AbstractThe financial reporting world has recently faced a number of changes due to the impact of the Internet. Today, the revolution in business communication is accelerating and more data is being shared by a large number of participant users, aside from the company’s internal management, including: clients, business partners, financial market analysts, investors and government regulators. These changes have led to the development of eXtensible Business Reporting Language (XBRL), which is an open source Internet-based financial reporting language.
XBRL is an extension of eXtensible Markup Language (XML) that provides machine readable tags for each individual data element in each financial statement. XBRL is likely to be used as a platform that offers universal standards for defining business information. XBRL can ease the preparation, analysis, and exchange of business information along each part of financial reporting supply chain and across companies around the world. It can also increase the efficiency for all related users of business data.
This study has analysed the accuracy of XBRL outputs by conducting a literature review and by checking the accuracy of the real company XBRL filing submissions that are published publicly. This study has found that there were many errors in these public XBRL documents that were caused either through a few basic common errors or from mistakes in related financial information. Therefore, this study has aimed to discover any possible causes of errors in XBRL filings. It has also aimed to find a way to detect those errors. Consequently, this study conducted a semantic checking system that aimed to detect XBRL errors and so enhance the accuracy of financial statements.
To develop the semantic checking system, the results of an error finding analysis were combined, filtered, and classified into each category of errors, including the integration of accounting, business, and technology knowledge to fulfil the system. A process flow for the semantic checking system was created to help understand both the method and the rule. The rules were then set up to determine the different aspect of errors, which had a different method to manage and reduce errors. The semantic checking system was created in terms of the information specification of the XBRL filings. The system was designed to be more practical for the users by presenting the relationship between the real data and accounting practice. Moreover, a prototype was produced and the case study method was applied to prove the development of the system. This step was able to ensure the accuracy of the semantic checking system.
Finally, this semantic checking system has been shown to improve the accuracy of XBRL filings. It also emphasises the importance of employing XBRL preparers who are aware of all of the possible issues that may arise while preparing an XBRL-based filing submission.
|Date of Award||Mar 2013|
|Supervisor||Shikun Zhou (Supervisor), David Ndzi (Supervisor) & Spencer Onuh (Supervisor)|