Abstract 2 1.1Background 5 1.2ProblemStatement 6 1.3ResearchQuestions 7 1.4Researchobjective 8 2.1TheFraudDiamondModel 9 2.1.1OriginofFraudDiamondModel 9 2.1.2Theadditionalfactor 10 2.2TheFraudPentagonModel 10 2.3ComplexityofFraud 11 2.3.1Frameworks 11 2.3.2Typesoffrauds 12 2.4ImplementationofAIandmachinelearning 12 2.4.1NaiveBayesMethod 13 2.4.2ArtificialNeuralNetworkMethod 13 2.4.3SupportVectorMachineMethod 13 2.5ErrorsinInternalAuditing 14 2.5.1CommissionErrors 14 2.5.2OmissionErrors 14 2.5.3PrincipleErrors 14 2.5.4DuplicationErrors 14 2.5.5CompensationErrors 15 2.6Regulatoryissues 15 2.6.1InternationalAuditingregulations 15 2.6.2NationalAuditingStandards 16 2.6.3IndonesianAccountingStandards 17 2.7InternalControlsandRiskManagement 18 2.7.1RolesofInternalControl 18 2.7.2RolesofRiskmanagement 19 2.8ExternalAuditorExpertiseandQualifications 20 3.1Datacollection 21 3.2DataAnalysis 22 3.3TheAssessment 22 4.1Findings 23 4.1.1DatatakenfromPWCstandardoperatingprocedure 23 4.1.2DatatakenfromAksesmu 26 4.1.3Datatakenfromfinancialprocess 31 4.1.4Thetoolstheyusedintheiraudit 32 4.1.5DatatakenfromAksesmupastincident 33 4.1.6Datatakenfrominterview 33 4.2.1Discussion 35 4.2.2ComparingPWCSOPwithAksesmu 37 5.1Conclusion 40 5.2Recommendation 41 5.3Citations 42 5.4Appendices 43.