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SolutionsManual–Chapter3
SolutionstoDiscussionQuestions
Whatisthedifferencebetweenatargetandaclass?
Atargetisaspecificattributeorvaluethatananalystistryingtoevaluate,suchasaninterestrateorscore.Aclassisacategoryorgroupingthatadataobjectisassignedto,suchasfraudornotfraud.
Whatisthedifferencebetweenasupervisedandanunsupervisedapproach?
Thesupervisedapproachreliesonananalysisofpastdatatopredicttheclassassignmentorregressedvalueforanewunknownobservation.Classificationandregressionarepopularsupervisedmodels.Anunsupervisedapproachisusedtoexploredataanddiscoverpreviously-unknownpatterns.Clusteringandprofilingarecommonunsupervisedmodelsthathelpresearchersidentifygroupsofdatathatmaynotbeobvious.
Whatisthedifferencebetweentrainingdatasetsandtest(ortesting)datasets?
Supervisedmodelsrelyonpreviously-analyzedhistoricaldatatopredictfutureoutcomes.Forexample,anauditormayidentifyfraudulenttransactionsandlabelthoseasfraud.Aportionofthatdataisusedtotrainthemodel,meaningthatatoolanalyzesthehistoricaltrainingdataandtriestoidentifytheattributesthatarethebestpredictorsofaclassorvalue.Oncethemodelhasbeendeveloped,anotherportionofthehistoricaldataisusedtotestthemodeltoseewhichvaluethemodelpredictsforthatdata.Thetoolthencomparesthepredictedvaluesinthetestdatasetstotheactualvaluesinthetestdatasettoevaluatethemodelforaccuracy.Asetofhistoricaldatacanbesplitmanywaysintotrainingandtestingdatasets.
UsingFigure3-5asaguide,whatarethreedataapproachesassociatedwiththesupervisedapproach?
Classification,Causalmodeling,andregression.
UsingFigure3-5asaguide,whatarethreedataapproachesassociatedwiththeunsupervisedapproach?
Profiling,co-occurrencegrouping,andclustering.
Howmightthedatareductionapproachbeusedinauditing?
Onceanauditorhasidentifiedtypesofdatathatarehighrisk(e.g.transactionsonweekends,vendorswithP.O.Boxaddresses)theymayfilterthedatatoshowonlythosetypesoftransactions(basedonthedate,oraddressfieldinthiscase).
Alsomentionedinthechapterarefilteringonsuspiciousvendornames,sequencechecks,andgapdetection.
Howmightclassificationbeusedinapprovingordenyingapotentialfraudulentcreditcardtransaction?
Inthisanalysis,theclassassignedtoaspecificcreditcardtransactionwouldbeeither“fraud”or“notfraud”.Historicalrecordswouldbeassignedoneofthesetwoclasses,basedoncustomerclaims,etc.Aclassificationmodelwouldusepartofthishistoricaldatatotrainamodeltoidentifytheattributesthatarethebestpredictersofafraudulenttransaction.Thentheremainingdatawouldbeusedtovalidatethemodelandtestforaccuracy.
Howissimilaritymatchingdifferentfromclustering?
Similaritymatchinghasaspecificgoalinmind,suchastryingtofindcustomerswhoarelikeyourbestcustomers.Inthiscase,wehaveaspecifictargetandaretryingtolocatesimilarobjects.Clusteringisanattempttofindnaturalgroupingswithoutbeingdrivenbyaspecificpurpose.Clusteringismoreexploratorywheresimilaritymatchingassumesyouknowwhatyou’relookingfor.
Howdoesfuzzymatchwork?Giveanaccountingsituationwhereitmightbemostuseful?
Afuzzymatchusesprobabilitytoshowlikelymatches,basedonhowmuchthetwovalueshaveincommon.Forexample,tworecordsthatcontainaddresseswithsomedefinedpercentageofmatchingcharacterswouldbeconsideredafuzzymatch.Thisallowsauditorstofindrecordsthatapproximateeachotherinthecasewhereanemployeemighttrytoconcealaconnectionbyvaryingthevaluestoavoidexactmatches.
Compareandcontrasttheprofilingdataapproachandthedevelopmentofstandardcostforaunitofproductionatamanufacturingcompany?Aretheysubstantiallythesameordotheyhavedifferences?
Dataprofilingmaybeusedtodetermineproductioncostandvolumebehaviortodetermineabenchmarkforfuturecostandvolume.Thisislikewhatamanagerofamanufacturingcompanydoesindeterminingstandardcostforaunitofproduction.Theyareverysimilarinthatthegoalistocalculateabenchmarkforcontrollingpurposes.
Themaindifferencesisthatdataprofilingcanincorporatealargeramountofdata(suchasmarkettrends,changingfuelprices,orweatherpatterns)toautomaticallygenerateandcontinuallyupdateamoreprecisebenchmark.
Figures3-1through3-4suggestthatvolumeanddistancearethebestpredictorsof“daystoship”forawholesalecompany?Anyothervariablesthatwouldalsobeusefulinpredictingthenumberof“daystoship”?
