Brief Course Description
1. Course Title:
Predictive Analytics and Modeling in Accounting
2. Language of Instruction:
Vietnamese
3. Course Code:
ACC507290
4. Credits:
3
5. Course Objectives:
The course Predictive Analytics and Modeling in Accounting provides students with foundational knowledge and skills in predictive analytics, quantitative modeling, and decision support within management accounting. Through the course, students are able to collect, process, and analyze financial and non-financial data, and to develop and apply predictive and analytical models to support managers in planning, scenario evaluation, control, and business decision-making under conditions of uncertainty.
In addition, the course contributes to the development of students’ analytical and critical thinking, enhances their ability to interpret and communicate analytical results to management, and fosters professional ethics, professional scepticism, and awareness of sustainable management in the context of modern business environments.
6. Brief Description of Course Content:
The course “Predictive Analytics and Modeling in Accounting” equips students with essential knowledge and skills in predictive analytics, quantitative modeling, and decision support within management accounting and business analysis. The course focuses on the use of financial and non-financial data to develop predictive and analytical models, supporting managers in planning, evaluating future scenarios, and making informed business decisions under conditions of uncertainty.
Key topics include: an overview of predictive analytics and modeling in accounting, data foundations for predictive analysis, trend and baseline analysis, modeling cost–activity–outcome relationships, commonly used predictive and forecasting techniques (including time-series and regression models), scenario and sensitivity analysis, and the application of predictive analytics in performance measurement and ESG-related information. The course also emphasizes the role of accountants in implementing predictive analytics projects, communicating analytical insights to management, and addressing the limitations, risks, and ethical considerations associated with predictive analytics and modeling.