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Predictive audit analytics

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TitleInfo
Title
Predictive audit analytics
SubTitle
evolving to a new era
Name (type = personal)
NamePart (type = family)
Kuenkaikaew
NamePart (type = given)
Siripan
DisplayForm
Siripan Kuenkaikaew
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Vasarhelyi
NamePart (type = given)
Miklos
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Miklos Vasarhelyi
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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)
Gal
NamePart (type = given)
Graham
DisplayForm
Graham Gal
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)
2013
DateOther (qualifier = exact); (type = degree)
2013-10
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
The traditional audit is retroactive in nature and requires some time to process and is subject to substantial latency. With the evolution of technology, assurance processes could be automated and accelerated to provide more frequent and may be preventive audits. This study contributes to the assurance literature by proposing an audit framework that is more responsive to current business needs. Using the traditional continuous auditing as a basis, the first essay proposes the predictive audit framework. The predictive audit is a forward looking process that utilizes predictive analytics to estimate possible outcomes of business activities, and allow auditors to execute their work proactively. The predictive audit differs from the traditional audit in several aspects such as control approach, objective, and frequency. The preventive audit is defined as a predictive audit with filtering rules to block highly probable faulty transactions prior to their execution. The second essay examines the application of the predictive audit on a bank’s real business data set to determine potential irregularities. This study aims to assist internal auditors concerning the validity of sales transactions. The possible outcome of the sale transaction is identified using three machine learning techniques: decision trees, logistic regression, and support vector machine. The results show that logistic regression outperforms other algorithms. With a proper sales variables selection, the predictive model could accurately predict results with high accuracy, true positive rates, as well as a reasonably low false positive rate. The robust results of the predictive audit can be used as a baseline to create screening rules for the preventive audit. In the third essay, the predictive audit is deployed to determine the possible results of credit card sales transactions. Consequently, the filtering rule constructs are derived from the predictive model. These rules can be implemented at the beginning of the business process as the preventive audit to flag or block transactions before they are executed. Alternatively, the filtering rules can be applied to the results of the predictive audit to reduce a number of transactions that auditors have to investigate. The rules significantly increase the possibility of discovering problematic transactions.
Subject (authority = RUETD)
Topic
Management
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_5103
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
ix, 137 p. : ill.
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = vita)
Includes vita
Note (type = statement of responsibility)
by Siripan Kuenkaikaew
Subject (authority = ETD-LCSH)
Topic
Auditing--Data processing
Subject (authority = ETD-LCSH)
Topic
Bank examination
RelatedItem (type = host)
TitleInfo
Title
Graduate School - Newark Electronic Theses and Dissertations
Identifier (type = local)
rucore10002600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3S46PZQ
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
Kuenkaikaew
GivenName
Siripan
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2013-09-30 21:33:11
AssociatedEntity
Name
Siripan Kuenkaikaew
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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Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
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