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Copyright?2019McGraw-HillEducation.Allrightsreserved.NoreproductionordistributionwithoutthepriorwrittenconsentofMcGraw-HillEducation.
Instructor’sResourceManual
DataAnalyticsforAccounting
1stEdition
VernonJ.Richardson
RyanA.Teeter
KatieL.Terrell
TABLEOFCONTENTS
TotheInstructor 3
AssignmentSchedulesIncludingallChapters 6
PresentationSuggestions 7
Chapter
DataAnalyticsinAccountingandBusiness……….7
DataPreparationandCleaning………………9
ModelingandEvaluation:GoingfromDefiningBusinessProblemsandDataUnderstandingtoAnalyzingDataandAnsweringQuestions……….11
Visualizations:UsingVisualizationsandSummariestoShareResultswithStakeholders………13
TheModernAuditandContinuousAuditing………………….…15
AuditDataAnalytics……………..17
GeneratingKeyPerformanceIndicators…………19
FinancialStatementAnalytics……………………21
LabIntroduction…………..…..23
RequestingRemoteDesktopAccounts……………...…………...24
UARKRemoteDesktopFrequentyAskedQuestions…………26
ShortGuidetoConnectingtotheRemoteDesktopatUARK………………28
Labs…………………...…………31
DAA1eSoftwareAcademicLicensesandDownloads…………...33
Chapter1Labs………………………35
Chapter2Labs………………………36
Chapter3Labs………………………39
Chapter4Labs………………………40
Chapter5Labs………………………41
Chapter6Labs………………………41
Chapter7Labs………………………43
Chapter8Labs………………………43
TOTHEINSTRUCTOR
Thisguideincludessuggestedassignmentschedules,topicaloutlines,chaptercommentsandobservations,andsuggestedteamexercisesbasedontheauthorsexperienceteachingdataanalytics.
AssignmentSuggestions.Thistextbookisnotdesignedtobeasurveyofdataanalyticsinaccounting.Instead,itisintendedtodevelopstudentskillstosupportaccountant’srolesasdataanalysts.Consequently,werecommendthattheassignmentsincludetheproblemsandlabsthatwilldeveloptheseskillsandrequirecriticalthinking.Differentinstructorswillteachthiscoursedifferently,somechoosingtoonlyusethelabsoronlyincludethetext.Othershopingtocoverthistextbookineightweeks,insteadofafullfifteen-weekperiod.Theassignmentsuggestionsassumethatthismaterialwillbecoveredoverfifteen-weekperiod.
BriefTopicalOutlines.TheseoutlinesaredesignedtoassistinstructorsincoordinatingclassroomdiscussionswithmaterialcoveredinthetextbookandthePowerPoints.TheBriefTopicalOutlinesidentifytopicsthatwebelieveareimportantenoughtomeritsomeclassroomdiscussion.Theoutlinesalsoincludereferencestoillustrationsinthetextbook,PowerPoints,questions,problems,andcasesthatmayserveasusefulsupplementstoyourclasspresentations.
CommentsandObservations.Youwillprobablyfindthatourcommentsandobservationssuggestcoverageofmoretopicsthanyourtimewillallow.Thisisbecauseourcommentsaredrawnfromtheexperiencesofthreeinstructorsovermanysemesters.Therefore,wesuggestthatyouborrowfromourcommentsthatwhichappealstoyouanddiscardthatwhichdoesnot.
CourseDescriptionandObjectives.
Forinformationonly,weusethefollowingcoursedescriptionandobjectives:
CourseDescription
DataAnalyticsischangingthebusinessworld-datasimplysurroundsus!Withsomuchdataavailableabouteachofus(i.e.,howweshop,whatweread,whatwe’vebought,whatmusicwelistento,wherewetravel,whowetrust,etc.),arguably,thereisthepotentialforanalyzingthatdatainawaythatcananswerfundamentalbusinessandaccountingquestionsandcreatevalue.
