A Generalizable Knowledge-Based Framework for Audit Planning Expert Systems.

Abstract Many auditing expert systems have been developed for individual components of the audit planning process such as inherent risk assessment and internal control evaluation, The audit planning process involves integrating judgments from each step in the process into subsequent steps. Based on a task analysis of the audit planning process, this paper presents a generalizable knowledge-based framework for the development of expert systems encompassing the entire audit planning process from assessment of overall audit risk to selection of appropriate audit procedures. The framework, which incorporates the audit risk model, suggests the use of knowledge-bases for the heuristic reasoning components of audit planning expertise and a database for the factual knowledge components. Knowledge of how to select appropriate audit procedures given a particular audit situation is best represented using a pattern matching algorithm. The paper also describes an attribute-based design approach which facilitates flexibility in the resulting expert system.