Taxonomy of Fraud Detection Metrics for Business Processes

Abstract

A business process is a set of connected events, activities, and decision points, including actors and objects, which collectively produce a beneficial outcome for the customer. The success of an organization's strategic goals and performance depends on how well these business processes are implemented and executed. However, process-based fraud (PBF), a type of fraud that occurs in business processes, can be an obstacle to achieving this. Literature analysis shows that to date PBF detection metrics have not been sufficiently addressed. Specifically, there is overlap, confusion, and no standard for fraud definitions and categories that can affect our understanding of fraud mechanisms. This study develops a taxonomy to expose the dimensions, characteristics, and objects of PBF detection and to determine their relationships by using the design science research methodology. The developed taxonomy identifies four PBF dimensions with the following characteristics: (1) process perspective {time, function, data, resource, and location}, (2) presentation layer {process map, process stream, process model, process instance, and process activity}, (3) fraud data scheme {anomalous, discrepant, missing, and wrong}, and (4) fraud domain {generic and specific}. The objective of this taxonomy is to offer a useful tool to anyone seeking to classify, develop, and evaluate PBF detection metrics, along with a holistic view of PBF detection and the determination of its borders. Additionally, it may help in standardizing the concepts of PBF detection metrics to ensure consistency between stakeholders.

Keywords

• Business process fraud
• fraud categories
• fraud classification
• fraud detection
• fraud indicators
• fraud metrics