Fraud detection for financial statements of business groups

Yuh Jen Chen, Wan Ching Liou, Yuh Min Chen, Jyun Han Wu

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


Investors rely on companies' financial statements and economic data to inform their investment decisions. However, many businesses manipulate financial statements to raise more capital from investors and financial institutions, which reduces the practicality of financial statements. The modern business environment is highly information-oriented, and firms' information systems and activities are complex and dynamic. Technology for avoiding fraud detection is continually updated. Recent studies have focused on detecting financial statement fraud within a single business, but not within a business group. Development of methods for using diverse data to detect financial statement fraud in business groups is thus a high priority in the advancement of fraud detection. This study develops an approach for detecting fraud in the financial statements of business groups. The proposed approach is applied to reduce investment losses and risks and enhance investment benefits for investors and creditors. The study objectives are achieved through the following steps: (i) design of a process for detecting fraud in the financial statements of business groups, (ii) development of fraud detection techniques for use with such statements, and (iii) demonstration and evaluation of the proposed approach.

Original languageEnglish
Pages (from-to)1-23
Number of pages23
JournalInternational Journal of Accounting Information Systems
Publication statusPublished - 2019 Mar

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Accounting
  • Finance
  • Information Systems and Management


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