A conceptual framework for of artificial neural networks for accounting

Abstract

It is clear that accountants have historically been at the forefront of introducing new technologies to achieve high-speed data analysis, improving accuracy and saving costs and time in accounting operations. Accounting, has distinctive characteristics and requirements, including compliance with regulatory requirements. Accounting is a process that involves managing large amounts of data and performing repetitive tasks that consume a significant portion of companies' financial and human resources. Consequently, enterprises are constantly striving to use technological advances to improve the efficiency and effectiveness of their business processes. In recent years, there has been a marked increase in interest shown by accounting professionals and large accounting firms in the use of new technologies, especially those related to artificial neural networks for accounting purposes. The present study aims to investigate the factors influencing the application of artificial neural networks for accounting and the possibilities and challenges that artificial neural networks for accounting present for its potential use in accounting and reporting in part or in full in the near future. The present paper also provides a conceptual framework to address these issues and facilitate future research in this area. Numerous case studies, analogy and grouping methods, analysis, synthesis, comparison, systems and logic approaches were used as methodology.