With the development of information technology and rapidly changing market conditions, corporate IT systems are not simply a means of assisting work, but rather a core element of management strategy. In particular, the importance of corporate accounti...
With the development of information technology and rapidly changing market conditions, corporate IT systems are not simply a means of assisting work, but rather a core element of management strategy. In particular, the importance of corporate accounting information management is increasing amidst the increasing number of advanced cyber security threats and accounting fraud cases. Research is actively being conducted to utilize accounting information as basic data for information technology. When a company introduces an IT system, it should consider not only cost issues but also the characteristics of the company. In addition, complex systems can actually cause inefficiency.
In this paper, we propose a method for a user-centered accounting management system that can incorporate correlations into accounting information and reflect the characteristics of the company. We developed a system that can predict future budgets by analyzing past and current budget data through a correlation application module using the Kendall-Tau correlation coefficient. In addition, we proposed a solution to the burden of corporate accounting work by enabling user-centered budget setting through an item movement module. In order to respond to the characteristics of the company and the changing environment, we applied a weight adjustment module, which increased the accuracy of data and provided flexibility in the practical environment.
If the developed system is applied to an actual company to verify its practical efficiency, it can be used to improve the company's accounting management method. This paper aims to enhance the flexibility and applicability of the system to perform user-centered accounting management tasks. It is also expected to help companies make strategic decisions by predicting future budgets by increasing the accuracy of past budget data and current budget data analysis using correlations.