for the efficiency and effectiveness of the implementation by internal auditors. Cluster analysis has been used extensively in marketing as a way to understand market segments and customer behavior. This study examines the application of cluster analysis in the accounting domain. It can be used for exploratory data analysis (EDA), but also can be used for anomaly detection (i.e. for audit purposes). The results provide a guideline and evidence for the potential application of this technique in the field of audit.
Subject (authority = RUETD)
Topic
Management
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_3811
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
xi, 167 p. : ill.
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = vita)
Includes vita
Note (type = statement of responsibility)
by Sutapat Thiprungsri
Subject (authority = ETD-LCSH)
Topic
Cluster analysis
Subject (authority = ETD-LCSH)
Topic
Auditing—Statistical methods
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10002600001.ETD.000063977
RelatedItem (type = host)
TitleInfo
Title
Graduate School - Newark Electronic Theses and Dissertations
Identifier (type = local)
rucore10002600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T35T3JHD
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
THIPRUNGSRI
GivenName
SUTAPAT
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2012-01-10 02:09:30
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Name
SUTAPAT THIPRUNGSRI
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - Newark
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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