A Comparative Evaluation of Belief Revision Models in Auditing

Abstract

External auditors typically gather audit evidence in a sequential fashion and revise their estimates of likelihood of material misstatements based on the evidence collected. Optimal utilization of audit evidence can help control audit risk and improve audit efficiency and effectiveness. This paper first shows how a typical audit risk assessment and belief revision task can be modeled using four theoretical models of belief revision. Then the descriptive properties of these models are evaluated based on the actual judgments of experienced auditors who assessed the likelihood of error in a task involving inventory valuation. A realistic audit case was administered to 101 experienced auditors. Models based on the following theories were evaluated: a version of Bayesian inference labeled Cascaded Inference Theory (Schum 1987; Schum and DuCharme 1971), two versions of the Belief Adjustment Model (Hogarth and Einhorn 1992), and a version of the Dempster‐Shafer Theory of Belief Functions (Srivastava and Shafer 1...