Data analytics for internal auditors:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton ; London ; New York
CRC Press
[2017]
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| Schriftenreihe: | Internal Audit and IT Audit
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXII, 417 Seiten |
| ISBN: | 9781498737142 |
Internformat
MARC
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Datensatz im Suchindex
| _version_ | 1804177367104487424 |
|---|---|
| adam_text | Titel: Data analytics for internal auditors
Autor: Cascarino, Richard E
Jahr: 2017
Contents
About the Author xiii
Introduction xv
Chapter 1 Introduction to Data Analysis 1
Benefits to Audit 2
Data Classification 5
Audit Analytical Techniques 7
Data Modeling 7
Data Input Validation 8
Getting the Right Data for Analysis 9
Statistics 11
Chapter 2 Understanding Sampling 15
Population Sampling 15
Sampling Risk 17
General Advantages 20
Planning the Audit 20
Data Analysis Objectives 21
Characteristics of Populations 21
Population Variability and Probability Distributions 22
Binomial Distributions 22
Poisson Distribution 23
Continuous Probability Distributions 24
Normal Distribution 24
Uniform Distributions 25
Exponential Distribution 26
Central Tendency and Skewed Distributions 26
Population Characteristics 27
Chapter 3 Judgmental versus Statistical Sampling 29
Judgmental Sampling 29
Hie Statistical Approach 31
Sampling Methods 31
Calculation of Sample Sizes 36
Attribute Sampling Formula 36
Classic Variable Sampling Formula 38
PPS Sampling Formula 38
Selecting the Sample 40
Interpreting the Results 41
Nonparametric Testing 42
Confusing Judgmental and Statistical Sampling 43
Common Statistical Errors 43
Chapter 4 Probability Theory in Data Analysis 45
Probability Definitions 45
Classical Probability 46
Empirical Probability 47
Subjective Probability 48
Probability Multiplication 48
Conditional Probability 48
Bayes Theorem 50
Use in Audit Risk Evaluation 51
Other Uses 52
Financial Auditing 52
Overstatement of Assets 53
Probability Distributions 53
Chapter 5 Types of Evidence 55
Influencing Factors 55
Quantity Required 57
Reliability of Evidence 57
Relevance of Evidence 58
Management Assertions 58
Audit Procedures 59
Documenting the Audit Evidence 60
Working Papers 60
Working Paper Types 60
Contents of Permanent File 62
Contents of Current File 63
Selection 63
Client Background 63
Internal Control Descriptions 64
Audit Program 64
Results of Audit Tests 64
Audit Comment Worksheets 65
Report Planning Worksheets 65
Copy of the Audit Report 65
Follow-Up Program 65
Follow-Up of Prior Audit Findings 66
Audit Evaluation 66
Ongoing Concerns 66
Administrative/Correspondence 66
General Standards of Completion 66
Cross-Referencing 66
Tick Marks 67
Notes 68
Working Paper Review 68
General Review Considerations 69
Working Paper Retention/Security 70
Chapter 6 Population Analysis 71
Types of Data 71
Correspondence Analysis 72
Factor Analysis 72
Populations 74
Sampling Error 75
Central Tendency 76
Variation 77
Shape of Curve 80
Chapter 7 Correlations, Regressions, and Other
Analyses 83
Quantitative Methods 83
Trend Analysis 83
Chi-Squared Tests 85
Correspondence Analysis 86
Cluster Analysis 86
Graphical Analysis 88
Correlation Analysis 88
Audit Use of Correlation Analysis 90
Learning Curves 91
Ratio and Regression Analysis 92
The Least Squares Regression Line 93
Audit Use of Regression Analysis 94
Linear Programming 94
Parametric Assumptions 96
Nonparametric Measurement 96
Kruskal-Wallis Analysis of Variance (ANOVA) Testing 96
Chapter 8 Conducting the Audit 99
Audit Planning 99
Risk Analysis 100
Determining Audit Objectives 104
Compliance Audits 105
Environmental Audits 106
Financial Audits 106
Performance and Operational Audits 107
