Continuous Auditing and Data Mining

Continuous Auditing and Data Mining

Edward J. Garrity (Canisius College, USA), Joseph B. O’Donnell (Canisius College, USA) and G. Lawrence Sanders (State University of New York at Buffalo, USA)
Copyright: © 2005 |Pages: 6
DOI: 10.4018/978-1-59140-557-3.ch042
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Abstract

Investor confidence in the financial markets has been rocked by recent corporate frauds and many in the investment community are searching for solutions. Meanwhile, due to changes in technology, organizations are increasingly able to produce financial reports on a real-time basis. Access to this timely information can help investors, shareholders, and other third parties, but only if this information is accurate and verifiable. Real-time financial reporting requires real-time or continuous auditing (CA) to ensure integrity of the reported information. Continuous auditing “ is a type of auditing which produces audit results simultaneously, or a short period of time after, the occurrence of relevant events” (Kogan, Sudit, & Vasarhelyi, 2003, p. 1). CA is facilitated by eXtensible Business Reporting Language (XBRL), which enables seamless transmission of company financial information to auditor data warehouses. Data mining of these warehouses provides opportunities for the auditor to determine financial trends and identify erroneous transactions.

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