Students

ACCG2067 – Foundations of Forensic and Data Analytics

2025 – Session 1, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff
Kathleen Clough
kathleen.clough@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
40cp at 1000 level or above
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit introduces students to the practice and procedures of forensic accounting and the important role played by the forensic accountant in the legal and business environment. Students will be exposed to the theory and principles of application, of data analytics skills and techniques in relation to fraud detection, fraud and risk exposures, dispute resolution, cyber and financial crimes and legal obligations and processes. The unit aims to develop in students an appreciation of how the application of forensic and data analytics skills and strategies are essential to the role of the forensic accountant as an expert witness and professional advisor.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Understand the role of forensic accounting within the legal system, including the legal, ethical, and professional obligations of forensic accountants.
  • ULO2: Describe risk assessment methods and identify fraudulent schemes commonly observed in organisations.
  • ULO3: Identify and evaluate sources of evidence necessary for investigating fraudulent schemes.
  • ULO4: Comprehend the theoretical foundations and principles of applying data analytics techniques to forensic accounting.
  • ULO5: Apply technological tools to effectively extract and analyse financial data in support of investigative processes.

Assessment Tasks

Name Weighting Hurdle Due
Professional practice: Fraud detection 30% No Week 7
Formal and observed learning: Test 40% No Week 9
Skills development: Forensic and data analytics 30% No Weekly

Professional practice: Fraud detection

Assessment Type 1: Case study/analysis
Indicative Time on Task 2: 25 hours
Due: Week 7
Weighting: 30%

 

The purpose of this assessment is for you to develop critical professional expertise in fraud detection.   You will collaboratively apply theoretical concepts and frameworks to analyse real-world fraudulent schemes.   Skills in focus: - Analytical skills - Problem solving - Digital skills   Deliverable: Written submission Group assessment

 
On successful completion you will be able to:
  • Understand the role of forensic accounting within the legal system, including the legal, ethical, and professional obligations of forensic accountants.
  • Describe risk assessment methods and identify fraudulent schemes commonly observed in organisations.
  • Identify and evaluate sources of evidence necessary for investigating fraudulent schemes.
  • Comprehend the theoretical foundations and principles of applying data analytics techniques to forensic accounting.

Formal and observed learning: Test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 30 hours
Due: Week 9
Weighting: 40%

 

The purpose of this assessment is for you to demonstrate your understanding and knowledge of key topics from the unit.   You will participate in a formal test.   Skills in focus: - Discipline Knowledge - Problem Solving - Critical Thinking   Deliverable: Test Individual assessment

 
On successful completion you will be able to:
  • Understand the role of forensic accounting within the legal system, including the legal, ethical, and professional obligations of forensic accountants.
  • Describe risk assessment methods and identify fraudulent schemes commonly observed in organisations.
  • Identify and evaluate sources of evidence necessary for investigating fraudulent schemes.
  • Comprehend the theoretical foundations and principles of applying data analytics techniques to forensic accounting.
  • Apply technological tools to effectively extract and analyse financial data in support of investigative processes.

Skills development: Forensic and data analytics

Assessment Type 1: Reflective Writing
Indicative Time on Task 2: 20 hours
Due: Weekly
Weighting: 30%

 

The purpose of this assessment is for you to develop your skills in forensic and data analytics and fraud detection.   You will examine and analyse real case scenarios. You will reflect on your understanding of the topics covered to highlight the insights you have gained from the cases for your future professional practice.   Skills in focus: - Problem Solving - Critical thinking - Communication skills   Deliverable: Written submission Individual assessment

 
On successful completion you will be able to:
  • Understand the role of forensic accounting within the legal system, including the legal, ethical, and professional obligations of forensic accountants.
  • Describe risk assessment methods and identify fraudulent schemes commonly observed in organisations.
  • Identify and evaluate sources of evidence necessary for investigating fraudulent schemes.
  • Comprehend the theoretical foundations and principles of applying data analytics techniques to forensic accounting.
  • Apply technological tools to effectively extract and analyse financial data in support of investigative processes.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

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 and Resources

Textbook: Kranacher, Riley: Forensic Accounting and Fraud Examination, 3rd Edition

Policies and Procedures

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.

Student Code of Conduct

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

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

Academic Integrity

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.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

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. 

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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.

Unit information based on version 2025.04 of the Handbook