Determining the accuracy of budgets : a machine learning application for budget change pattern recognition

Yip, Kai Leung

Thumbnail
Share
View fulltext online
Date
2012
Permanent link to Research Bank record:
https://hdl.handle.net/10652/2036
Abstract
With the aid of open-sourced database and software libraries, we developed a data mining software prototype for SME business intelligent budgeting planning. The experiment demonstrates the existence of the change pattern of financial variables for a certain SME industry group. A budget inaccuracy alarm system is developed. The system classifies a budget whether viable or inviable. As a result, SME businesses or non-profit organisations can make better decisions by improving forward looking financial analysis. This allows them to immediately develop contingency measures, revise the policy and get the business back on the right track. This has been a long-desired function needed by a business or a bank.
Keywords:
budget change pattern tecognition, budgeting, business planning, data mining, financial forecast, financial ratio, financial variable, government budget, intelligent budgeting, machine learning, small and medium-sized enterprises (SMEs), small businesses
ANZSRC Field of Research:
080109 Pattern Recognition and Data Mining
Degree:
Master of Computing
Supervisors:
Pang, Paul; Zhao, Xiaohui
Rights:
This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
Metadata
Show detailed record
This item appears in