Methodology of Digital Transformation Practices of Accounting Firm

Authors

  • Shing Han Li National Taipei University of Business, Taipei, Taiwan
  • Jenten Liu National Taipei University of Business, Taipei, Taiwan
  • Li Hua Huang National Taipei University of Business, Taipei, Taiwan
  • Chiting Huang National Taipei University of Business, Taipei, Taiwan
  • Chien Chi National Taipei University of Business, Taipei, Taiwan

DOI:

https://doi.org/10.15379/ijmst.v10i1.2632

Keywords:

Digital Transformation, Digital Auditing, Data Analysis, Machine Learning

Abstract

For accounting firms, digital auditing is an important task which helps them to examine financial data and ensure the accuracy of the data on the reports. However, which data analysis techniques should be adopted to improve the efficiency and accuracy of digital audit is an important issue. This study aims to explore the feasibility and practical applications of using data analytics techniques in digital auditing; These techniques can help auditors to systematically check, test and evaluate the accuracy, completeness, reliability and effectiveness of corporate information systems and data according to the systematic procedure. The DIKW model is a model that establishes a connection between knowledge and wisdom based on the framework of knowledge management, using the traditional concept of "data-information-knowledge-wisdom". This study will start from the theoretical level to explore the practical research of digital auditing combined with the DIKW model using data models, visualization analysis, machine learning, and related technical and practical problems. Effective solutions are proposed for each situation for future development. The implementation of this research is expected to help auditors choose appropriate data analysis techniques for digital auditing to ensure data accuracy and reliability.

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Published

2023-10-11

How to Cite

[1]
S. H. . Li, J. . Liu, L. H. . Huang, C. Huang, and C. . Chi, “Methodology of Digital Transformation Practices of Accounting Firm”, ijmst, vol. 10, no. 1, pp. 695-708, Oct. 2023.