Overview

This unit is developed with direct input from industry to ensure graduates have relevant career-ready knowledge and skills. The result is a unit that delves into the intersection of accounting principles and cutting-edge tools to uncover fraud, embezzlement, and financial misconduct. Through a lens of integrity and ethical practice, we explore how forensic accountants and fraud investigators utilize advanced software, data analytics, and investigative techniques to navigate complex financial landscapes. Where possible, the unit delivery will involve guest presenters.

Requisites

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 2
Location
Hawthorn
Start and end dates
04-August-2025
02-November-2025
Last self-enrolment date
17-August-2025
Census date
31-August-2025
Last withdraw without fail date
19-September-2025
Results released date
09-December-2025
Semester 1
Location
Hawthorn
Start and end dates
02-March-2026
31-May-2026
Last self-enrolment date
15-March-2026
Census date
31-March-2026
Last withdraw without fail date
21-April-2026
Results released date
07-July-2026
Semester 2
Location
Hawthorn
Start and end dates
03-August-2026
01-November-2026
Last self-enrolment date
16-August-2026
Census date
01-September-2026
Last withdraw without fail date
22-September-2026
Results released date
08-December-2026

Unit learning outcomes

Students who successfully complete this unit will be able to:

  1. Construct and evaluate the fundamentals relating to the nature, types and symptoms of fraud.
  2. Utilise technology-assisted techniques to detect, investigate and mitigate fraud exposures
  3. Evaluate emerging threats and trends relating to cybersecurity and ethics
  4. Work in groups to analyse and extrapolate meaning from authentic fraud case studies

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)

On-campus 

Class 1

2.00 12 weeks 24

Online 

asynchronous Lecture

1.00 12 weeks 12

Unspecified Activities 

Independent Learning

9.5 12 weeks 114
Total     150

Assessment

Type Task Weighting ULOs
Assignment 1 Group 20-30% 1,2,4
Assignment 2 Individual 20-30% 1,2,3
Assignment 3 Individual 40-60% 1,2,3

Content

  • Fraud definition, classifications and motivations.
  • Legal and regulatory framework.
  • Preventing Fraud: Internal Controls, Codes of Conduct (ACS, ACFE), Whistleblowing.
  • Detecting Fraud: Data-driven fraud detection.
  • Data mining and analysis with a fraud lens.
  • Artificial Intelligence in Fraud investigations – industry insights.
  • Regulatory technology, Generative AI for Know Your Customer (KYC).
  • Forensic Analytics and Technologies - industry insights.
  • Financial Crime - Anti-Money Laundering & Counter-Terrorism Financing.
  • Crypto crime --> Blockchain.

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.