會(huì)計(jì)數(shù)據(jù)分析DAA-1e-IRM-2018-v3

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