Coronavirus (COVID-19) Update
Due to the Coronavirus (COVID-19) pandemic, any references to assessment tasks and on-campus delivery may no longer be up-to-date on this page.
Students should consult iLearn for revised unit information.
Find out more about the Coronavirus (COVID-19) and potential impacts on staff and students
Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Co-ordinator
Kathleen Clough
Level 3, 4ER Building, Room 313
Via Appointment
Moderator
Rahat Munir
Rahat Munir
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
ACCG6011 or ACCG611 or (admission to MActPrac or MBkgFin or GradCertForAccg or GradDipForAccg or MForAccgFinCri)
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
In this unit students will be exposed to the theory and application of data analytics skills and techniques in relation to fraud detection and identifying business risks. The unit will introduce students to mechanisms and principles relevant to tracing assets, investigating flow of funds and reconstructing accounting information. Visual and location analytic capabilities that use a variety of tools and techniques, along with external data sets, will be explored. The unit will also equip students with the capacity to appraise applications and strategies to enable collection, assessment, review, production and presentation of unstructured data. |
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Coronavirus (COVID-19) Update
Assessment details are no longer provided here as a result of changes due to the Coronavirus (COVID-19) pandemic.
Students should consult iLearn for revised unit information.
Find out more about the Coronavirus (COVID-19) and potential impacts on staff and students
Coronavirus (COVID-19) Update
Any references to on-campus delivery below may no longer be relevant due to COVID-19.
Please check here for updated delivery information: https://ask.mq.edu.au/account/pub/display/unit_status
Delivery
This unit requires intensive attendance, comprising of both online learning and face-to-face seminars at the University's campus.
DATE | TIME |
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Saturday, 7th March 2020 | 9 AM-12 PM, 1 PM-4 PM |
Saturday, 21st March 2020 | 9 AM-12 PM, 1 PM-4 PM |
Saturday, 4th April 2020 | 9 AM-12 PM, 1 PM-4 PM |
Saturday, 2nd May 2020 | 9 AM-12 PM, 1 PM-4 PM |
Details of assessments and online discussion forums will be available on iLearn.
Required and Recommended Texts and/or Materials
The unit is based upon a selection of reading materials including text chapters; professional reports; articles. Seminar content and reading materials are set out in the Unit Schedule herewith. Reading material will be accessible on iLearn (via Leganto) from the commencement of Session.
Face-to-face seminars may make use of PowerPoint; overhead projectors; visualisers.
There is a web page for this unit: https://unitguides.mq.edu.au/unit_offerings/112761/unit_guide.
Time Commitment
Students should be ready to allocate at least 150 hours during the session (in total) to ACCG8076. This includes all classes, assessments (estimates for assessment allocation are set out above under “Assessment Tasks”), personal study and other learning activities.
Coronavirus (COVID-19) Update
The unit schedule/topics and any references to on-campus delivery below may no longer be relevant due to COVID-19. Please consult iLearn for latest details, and check here for updated delivery information: https://ask.mq.edu.au/account/pub/display/unit_status
WEEK |
LEARNING OBJECTIVE |
CONTENT |
READINGS |
Week 1, Commencing 24th February 2020 |
LO1: Evaluate the theory, and principles of application, of data analytics skills and techniques relevant to forensic accounting |
Introduction to Fraud Types of Fraud The Need for Analysis Tools Matrices Link Diagrams Social Network Analysis Analysing Networks |
Forensic Accounting and Fraud Investigation for Non-Experts, H. Silverstone and M. Sheetz, Chapter 2, Fraud in Society
Forensic Accounting and Fraud Investigation for Non-Experts, H. Silverstone and M. Sheetz, Chapter 12, Analysis Tools for Investigators
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Week 2, Commencing 2nd March 2020 |
LO1: Evaluate the theory, and principles of application, of data analytics skills and techniques relevant to forensic accounting |
Introduction to Financial Analysis Key Ratios Data Mining as an Analysis Tool |
Forensic Accounting and Fraud Investigation for Non-Experts, H. Silverstone and M. Sheetz, Chapter 5, Fundamental Principles of Financial Analysis
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Face-to-Face Seminar, Saturday 7th March 2020 (9 AM – 12 PM, 1 PM – 4 PM) This face-to-face seminar will cover the Learning Objectives, Content and Readings as indicated in Weeks 1 and 2 above. |
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Week 3, Commencing 9th March 2020 |
LO1: Evaluate the theory, and principles of application, of data analytics skills and techniques relevant to forensic accounting |
Introduction to Data Mining Data Classification Association Analysis Cluster Analysis Outlier Analysis Application: Data Mining to Detect Money Laundering Tracing |
Statistical Techniques for Forensic Accounting, S. K. Dutta, Chapter 5, Understanding the Theory and Application of Data Analysis
Financial Investigation and Forensic Accounting, G. A. Manning, Chapter 14, Accounting and Audit Techniques |
Week 4, Commencing 16th March 2020 |
LO2: Investigate applications and strategies, including data mining, to enable collection, assessment, review, production and presentation of unstructured data |
Data Mining Routines Understanding the Integrity of the Data Understanding the Norm of the Data Entity Structures and Search Routines Strategies for Data Mining |
