Applied AI for Accounting and Finance
Overview
This unit introduces students to the practical applications of AI and machine learning in finance and accounting. Students will gain hands-on experience with supervised and unsupervised learning, text analysis, and large language model prompt engineering. The unit is accessible to students without prior programming experience. Students will explore fundamental use cases, utilise Large Language Models to assist in coding, implement domain-specific applications, and engage with the latest research. By the end of the unit, students will have developed a practical understanding of how AI and machine learning can be leveraged to solve real-world problems in finance and accounting.
Requisites
02-November-2025
Learning outcomes
Students who successfully complete this unit will be able to:
- Apply important machine learning and generative artificial intelligence methods and interpret outputs
- Critically analyse and apply model specification, model evaluation and diagnostic testing procedures in machine learning and artificial intelligence models for finance and accounting applications
- Analyse and create solutions to financial problems using machine learning software, large language models, and business data
- Critique specific limitations of AI models in finance and accounting and propose solutions for responsible use
- Work in groups to solve machine learning and artificial intelligence problems and clearly communicate results and interpretations
Teaching methods
All applicable locations
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
On Campus Class 1 |
2 | 12 weeks | 24 |
Online Lecture (asynchronous) |
1 | 12 weeks | 12 |
Unspecified Activities Independent Learning |
9.5 | 12 weeks | 114 |
| Total | 150 |
Assessment
| Type | Task | Weighting | ULOs |
|---|---|---|---|
| Assignment | Individual | 20-30% | 1,2,3,4 |
| Assessment | Individual | 40-60% | 1,2,3,4 |
| Presentation | Group | 20-30% | 1,2,3,45 |
Content
- Generative AI Prompt Engineering for Finance and Accounting
- Introduction to Modelling and Data Wrangling
- Cross Validation and Model Evaluation Techniques for Finance and Accounting
- Linear Models for Financial Prediction
- Classification for Business Problems
- LLM Bias and Hallucination Mitigation
- Text Analysis for financial documents and news
- Latest developments and future opportunities
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.