Fraud detection is made difficult in part due to the fact that most auditors have relatively little experience with it. We address the issue of what kind of knowledge supports success in financial statement fraud detection by examining the more general information processing problem of detecting a deception. We define deception as a process in which a deceiver (e.g. management) has intentionally manipulated an environment (a financial statement) so as to elicit a misleading representation in a target agent (e.g. an auditor). We develop a theory of the knowledge that the deceiver and the target use for respectively constructing and detecting deceptions. Drawing on the literature in several fields (e.g. cognitive ethology, military strategy, child development) we identify specific strategies and tactics for creating a deception. We then hypothesize that reasoning about a deceiver's goals is one of the main strategies for detecting deception. We use the strategies and tactics for creating a deception to propose what the knowledge that would lead to the detection of financial statement fraud must be like based on a proposed hierarchy of the manager's (deceiver's) goals. We compare the proposed detection knowledge with the knowledge base of a computer (expert system) model of financial statement fraud detection task that was successful in solving several real fraud cases (and was built independently from the proposed theory). We also compare properties of the detection knowledge proposed in our theory with the knowledge employed by several experienced auditors who performed the task of concurring partner review on one of the fraud cases successfully analyzed by the model.
Bibliographical noteFunding Information:
A consistent finding in cognitive studies of expertise is that those who are expert in a task tend to base their performance on the use of patterns of information developed through experience. These patterns trigger solution methods that have been successful with similar problems in the past (e.g. Glaser & Chi, 1988; Larkin et al., 1980). Fraud detection, however, occurs relatively infrequently in the life of an * This work was supported in part by a grant from the Peat Marwick Foundation. We are grateful for the time of the auditors who contributed the data reported here, as well as the collaboration of R. Glen Berryman.
Copyright 2019 Elsevier B.V., All rights reserved.