This course explores how data can be used to solve accounting problems across financial accounting, managerial accounting, and audit contexts. Students will gain exposure to techniques to explore how financial and non-financial data is used to forecast events, detect financial discrepancies and frauds, predict corporate default, optimize operations, and determine business strategy. The emphasis of this class will be on problem solving, theory, and application, with additional emphasis on interpretation and communication. Some programming will be required, but programming help will be provided at the start of the semester via online tutorial and through instructor-provided code. Some advanced analytics methods such as text analytics, neural networks and deep learning will also be introduced. This course has been designed to equip students with an analytics mindset to develop analytics strategies and make better business decisions.
This course contributes to the development of the following learning goals and objectives of the School’s Bachelor of Accountancy program: Learning Goal 1 (Accounting Competencies):
LO1.1: Our students can recognize, develop, measure, record, validate and communicate financial and other related information.
LO1.2: Our students can analyse, synthesise and evaluate financial and other related information for decision making in a management context. Students are expected to demonstrate the following technical competencies upon successful completion of this course:
- Understand the role of data analytics in solving accounting and business problems, such as revenue prediction, bankruptcy prediction, and fraud detection.
- Demonstrate familiarity with statistical programming in the contexts of forecasting and forensics.
- Transform financial and nonfinancial data into useful insights for business.
- Communicate inferences from analysis through writing, speaking, and visuals.
- Develop an ability to independently learn and explore new methods in analytics in this everchanging field.
Class activities are designed to further develop students’ analytical, communication, and active learning skills, as well as students’ professional ethics. Students must be prepared to go beyond lecture materials and prescribed reading.
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