Accordingtotheresultsof18thAnnualGlobalCEOSurveyconductedbyPwC,manyCEOsputahighvalueonDataAnalytics,and80%ofthemplacedataminingandanalysisasthesecond-mostimportantstrategictechnologyforCEOs.Infact,perPwC’s6thAnnualDigitalIQsurveyofmorethan1,400leadersfromdigitalbusinesses,theareaofinvestmentthattopsCEOs’listofprioritiesisbusinessanalytics.“DataDriven:Whatstudentsneedtosucceedinarapidlychangingbusinessworld,”byPwC,
/us/en/faculty-resource/assets/PwC-Data-driven-paper-Feb2015.pdf
,postedFebruary2015,extractedJanuary9,2016.
Thistextbookaddresseswhatwebelievewillbeasimilarimpactofdataanalyticsonaccountingandauditing.Forexample,wearguethatdataanalyticswillplayanincreasinglycriticalroleinthefutureofaudit.InarecentForbesInsights/KPMGreport“Audit2020:AFocusonChange”,thevastmajorityofsurveyrespondentsbelieveboththat:
auditorsmustbetterembracetechnologyand
technologywillenhancethequality,transparencyandaccuracyoftheaudit.
Nolongerwillauditorsbesimplycheckingforerrors,misstatedaccounts,fraud,andriskinthefinancialstatements,ormerelyreporttheirfindingsattheendoftheaudit.Throughtheuseofdataanalytics,auditprofessionalswillbecollectingandanalyzingthecompany’sdatasimilartothewayabusinessanalystwouldtohelpmanagementmakebetterbusinessdecisions.Inourtextbook,weemphasizeauditdataanalyticsandallthetestingthatcanbedonetoperformaudittesting.
Dataanalyticsalsopotentiallyhasanimpactonfinancialreporting.WiththeuseofsomanyestimatesandvaluationsinFinancialAccounting,somebelievethatemployingDataAnalyticsmaysubstantiallyimprovethequalityoftheestimatesandvaluations.Likewise,theuseofXBRLdatagivesaccountantsaccesstomoretimelyandmoreextensiveaccountingdataforfinancialanalysis.
Thistextbookrecognizesthataccountantsdon’tneedtobecomedatascientists–theymayneverneedtobuildadatarepositoryordotherealhardcoredataanalyticsormachinelearning–however,wedoemphasizesevenskillsthatwebelieveanalytic-mindedaccountantsshouldhave,includingthefollowing:
DevelopinganAnalyticsMindset-recognizewhenandhowdataanalyticscanaddressbusinessquestions
DataScrubbingandDataPreparation–comprehendtheprocessneededtocleanandpreparethedatabeforeanalysis
DataQuality–recognizewhatismeantbydataquality,beitcompleteness,reliabilityorvalidity
DescriptiveDataAnalysis–performbasicanalysistounderstandthequalityoftheunderlyingdataanditsabilitytoaddressthebusinessquestion
DataAnalysisthroughDataManipulation–demonstrateabilitytosort,rearrange,mergeandreconfiguredatainamannerthatallowsenhancedanalysis.
DefiningandAddressingProblemsthroughStatisticalDataAnalysis–identifyandimplementanapproachthatwillusestatisticaldataanalysistodrawconclusionsandmakerecommendationsonatimelybasis
DataVisualizationandDataReporting–reportresultsofanalysisinanaccessiblewaytoeachvarieddecisionmakerandtheirspecificneeds
Consistentwiththeseskillswedesireinallaccountants,werecognizethatDataAnalyticsisaprocess.Theprocessbeginsbyidentifyingbusinessquestionsthatcanbeaddressedwithdata,andthentestthedata,refineourtestingandfinally,communicatethosefindingstomanagement.WedescribeourdataanalyticsprocessbyusinganestablisheddataanalyticsmodelcalledtheIMPACTCycle,byIssonandHarriott:
IdentifytheQuestion
MastertheData
PerformTestPlan
AddressandRefineResults
CommunicateInsights
TrackOutcomes
CourseObjectives
Aftercompletingthiscourse,studentsshouldbeableto:
Describeindetailthepurposeofdataanalyticsandhowitcancreatevalueforaccountants.
DescribetheIMPACTmodelandhowitcanbeusedtoaddressmostaccountingissuesthatcanbeaddressedbyaccountants.
Demonstrateproficiencyinmultiplesoftwaretoolstomanagedata,performtestanalyses,communicatefindingsthroughtext,tablesandvisualizations.
