University of Technology Sydney

25883 AI-driven Compliance, Anomaly and Fraud Detection

Requisite(s): 24 credit points of completed study in spk(s): C04048 Master of Finance OR 24 credit points of completed study in spk(s): C04258 Master of Finance (Extension) OR 24 credit points of completed study in spk(s): C07021 Graduate Diploma Finance OR 24 credit points of completed study in 24Credit Points spk(s): MAJ08984 c 36cp Finance Major MBA
The lower case 'c' after the subject code indicates that the subject is a corequisite. See definitions for details.
These requisites may not apply to students in certain courses. See access conditions.



In the fast-paced and complex world of finance, ensuring compliance and preventing fraud are paramount. This subject delves into the pivotal role of artificial intelligence (AI) in mitigating these risks and safeguarding the integrity of financial systems. This subject introduces finance students to a captivating realm where AI technologies hold the key to uncovering hidden patterns, detecting irregularities, and fortifying compliance measures. By blending theory and practice, students gain a conceptual understanding of cutting-edge techniques, methodologies, and ethical considerations involved in leveraging AI for these critical tasks. Real-life scenarios presented in class help illustrate the urgent need for advanced technologies in the finance industry.

Students are immersed in the world of data integration, pre-processing, feature engineering, ensemble methods, and text mining techniques. They discover how AI can consolidate diverse datasets, standardise formats, and transform raw information into valuable insights. To help navigate the delicate balance between technological advancements and responsible AI usage, the subject delves into the ethical dimensions with the examination of the risks of algorithmic bias, data privacy concerns, and the need for transparency and accountability in implementing AI solutions. Armed with a comprehensive understanding of AI-driven compliance, anomaly detection, and fraud prevention, students emerge prepared to tackle the challenges faced by the finance industry and will possess the knowledge and skills to leverage AI technologies to detect financial irregularities, make data-driven decisions, and safeguard the trust and confidence of investors and clients.

Detailed subject description.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.