Fraud Audits 107
Forensic Auditing 108
Quality Audits 110
Program Results Audits 110
IT Audits 111
Audits of Significant Balances and Classes of Transactions 112
Accounts Payable Audits 114
Accounts Receivable Audits 115
Payroll Audits 116
Banking Treasury Audits 116
Corporate Treasury Audits 117
Chapter 9 Obtaining Information from IT Systems
for Analysis 119
Data Representation 119
Binary and Hexadecimal Data 119
Binary System 119
Hexadecimal System 119
ASCII and EBCDIC 120
Fixed-Length Data 120
Delimited Data 121
Variable-Length Data 121
Databases 121
Definition of Terms 122
Principals of Data Structures 123
Database Structuring Approaches 123
Sequential or Flat File Approach 123
Hierarchical Approach 124
Network Approach 124
Relational Model 125
Data Manipulation 125
Terminology 126
Big Data 126
The Download Process 128
Access to Data 129
Downloading Data 129
Data Verification 130
Obtaining Data from Printouts 131
Sanitization of Data 131
Documenting the Download 132
Chapter 10 Use of Computer-Assisted Audit
Techniques 135
Use of CAATs 135
Standards of Evidence 136
Test Techniques 137
Embedded Audit Modules (SCARFs—System Control
Audit Review Files) 139
CAATs for Data Analysis 139
Generalized Audit Software 141
Application- and Industry-Related Audit Software 143
Customized Audit Software 144
Information Retrieval Software 144
Utilities 144
Conventional Programming Languages 144
Common Problems 145
Audit Procedures 146
CAAT Use in Non-Computerized Areas 147
Getting Started 147
CAAT Usage 149
Finance and Banking 150
Government 151
Retail 154
Services and Distribution 155
Health Care 155
General Accounting Analyses 157
Chapter 11 Analysis of Big Data 159
Online Analytical Processing (OLAP) 161
Big Data Structures 162
Other Big Data Technologies 164
Hive 167
Statistical Analysis and Big Data 167
R 168
Chapter 12 Results Analysis and Validation 171
Implementation of the Audit Plan 172
Substantive Analytical Procedures 173
Validation 175
Data Selection Bias 177
Questionnaire Analysis 177
Use of Likert Scales in Data Analysis 178
Statistical Reliability Analysis 179
Chapter 13 Fraud Detection Using Data Analysis 181
Red Flags and Indicators 181
Pressure Sources 181
Changes in Behavior 182
General Personality Traits 182
Nature of Computer Fraud 184
Computer Fraud Protection 185
Cloud Computing 186
Information Fraud 187
Seeking Fraud Evidence 188
Chain of Custody 189
Starting the Process 190
Detecting e-Commerce Fraud 198
Business-to-Consumer (B2C) 200
Business-to-Business (B2B) 200
Fraud Detection in the Cloud 201
Planning the Fraud Analysis 202
Common Mistakes in Forensic Analysis 203
Chapter 14 Root Cause Analysis 205
Chapter 15 Data Analysis and Continuous Monitoring 211
Monitoring Tools 216
Software Vendors 218
Implementing Continuous Monitoring 220
Overcoming Negative Perceptions 223
Potential Benefits 224
Chapter 16 Continuous Auditing 225
Continuous Auditing as Opposed to Continuous Monitoring 225
Implementing Continuous Auditing 227
Structuring the Implementation 228
Perceived Downsides of Continuous Auditing 230
Actual Challenges 232
Obtaining Support 233
Maintaining the Support 234
Chapter 17 Financial Analysis 237
Analyzing Financial Data 238
Balance Sheet 240
Income Statement 242
Statement of Cash Flows 243
Creative Revenue Enhancements 246
Depreciation Assumptions 246
Extraordinary Gains and Losses 246
Use of Ratios 247
Horizontal Analysis 252
Vertical Analysis 252
DuPont Analysis 252
Subsidiary Ledgers 254
Accounts Payable Analysis and Reconciliation 256
Analysis of Duplicate Payments 257
Payments for Goods or Services Not Received 257
Financial Database Analysis 258
Achieving Appropriate Discounts 259
Analyzing Accounts Receivable 259