Answersvary,butsomesuggestedvariablesmightbenumberofemployeesworking,dayoftheweek,logisticscapacity,temperature,etc.
SolutionstoProblems
Relatedpartytransactionsinvolvepeoplewhohaveclosetiestoanorganization,suchasboardmembers.Assumeanaccountingmanagerdecidesthatfuzzymatchingwouldbeausefultechniquetofindundisclosedrelatedpartytransactions.Whatdatawouldthemanagerneedtotestforrelatedpartytransactions?Whatwouldtheprocesslooklike?
Toperformfuzzymatching,themanagerwouldneedalistofrelatedpartiesandtheircontactinformation.Additionally,shewouldneedthecontactinformationforvendorsandcustomersthatparticipateincompanytransactions.
Themanagerwouldjointherelatedpartycontacttablewiththevendorand/orcustomercontactinformation.Sinceitislikelythattheaddresseswillbesimilarbutnotexact,usingthefuzzymatchtoolinExcelorIDEAwouldhavethemanagerselectthesimilarfields,inthiscaseaddressandzipcode.Themanagerwouldthenreviewthetransactionsthatinvolvevendorsorcustomersthatmatchtoseeiftheyarerelatedpartytransactions.
Anauditoristryingtofigureoutiftheinventoryatanelectronicsstorechainisobsolete.Whatcharacteristicsmightbeusedtohelpestablishamodelpredictinginventoryobsolescence?
Answersmayvary.Theauditormaylookatsimplemetricssuchastheageoftheinventory(e.gbasedonpurchasedate),orratios(e.g.turnoverforspecificproducts).Ifthereisarecordofinventorythathasbeendeemedobsoleteinthepast,theauditorsmaybeabletodevelopamodelbasedoncharacteristicsofthoseitems(e.g.size,type,manufacturer).Aclassificationmodelwoulddeterminetheprobabilityofwhichitemsareobsoleteornotobsoleteandcouldbeusedtoevaluateaclient’scompleteinventory.
Anauditoristryingtofigureoutifthegoodwillitsclientrecognizedwhenitpurchasedafactoryhasbecomeimpaired.Whatcharacteristicsmightbeusedtohelpestablishamodelpredictinggoodwillimpairment?
Goodwillimpairmentiscalculatedusingatwo-steptest.Firsttheauditormustdeterminewhetherthegoodwillisimpairedbycomparingthebookvaluewiththefairvalue.Thentheauditormustcalculatetheimpliedfairvalueofgoodwillandcollectevidenceastowhethermanagementrecordedtheimpairment.
Amodelwouldneedtolookatbothquestionsbasedoninput(e.g.accountbalances)fromthegeneralledgeranddeterminantsoffairvalue(e.g.marketdata,assessmentdata).Tocreateatrulypredictivemodel,theauditorwouldcollectdataonimpairmentfromotherclientsandusethoseobservationstobuildamodelthatcouldbeusedtopredictwhetheranewclientisalsoimpaired.
Thisprovidesaninterestingdiscussiononprivacyconcerns.Forexample,wouldaclientbewillingtosharedatathatcouldbeusedtobuildamodelfortheauditors?Mostlikely,no.Couldtheauditorbuildamodeliftheirclienthadmultipleacquireddivisionswithahistoryofimpairment?Probably,yes,buttheremaynotbesufficientobservationstomakeanaccurateenoughprediction.
Howmightclusteringbeusedtoexplaincustomersthatoweusmoney(accountsreceivable)?
Oneformofclusteringthatisalreadyusedforaccountsreceivableistheagingofaccounts.Theaginggroupsaccountsbyhowoldthereceivableis,withtheexpectationthatolderaccountsarelesslikelytobecollected.
Agingreliesononlyonedimension,time,andfocusesonthetransaction,notthecustomer.Clusteringmaybeusefulindeterminingwhethercustomersformnaturalgroupingsrelativetotheirabilitytopaytheirbills,basedoncorrelatedattributes,suchaslocation,size,volumeoforders.
Ifwehavegooddatathatshowswhichcustomershavehadaccountswrittenoff,wemayexpandthismodeltopredictthelikelihoodofnonpaymentbyusingaclassificationmodel.
Whywouldtheuseofdatareductionbeusefultohighlightrelatedpartytransactions(e.g.,CEOhasherownseparatecompanythatthemaincompanydoesbusinesswith)?
Answerswillvary.Datareductioncanbeusedtofiltertransactionsonspecificattributes.Byremovingunrelatedtransactionsfromtheanalysis,managementoranauditorcouldclearlyseethescopeandvolumeoftransactionsandeitheracceptthosewithadisclosureormakearecommendationtoimplementbetterinternalcontrolstopreventthemfromoccurring.
HowcouldXBRLbeusedbyaninvestortodoananalysisoftheindustry’sinventoryturnover?
AssumingXBRLdataisvalidandaccurate,aninvestorwouldidentifyspecificaccounttags(e.g.InventoryNet,
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