Explainhowdataanalyticscanbeusedinaccounting,auditing,managerialaccountingandfinancialaccountingtofindpatterns,errors,andanomaliesandfindinsightsusefultodecisionmaking.
Describeanddemonstratedifferenttypesoftestapproachesthatcanbeusedtogatherinsightsindecisionmaking.
NotetoInstructorswhoplanonUsingComprehensiveLabswithDillard’sdata:
TheuseofDillard’sdatarequiresgainingaccesstothedatahousedattheUniversityofArkansas.
Foryourstudentstogainaccess,youwillneedtofollowtheproceduresoutlinedbelow.
Pleaseallowuptooneweekforfullaccess.
Forinstructors,werecommendthatyourequeststudentaccountsinadvancetoyourfirstlabusingtheComprehensiveCasewhichusesDillard’sdata.Oneyouhavearemoteaccessaccount,youcanlogintoaccesstheUniversityofArkansasserverusingoneofthefollowingsystems:Windows10App,Windows,orMac.Guidelinesforlogginginwitheachofthesesystemscanbefoundbelow:
RequestingRemoteDesktopAccounts
LoggingintoUARKRemoteDesktop–Window10App
LoggingintoUARKRemoteDesktop–Mac
LoggingintoUARKRemoteDesktop–WindowsLegacy
StillhaveQuestions?
UARKRemoteDesktopFAQ
VernonJ.Richardson
RyanA.Teeter
KatieL.Terrell
ASSIGNMENTSCHEDULEINCLUDINGALLCHAPTERS—Assignments
PRIVATE
Chapter
Topic
WrittenAssignment
ObjectiveQuestions
1
DataAnalyticsinAccountingandBusiness
Questions1-8,1-13,Problems1-1,1-2,1-3,1-4
MC1-1to1-10
1
Labs(iftimepermits)
Lab1-1and1-3
2
DataPreparationandCleaning
Problem2-1,2-3,2-4,2-5
MC2-1to2-10
2
Labs(iftimepermits)
Lab2-2and2-4
3
ModelingandEvaluation:GoingfromDefiningBusinessProblemsandDataUnderstandingtoAnalyzingDataandAnsweringQuestions
Problem3-1,3-3,3-5.3-6
MC3-1to3-22
3
Labs(iftimepermits)
Lab3-3and3-4
4
Visualizations:UsingVisualizationsandSummariestoShareResultswithStakeholders
Problem4-2,4-3,4-8and4-9
MC4-1to4-15
4
Labs(iftimepermits)
Lab4-2and4-3
5
TheModernAuditandContinuousAuditing
Problem5-4and5-5
MC5-1to5-10
5
Labs(iftimepermits)
Lab5-3and5-4
6
AuditDataAnalytics
Problem6-3,6-5,and6-7
MC6-1to6-10
6
Labs(iftimepermits)
Lab6-3and6-4
7
GeneratingKeyPerformanceIndicators
Problem7-1,7-5and7-7
MC7-1to7-10
7
Labs(iftimepermits)
Lab7-2and7-3
8
FinancialStatementAnalytics
Problem8-1,8-3,8-5
MC8-1to8-10
8
Labs(iftimepermits)
Lab8-1and8-2
PRESENTATIONSUGGESTIONS
CHAPTER1
DataAnalyticsinAccountingandBusiness
BriefTopicalOutline
A. Introduction
1. WhatisDataAnalytics?(PowerPoints1-5–1-8)
2. HowdoesDataAnaltyicsAffectBusiness?(PowerPoints1-9–1-11)
3. HowdoesDataAnalyticsAffectAuditing?(PowerPoints1-12,1-13)
4. HowdoesDataAnalyticsAffectFinancialReporting?(PowerPoint1-14)
5. HowdoesDataAnalyticsAffectTaxes?(PowerPoint1-15)
B. IntroductiontotheIMPACTModel(PowerPoint1-16–1-18)
1. IdentifytheQuestions(PowerPoint1-19)
2. MastertheData(PowerPoint1-20)
3. PerformtheTestPlan(PowerPoint1-21)
4.AddressandRefineResults(PowerPoint1-22)
5. CommunicateInsights(PowerPoint1-23)
6. TrackOutcomes(PowerPoint1-24)
C. DataAnalyticsSkillsNeededbyAccountants(PowerPoints1-26–1-29)
D. Hands-onExampleoftheIMPACTModel(PowerPoints1-30)
1. IdentifytheQuestions(PowerPoint1-31)
2. MastertheData(PowerPoints1-32,33,34)
3. PerformtheTestPlan(PowerPoints1-35–1-38)
4.AddressandRefineResults(PowerPoints1-39,40)
5. CommunicateInsights(PowerPoint1-41)
6. TrackOutcomes(PowerPoint1-42)
E. Summary–(PowerPoint1-44)
CommentsandObservations
Inourfirstclassmeeting,wediscussnotonlyabouttheroleofaccountantsasinformationprovider,butalsohowthatroleissteadilychangingtobecomeaninterpreterofdata.Thatis,toactivelylooktodataandtheinterpretationofthatdatatohelpanswerbusinessproblemsbydecidewhatquestionsneedanswering,whatinformationneedstobecollected,buildorensurethattheinformationsystemiscollectingit,analyzethecollectedinformationtomeetitsintendedpurpose.
