Abstract
Occupational fraud is defined as the deliberate misuse of one's occupation for personal enrichment. It poses a significant challenge for organizations and governments. Estimates indicate that the funds involved in occupational fraud cases investigated across 125 countries between 2018 and 2019 exceeded US$3.6 billion. Process-based fraud (PBF) is a form of occupational fraud that is perpetrated inside business processes. Business processes underlie the logic of the work that organizations undertake, and they are used to execute an organization's strategies to achieve organizational goals. Business processes should be examined for potential fraud risks to ensure that businesses achieve their objectives. While it is impossible to prevent fraud entirely, it must be detected. However, PBF detection metrics are not well developed at present. They are scattered, unstandardized, not validated, and, in some cases, absent. This study aimed to develop a comprehensive PBF detection metric by leveraging and operationalizing a taxonomy of fraud detection metrics for business processes as an underlying theory. 41 PBF detection metrics were deduced from the taxonomy using design science research. To evaluate their utility, the application of the metrics was undertaken using illustrative scenarios, and a real example of the implementation of the metrics was provided. The developed metrics form a complete, classified, validated, and standardized list of PBF detection metrics, which include all the necessary PBF detection dimensions. It is expected that the stakeholders involved in PBF detection will use the metrics established in this work in their practice to increase the effectiveness of the PBF detection process.