This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Krishnan, R. Articles by Kaplan, D. Search for Related Content

On Data Reliability Assessment in Accounting Information Systems

The Heinz School, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213-3890
The R. H. Smith School of Business, University of Maryland, College Park, Maryland 20742-7215
The Heinz School, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213-3890
The Heinz School, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213-3890
rk2x{at}cmu.edu
jmpeters{at}umd.edu
rpadman{at}cmu.edu
djk{at}andrew.cmu.edu

The need to ensure reliability of data in information systems has long been recognized. However, recent accounting scandals and the subsequent requirements enacted in the Sarbanes-Oxley Act have made data reliability assessment of critical importance to organizations, particularly for accounting data. Using the accounting functions of management information systems as a context, this paper develops an interdisciplinary approach to data reliability assessment. Our work builds on the literature in accounting and auditing, where reliability assessment has been a topic of study for a number of years. While formal probabilistic approaches have been developed in this literature, they are rarely used in practice. The research reported in this paper attempts to strike a balance between the informal, heuristic-based approaches used by auditors and formal, probabilistic reliability assessment methods. We develop a formal, process-oriented ontology of an accounting information system that defines its components and semantic constraints. We use the ontology to specify data reliability assessment requirements and develop mathematical-model-based decision support methods to implement these requirements. We provide preliminary empirical evidence that the use of our approach improves the efficiency and effectiveness of reliability assessments. Finally, given the recent trend toward specifying information systems using executable business process models (e.g., business process execution language), we discuss opportunities for integrating our process-oriented data reliability assessment approach—developed in the accounting context—in other IS application contexts.

Key Words: workflow and process management; accounting information systems; mathematical modeling; internal control
History: This paper was received on June 4, 2003.

This article has been cited by other articles:

				Z. Jiang, S. Sarkar, P. De, and D. Dey A Framework for Reconciling Attribute Values from Multiple Data Sources Management Science, December 1, 2007; 53(12): 1946 - 1963. [Abstract] [PDF]