Wethenstartdefiningdataanalyticsandhowitcreatesvalueinbusinessandthenmorespecificallywhatdataanalyticshasdoneandhasthepotentialofdoinginauditing,managerialaccounting,financialreportingandtaxes.
WethenintroducetheIMPACTmodel.TheIMPACTmodelservesasafoundationforthischapter,andforeachremainingchapter.Wealsouseitasafoundationforeachofthelabsthroughoutthetext.Wediscusseachofthesesteps,onebyoneandtalkaboutwhateachstepentailsandwhyitisimportant.
Wespendsometimenamingtheskillsneededbyaccountantsandwhatwewilldointhetextbooktohelpgetthemthere.
WewrapupthechapterbyillustratingtheIMPACTmodelwiththereal-worldLendingClubdata.WegothrougheachstepoftheIMPACTmodelonebyone,askingwhattypesofquestionsLendingClubwouldlikelywantansweredandfocusinontheloandecisionofwhethertoextendaloanornot.Thediscussioncontinuesbyaskingwhatdatacouldbeusedtoanswerthesequestionsifwecouldgetanydatawewanted,etc.Ithenjumpintothedatawiththemtoshowthemwhatisthere.Wetalkaboutdatacleaning,datatransformationandwhatassumptionswewouldneedtomaketodothat.Wealsodosomepivottablesanalysisandanswerthequestionofwhyloanswererejectedandinverselywhyloansareaccepted.
WhileIhaven’tdoneityet,IwonderedhowtheclassdiscussionwouldchangeifwestartedwithillustratingtheIMPACTmodelandtheLendingClubdata.Therearealwaysprosandconsofusingaflippedclassroommodel,butitissomethingthatyoumightconsider.
Oneofthegoalsofchapter1isforthestudentstoopentheirmindsandreallylearnwhatdataanalyticscandoforaccountants.Ibelievethischapterprovidesagoodintroductionandfoundationforwhatwillbeincludedinthetextbookandstarttoaddresstheskillsneeded.
SuggestedTeamExercise
Justasthediscussionofthequestionsthatcouldbeansweredwithdataanalytics,Ihavethemthinkofauditingdataandthinkwhatauditingissues/questionsauditorshavewithsalesandhowthatcouldtheycouldbeaddressedwithsay,thecompletesalesjournal.Ithinkitishelpfulforthestudentstomeetinlittlegroupsandseeiftheycanaddressthattopicandthenreporttheirfindingsreadyforafullclassdiscussion.
