Unit convenor and teaching staff |
Unit convenor and teaching staff
Nuraddeen Nuhu
Kathleen Clough
|
---|---|
Credit points |
Credit points
10
|
Prerequisites |
Prerequisites
ACCG6011 or ACCG611 or (admission to MActPrac or MBkgFin or MBusAnalytics or GradCertForAccg or GradDipForAccg or MForAccgFinCri)
|
Corequisites |
Corequisites
|
Co-badged status |
Co-badged status
|
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:
Name | Weighting | Hurdle | Due |
---|---|---|---|
Class Test | 20% | No | Week 6 |
Class Presentation | 20% | No | Week 9 |
Participation | 20% | No | Weekly |
Critical Essay | 40% | No | Week 12 |
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 18 hours
Due: Week 6
Weighting: 20%
The class test may include one, or a combination of, the following types of assessment: multiple-choice questions, true/false questions, short answer style questions, problem scenario or evidence- based questions.
Assessment Type 1: Presentation
Indicative Time on Task 2: 18 hours
Due: Week 9
Weighting: 20%
In this assessment students will deliver a 10-minute presentation that requires a consolidation of the theory, and application of data analytics skills and techniques to enable the assessment, review, and presentation of unstructured data relevant to advance a forensic accounting investigation. A summary report will be required to accompany the presentation.
Assessment Type 1: Participatory task
Indicative Time on Task 2: 20 hours
Due: Weekly
Weighting: 20%
This assessment involves evidence of preparation for, participation in, and contribution to seminars and online discussion forums.
Assessment Type 1: Essay
Indicative Time on Task 2: 34 hours
Due: Week 12
Weighting: 40%
In this assessment students will be required to critically reflect on the key issues and principles of professional digital forensic practice in the recovery of digital evidence to support an investigation. The submission should not exceed 2500 words.
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
Delivery
This is an online unit. 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 from text chapters. Reading material will be accessible via iLearn from the commencement of Session.
Seminars may make use of PowerPoint and videos.
Week |
Learning Objective |
Content |
1 |
LO1: Evaluate the theory, and principles of application, of data analytics skills and techniques relevant to forensic accounting |
This week covers fundamental principles of financial analysis and emphasizes the importance of due diligence, explores the reasons for conducting financial analysis, discusses trust considerations, highlights additional factors, addresses financial analysis for non-experts, and concludes with a forward-looking perspective. |
2 |
LO1: Evaluate the theory, and principles of application, of data analytics skills and techniques relevant to forensic accounting |
This week explores Analysis Tools for Investigators, beginning with an introduction. It delves into the reasons for using analysis tools, covering associational and temporal analysis, and concludes with a summarizing perspective. |
3 |
LO1: Evaluate the theory, and principles of application, of data analytics skills and techniques relevant to forensic accounting |
This week explores Data-Driven Fraud Detection and covers errors and frauds, the data analysis process, software tools, data access, analysis techniques, outlier investigation, stratification, summarization, real-time analysis, and the analysis of financial statements. |
4 |
LO2: Investigate applications and strategies, including data mining, to enable collection, assessment, review, production and presentation of unstructured data |
This week explores Cash Receipts and Other Asset Misappropriations and covers skimming schemes for cash and receivables, cash larceny schemes, noncash misappropriation schemes, concealing inventory shrinkage, and methods for preventing and detecting noncash thefts concealed by fraudulent support. |
5 |
LO2: Investigate applications and strategies, including data mining, to enable collection, assessment, review, production and presentation of unstructured data |
This week explores Cash Disbursement Schemes and covers billing, check tampering, payroll, expense reimbursement, and register disbursement schemes—providing insights into fraudulent practices and strategies for prevention and detection. |
WEEK 6: Class Test 20% |
||
6 |
LO2: Investigate applications and strategies, including data mining, to enable collection, assessment, review, production and presentation of unstructured data |
This week explores Financial Statement Fraud and covers the who, why, and how of financial reporting fraud, the intersection of accounting principles and fraud, various fraudulent financial statement schemes, the role of the capital forum, methods for detecting such schemes, and strategies for deterring financial statement fraud. |
7 |
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 |
This week explores Fraud Detection: Red Flags and Targeted Risk Assessment and includes insights into corporate governance and fraud, the process of fraud detection, and the significance of targeted fraud risk assessment, especially in a digital environment. |
8 |
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 |
This week explores Evidence-Based Fraud Examinations and covers the essentials of fraud examinations—addressing who, what, where, when, how, and why. It emphasizes organizing evidence, documenting work product, and explores various sources specific to the act, concealment, and conversion in fraud cases. |
WEEK 9: Class Presentation 20% |
||
9 |
LO4: Examine issues and key principles of professional digital forensic practice, including chain of custody and best practice procedures |
This week explores the Legal, Regulatory, and Professional Environment and begins with an introduction and covers the rights of individuals, probable cause, rules of evidence, the criminal justice and civil justice systems. It also addresses basic accounting principles, the regulatory system, and the role of corporate governance. |
10 |
LO4: Examine issues and key principles of professional digital forensic practice, including chain of custody and best practice procedures |
This week explores Using Information Technology for Fraud Examination and Financial Forensics and explores the digital environment, digital evidence, detection, and examination in digital spaces. It also includes a discussion on the role of graphics and graphics software, as well as the use of case management software. |
11 |
LO5: Diagnose and appraise mechanisms to uncover or recover evidence from digital devices to support litigation and investigations |
This week explores essential topics in this overview: Introduction sets the stage, emphasizing Forensic Soundness, delving into Forensic Analysis Fundamentals, unravelling Crime Reconstruction intricacies, and navigating the complexities of Networks and the Internet. |
WEEK 12: Critical Essay 40% |
||
12 |
LO5: Diagnose and appraise mechanisms to uncover or recover evidence from digital devices to support litigation and investigations |
This week explores Forensic Analysis with an overview covering the application of the scientific method to digital forensics. It also includes an exploration of uses, data gathering, hypothesis formation, evaluation, and the crucial aspects of drawing conclusions and reporting. |
13 |
Revision and Feedback |
Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.
The Library provides online and face to face support to help you find and use relevant information resources.
Macquarie University offers a range of Student Support Services including:
Got a question? Ask us via the Service Connect Portal, or contact Service Connect.
For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.
When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
Date | Description |
---|---|
15/02/2024 | Mapping of LO to assessments |
Unit information based on version 2024.04 of the Handbook