Chapter 18 Excel and Data Analysis 263
Excel Data Acquisition 265
Excel Functions 266
Excel Database Functions 266
Excel Financial Functions 267
Financial Analysis Using Excel 268
DuPont Analysis 268
Z Score Analysis 269
Graphing and Charting 270
ACL Add-On 271
Chapter 19 ACL and Data Analysis 275
Access to Data 275
Importing Data into ACL 276
Joining and Merging Tables 279
Starting the Analysis 280
Analysis Options 280
ACL Tools 282
ACL Scripts 282
ACL Script Editor 283
Script Recorder 283
Creating from a Table History 283
Creating from Log Entries 284
Exporting a Script 284
Copying from Another ACL Project 284
Continuous Monitoring/Auditing in ACL 284
Data Visualization 285
Chapter 20 IDEA and Data Analysis 287
CaseWare IDEA* 287
General Usage 288
Sampling 289
Excel 290
Access 291
Print Report and Adobe PDF Files 291
Text Files 293
Chapter 21 SAS and Data Analysis 297
Operating Environment 298
Importing and Analyzing Data 299
SAS Usage 301
SAS and Fraud Detection 301
Enterprise Case Management 301
Chapter 22 Analysis Reporting 303
Conventional Internal Audit Report Writing 303
Audit Reporting 304
General Audit Reporting and Follow-Up 305
Clear Writing Techniques 306
Subheadings 309
Basic Report Structures 309
Executive Summary 309
Background, Scope, and Objectives 310
Summary of Major Findings 310
Audit Opinion 310
Detailed Findings 311
Recommendations 312
The Technical Analytical Report 313
Polishing and Editing the Report 316
Distributing the Report 317
Following Up 318
Chapter 23 Data Visualization and Presentation 321
Communication Modes 321
Choosing Visuals for Impact 324
Non-Quantitative Visualization 330
Big Data Visualization 330
Using Visualizations 331
Choosing the Tool 332
Internal Audit Usage 335
Making Visualization Effective 336
Chapter 24 Conclusion 337
Where Are We Going? 338
What Stays the Same? 340
Skilling-Up for the Job 340
Specialists or Generalists 341
Centralized or Decentralized 342
Analytical Problems Now and in the Future 343
Getting Hold of the Data 344
Appendix 1: ACL Usage 347
Appendix 2: IDEA Usage 359
Appendix 3: Risk Assessment: A Working Example 389
INDEX 393
|
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| isbn | 9781498737142 |
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| spelling | Cascarino, Richard E. 19XX- (DE-588)1186191880 aut Data analytics for internal auditors Richard E. Cascarino Boca Raton ; London ; New York CRC Press [2017] © 2017 XXII, 417 Seiten txt rdacontent n rdamedia nc rdacarrier Internal Audit and IT Audit Unternehmen (DE-588)4061963-1 gnd rswk-swf Innenrevision (DE-588)4072820-1 gnd rswk-swf Unternehmen (DE-588)4061963-1 s Innenrevision (DE-588)4072820-1 s DE-604 Erscheint auch als Online-Ausgabe 978-1-4987-3715-9 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029625951&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Cascarino, Richard E. 19XX- Data analytics for internal auditors Unternehmen (DE-588)4061963-1 gnd Innenrevision (DE-588)4072820-1 gnd |
| subject_GND | (DE-588)4061963-1 (DE-588)4072820-1 |
| title | Data analytics for internal auditors |
| title_auth | Data analytics for internal auditors |
| title_exact_search | Data analytics for internal auditors |
| title_full | Data analytics for internal auditors Richard E. Cascarino |
| title_fullStr | Data analytics for internal auditors Richard E. Cascarino |
| title_full_unstemmed | Data analytics for internal auditors Richard E. Cascarino |
| title_short | Data analytics for internal auditors |
| title_sort | data analytics for internal auditors |
| topic | Unternehmen (DE-588)4061963-1 gnd Innenrevision (DE-588)4072820-1 gnd |
| topic_facet | Unternehmen Innenrevision |
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