CHAPTER2
DataPreparationandCleaning
BriefTopicalOutline
Introduction(Powerpoint2-2)
MastertheData(PowerPoint2-4)
TheUseofRelationalDatabases((PowerPoints2-5and2-6)
HowareDataStoredinRelationalDatabases(PowerPoints2-7–2-10)
TheUseofaDataDictionary(PowerPoint2-11)
Extract,TransformandLoad(PowerPoints2-13–2-14)
Step1:Determinethepurposeandscopeoftherequest(PowerPoint2-15)
Step2:ObtaintheData(PowerPoints2-16–2-20)
Step3:ValidatetheDataforCompleteness(PowerPoint2-21)
Step4:CleantheData(PowerPoint2-22)
Step5:LoadtheDataforDataAnalysis(PowerPoint2-23)
Summary(PowerPoint2-25)
CommentsandObservations
Aswejourneythroughtheimpactmodel,afteridentifyingthequestion,westartlookingatthedata.So,thediscussionmightbeginbysaying,ifwehadallavailabledatatoanswerthisquestion,whatdatawouldweuse.Weaskquestionslike:
Whatdataisavailabletoaddressthekeyquestion?Isthereasystemthatalreadycapturesthatdata?
Whatisthequalityofthedata?Isitreliable?Isitbiased?Whydoesthatmatter?
Wherediditcomefrom(internalvs.externalsources),etc.?Whydoesthatmatter?
Ilikegoingthroughthebasicsofrelationaldatabasesagain.Theywon’tadmittorememberingitfromtheirAIScourse,iftheywerefortunatetohavetakenonebeforethiscourse.Thiswillhelpthemunderstandhowdatamightcomefromtheirdatasetsandpreparethemforsomeofthelabswherejoiningdifferenttablesusingtheprimaryand/orforeignkeysmightberequired.IalsopointoutthedatadictionaryforadatasetlikeLendingCluborDillards(particularlyifyouhavealreadycoveredtheseinclassinChapter1).
Itisimportanttoknowwhatdatayouneed,andthenbeingabletoaskforthatdatainacompleteway.Youcertainlydon’twanttokeepgoingbacktothedatasourcetoaskforadditionaldata.Andyouprobablycan’tjustaskforallofthedatabecauseitisoftenjusttoobigtouseitall!Onceyouhavethedatayouneedtovalidatethatyougotwhatyouaskedforandassessthedataqualityandthencleanthedataandgetitreadyforitsintendeduse.AsnotedinChapter1,dataanalystsspendbetween50and90%oftheirtimecleaningandpreparingthedataaspartofETL(Extract,Load,andTransfer).Thefinalstepistoloadthedatainsometypeofanalysisprogram,whichoftendependsonthetestapproachused,yourownfamiliaritywiththesoftwarepackagesandwhetheryouwanttousemoreofananalysispackage(suchasExcelorSASorWeka,etc)oravisualizationprogram(suchasTableau).
SuggestedTeamExercise
GivenaccesstotheLendingClubdata,Iliketostarttheteamexercisebyhighlightaloanacceptance/rejectiondecisionthatabankmustmake.Andsaysomethinglike,asateam,“writedownallofthedatayou’dliketoknowaboutanindividualbeforedecidingwhethertoextendaloanandifyoudoextendaloan,theinterestratethatyouwouldlikelygivethem”.Allowtheteamafull8-15minutestoputtogetherthedataneeds.Iallowstudentstothenpresenttheirfindings.
IthentakeovertheclassdiscussionAfterthat,welookatthedatadictionarysayingwhatisIdownloadtherawdatasetoftheloanrejectiondecisionsmadebyLendingClub.Iletthemseewhatdataisavailableandwhatcharacteristicstheyhave–aretheynumeric,aretheyranked,aretheymachinereadable,etc.?Wethenopenthedatasetofloanrejections–Igenerallyuse2013asitwillfitinExcelandseewhatissuesthereareincleaningthedata.Forexample,howdoyoudoanalysisiftheloandatasaysyearsofworkexperience“10+”insteadof“10”?Howdoyoubuildthatintoyouranalysis?Whatdoyoudowithmissingdata?Theseareallimportantquestionsthattheywillneedtostartaddressingastheybecomedataanalysts!