The Fraud Audit: Responding to the Risk of Fraud in Core Business Systems, L. W. Vona, Chapter 7, Data Mining for Fraud |
Face-to-Face Seminar, Saturday 21st March 2020 (9 AM – 12 PM, 1 PM – 4 PM) This face-to-face seminar will cover the Learning Objectives, Content and Readings as indicated in Weeks 3 and 4 above. |
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Week 5, Commencing 23rd March 2020 |
LO2: Investigate applications and strategies, including data mining, to enable collection, assessment, review, production and presentation of unstructured data |
Disbursement Fraud Payroll Fraud Fraud Risk Structure Data Analysis Data Mining Planning |
The Fraud Audit: Responding to the Risk of Fraud in Core Business Systems, L. W. Vona, Chapter 10, Disbursement Fraud
The Fraud Audit: Responding to the Risk of Fraud in Core Business Systems, L. W. Vona, Chapter 12, Payroll Fraud |
Week 6, Commencing 30th March 2020 |
LO2: Investigate applications and strategies, including data mining, to enable collection, assessment, review, production and presentation of unstructured data |
Revenue Misstatement Inventory Fraud Fraud Risk Structure Data Analysis Data Mining Planning |
The Fraud Audit: Responding to the Risk of Fraud in Core Business Systems, L. W. Vona, Chapter 13, Revenue Misstatement
The Fraud Audit: Responding to the Risk of Fraud in Core Business Systems, L. W. Vona, Chapter 14, Inventory Fraud |
Face-to-Face Seminar, Saturday 4th April 2020 (9 AM – 12 PM, 1 PM – 4 PM) This face-to-face seminar will cover the Learning Objectives, Content and Readings as indicated in Weeks 5 and 6 above. CLASS TEST 20% |
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Week 7, Commencing 6th April 2020 |
LO3: Manage and interpret complex or disparate sets of data to underpin business development, interpret risk, understand behavioural patterns, and detect suspicious or irregular behaviour
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Industry Data Financial Analysis Types of Fraud Revisited Fraud Detection Interpreting Potential Red Flags Professional Scepticism Fraud Triangle Risk Factors Information Gathering Analytical Procedures and Techniques Sampling Theory Statistical Sampling Techniques Non-statistical Sampling Techniques |
Financial Investigation and Forensic Accounting, G. A. Manning, Chapter 24, Audit Programs
A Guide to Forensic Accounting Investigation, W. Kenyon and P. D. Tilton, Chapter 13, Potential Red Flags and Fraud Detection Techniques
Statistical Techniques for Forensic Accounting, S. K. Dutta, Chapter 9, Sampling Theory and Techniques |
MID-SEMESTER BREAK (13TH APRIL 2020 TO 26TH APRIL 2020) |
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Week 8, Commencing 27th April 2020 |
LO3: Manage and interpret complex or disparate sets of data to underpin business development, interpret risk, understand behavioural patterns, and detect suspicious or irregular behaviour |
Probability Schematic Representation of Evidence Probative Value of Evidence Constraints and Limitations of Data Analysis Collection of Data Data Analysis Tools Descriptive Statistics Models for Displaying Data Data Analysis Software Benford’s Law |
Statistical Techniques for Forensic Accounting, S. K. Dutta, Chapter 6, Transitioning to Evidence
Forensic Accounting, R. Rufus, L. Miller and W. Hahn, Chapter 8, Transforming Data into Evidence (Part 1)
Forensic Accounting, R. Rufus, L. Miller and W. Hahn, Chapter 9, Transforming Data into Evidence (Part 2) |
Face-to-Face Seminar, Saturday 2nd May 2020 (9 AM – 12 PM, 1 PM – 4 PM) This face-to-face seminar will cover the Learning Objectives, Content and Readings as indicated in Weeks 7 and 8 above. This seminar will also provide an introduction to the Learning Objectives, Content and Readings covered in Weeks 9 through to 12. CLASS PRESENTATION 20% |
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Week 9, Commencing 4th May 2020 |
LO4: Examine issues and key principles of professional digital forensic practice, including chain of custody and best practice procedures
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Critical Steps in Gathering Evidence Chain of Custody Evidence Created Introduction to Digital Forensics |
A Guide to Forensic Accounting Investigation, W. Kenyon and P. D. Tilton, Chapter 10, Building a Case: Gathering and Documenting Evidence
Essentials of Forensic Accounting, M. A. Crain and others, Chapter 11, Digital Forensics |
Week 10, Commencing 11th May 2020 |
LO4: Examine issues and key principles of professional digital forensic practice, including chain of custody and best practice procedures |
Forensic Soundness Forensic Analysis Fundamentals Crime Reconstruction Networks and the Internet |
Handbook of Digital Forensics and Investigation, E. Casey, Chapter 1, Introduction |
Week 11, Commencing 18th May 2020 |
LO5: Diagnose and appraise mechanisms to uncover or recover evidence from digital devices to support litigation and investigations
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Scientific Method and Digital Forensics Digital Forensic Analysis Data Gathering and Observation Conclusions and Reporting |
Handbook of Digital Forensics and Investigation, E. Casey, Chapter 2, Forensic Analysis |
Week 12, Commencing 25th May 2020 |
LO5: Diagnose and appraise mechanisms to uncover or recover evidence from digital devices to support litigation and investigations
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Introduction to Electronic Discovery Case Management Identification of Electronic Data Forensic Preservation of Data Data Processing Production of Electronic Data |
Handbook of Digital Forensics and Investigation, E. Casey, Chapter 3, Electronic Discovery |
Week 13, Commencing 1st June 2020 |
CRITICAL ESSAY 40% DUE ON TUESDAY 2nd JUNE 2020 (2 PM) |
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