Expert systems for decision support in EDP auditing

The complexities of computer auditing have created a need for decision support for the EDP auditor. Traditional statistical techniques have proven valuable; however, there are important qualitative components which must be incorporated in the analysis. More importantly, there is a need for decision aids which not only produce analysis and probability estimates-but are able to explain their analysis and conclusions. Recent developments in artificial intelligence have made possible the development of expert systems which provide these capabilities. In this paper we present the motivation, framework, and development strategy for a decision support system for EDP auditing.This project was funded by a grant from the Peat, Marwick, Mitchell Foundation through its Research Opportunities in Auditing program. The views expressed herein are those of the authors and do not necessarily reflect the view of the Peat, Marwick, Mitchell Foundation. The authors are indebted to the participants of the workshops at the University of Florida and the University of Wisconsin for their helpful comments. In particular, we would like to thank Rowland Ataise, Alan Friedberg, Steve Johnson, Andy Luzi, Stan Biggs, Lynn McKell, and Marshall Romney.