CHAPTER3
ModelingandEvaluation:GoingfromDefiningBusinessProblemsandDataUnderstandingtoAnalyzingDataandAnsweringQuestions
BriefTopicalOutline
Introduction(PowerPoints3-2-3-5)
DataModelingandTestApproaches
Targetvs.Class(PowerPoint3-6)
SupervisedvsUnsupervisedApproaches(PowerPoints3-7-3-11)
ProfilingTestApproach(Powerpoints3-12-3-16)
DataReductionTestApproach(Powerpoints3-17-3-20)
RegressionTestApproach(Powerpoints3-21-3-24)
ClassificationTestApproach(Powerpoints3-25–3-32)
ClusteringTestApproach(Powerpoints3-33–3-36)
Summary(Powerpoint3-37)
CommentsandObservations
Inchapter3wedescribedatamodelingandvarioustestapproachesthataremostlikelytobeusedinaccountingandauditing.Ibeginbydifferentiatingbetweenatargetandaclass.Acreditscoreisagoodexampleofatarget,especiallybecauseIhavealreadycovereditinChapter1withtheLendingClubexample.Agoodexampleofaclassistheaccept/rejectdecisionthatanauditormakeswhendecidingwhetherornottotakeonanewclient.
Thediscussionthenmigratestounsupervisedvs.supervisedapproachesandwhetherornotwehaveaspecificquestion.Overall,arewetryingtofindpatterns(liketoCostCocustomersclusterintoidentifiablegroups)orhowoftendocustomersthataremorethan120dayslatepaytheamountsowed?Wethenintroducethevarioustypesofunsupervisedandsupervisedapproaches.Itrytocomeupwithanexampleofeachbecausethathelpsstudentsunderstandwhatwearetryingtosay.
Studentscanunderstandthisinformationandusuallythatisdeterminedbyhowgoodtheexampleswecomeupwith.
SuggestedTeamExercise
Therearemanypossibilitiesforteamexercises.Onemightbetohaveagrouptakeeachofthevarioustestapproachandcomeupwithanexampleofwhatfitsinthatspace.Givethemthewholelistoftestapproachesandgivethem10minutestotrytocomeupwithanexample.Forexample,whatisanaccountingproblemthatmightinvolveprofiling?
Alternatively,Ilikehavingstudentscomeupwithindependentvariablesforaregression.Sinceoneofmyresearchpapersfrom15yearsagopredictsthestockmarketreactiontoarestatementannouncement,Iwouldaskthestudentstotellmecharacteristicsofarestatementthatmightpredictthestockmarketresponseandthenfinallyputupwhatwefoundinourpaper.Ialwaysenjoyanexcusetobringresearchintotheclassroomandhere’smychance.
Palmrose,Zoe-Vonna,VernonJ.Richardson,andSusanScholz."Determinantsofmarketreactionstorestatementannouncements."
JournalofAccountingandEconomics
37.1(2004):59-89.
CHAPTER4
Visualizations:UsingVisualizationsandSummariestoShareResultswithStakeholders
BriefTopicalOutline
Introduction(Powerpoints4-2–4-4)
PurposeofDataVisualization(Powerpoint4-5)
QualitativevsQuantitative(Powerpoints4-6,4-7)
Declarativevs.Exploratory(Powerpoints4-8-4-10)
TypesofCharts(Powerpoints4-11–4-23)
RefiningtheCharts(Powerpoints4-24–4-29)
UseofWordingtoCreateInsight(Powerpoints4-30-4-35)
Summary(Powerpoint4-36)
CommentsandObservations
Ifindstudentsreallyenjoyvisualizations.Theyaregoodconsumersofitandnowthehopeisthattheybecomegoodproducersofit.
Studentshavenotusuallypreviouslythoughtmuchabouttypesofdata(qualitativevs.quantitative;declarativevs.exploratory).So,Iliketogiveabunchofexamples,oftencenteredaroundPowerpointslides4-7and4-8.Theexamplesusedontheslidearegood,butIliketopauseinmypresentationandhavethemthinkofothersimilarexamplesthatworkordon’twork.Iusuallylikeitwhentheymentionthewrongexampleofanindividualtypeandexplainingwhythatproposedvisualizationwon’tworkandthenwhereitdoesfit.
Ithenlikeslide4-10whichasksthequestionfromanotherdirectionandstatesherewehavesomedatasoisitqualitativeorquantitative;declarativeorexploratory?Ilikeslide4-17showinghowsomechartsillustratebiasoratleastmagnifythebias.Thesubsequentslidesshowinsomedetailtheprinciplesinshowinggoodvisualizations.
SuggestedTeamExercise
IfindstudentsarereallyhandyattheirlaptopsandgettingvisualizationsfromGoogleImages,etc.OnepossibleexercisemightbeforthestudenttosearchinGoogleImagesfor“WorstVisualizations”,“BiasedBarCharts”orthelike.ThenthestudentteamsprepareaPowerpointpresentationexplainingwhytheyarebadvisualizationsandthenreplacingthemwithwhattheyproposearegoodvisualizations.Hopefully,theotherstudentsintheclassroomwillthenrespondbyquestioningthepresentinggroupandofferingideasoftheirown.
CHAPTER5
TheModernAuditandContinuousAuditing
BriefTopicalOutline
Introduction(Powerpoints5-1-5-4)
TheModernAudit(Powerpoint5-5–5-10)
SummaryofAnalyticsAids(Powerpoints5-11)
EvaluateAuditData(Powerpoints5-12)
Homogeneousvs.HetereogeneousERPSystems(Powerpoints5-12–5-16)
AuditDataStandards(Powerpoints5-17–5-19)
SelectAppropriateAuditTasksandApproaches(Powerpoints5-20–5-26)
EvaluateAuditAlarmsinContinuousAuditing(Powerpoints5-27–5-33)
UnderstandWorkingPaperPlatforms(Powerpoint5-34–5-39)
Summary(Powerpoints5-40–5-41)
CommentsandObservations
Asyourecall,Chapters1-4laythefoundation,principallyfocusedaroundtheIMPACTmodelthatweusethroughoutthetext.Chapters5and6illustratetheIMPACTmodelspecificallyintheauditcontext(andsubsequentlyChapters7and8illustratestheIMPACTmodelinthemanagerialandfinancialaccountingcontextrespectively.Chapter5beginsbydiscussinghowdataanalyticsmightbeusedinthemodernaudit.Iliketothinkofthisdiscussionasthe“I”intheIMPACTmodeltohelpidentifythequestions.
Thenextlearningobjectiverevolvesaroundthechallengesingettingandevaluatingtheauditdata.UnlessthestudentshavetakenanERPclassorknowsomethingmoreaboutthem,IusuallyfindtheyhaveverylittleideaofhowERPsystemswork.ThediscussionofhomogeneousandheterogeneoussystemsleadstoagooddiscussionofhowERPsystemswork.Buteveniftherearehomogeneoussystems,therestillmightbeachallengeingettingthedatafromtheclient.Iusuallyhaveagoodsetofstudentsthathavebeenassociatedwitharecentauditandthechallengessometimesingettingtheappropriatedatafromtheclient.Thereason,oftentimes,thedatamightcomefromvarioussourcesanditmayneedtobecombinedinaspecificway.Wethentalkabouttheauditdatastandards.Igenerallywillgointosomedetailaboutwhattheauditdatastandardsdo,whytheyarevaluabletoauditorandauditeeandhowtheymaysetupameansofcontinuousauditinginthenot-so-distantfuture.
LearningObjective5-3and5-4involveadiscussionoftheauditplan.Itisagoodrefresherforthosewhohavetakentheauditclassand/orgoneonanauditinternship.IthinkitisanecessarydiscussionbeforegettingtotheauditalarmsandauditexceptionsthatmightbepartofacontinuousmonitororcontinuousauditdiscussioninLearningObjective5-5.
InLearningObjective5-6,Iliketostartthediscussionbytalkingabouttheroleofauditingincollectingevidencetosupportanauditjudgment,possiblyanauditopinion.Theresultsofthetestingdonewithdataanalyticsalsorequiresdocumentation.Orperhapsevenhowtheauditorrespondedtoanauditalarmorexception.Thismakestheresultsofdataanalyticsusefulinanaudit.
SuggestedTeamExercise
Oneideaforateamexerciseistodiscussauditexceptionsandalarms.
Herearesomepossiblescenarios:
Let’ssaywecollectdataonwhoentersmanualjournalentries(thoseenteredbyhumans).Howwouldwesetthethresholdonanalarm?Inotherwords,whenwouldwe,asaninternalauditor,wanttobeinformedthatanexceptionhadbeenmadeandwhatwouldwedowithit?
Whenwouldwewanttobenotifie
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