Detection of price manipulation fraud through rational choice theory: evidence for the retail industry in Taiwan

All enterprises, regardless of industry, are exposed to fraud risk. In the retail perpetrators manipulate sales price products instead quantity sold avoid inventory discrepancies. Fraud examiners attempt identify anomalous transactions using data analysis. This study analyzes causes fraudulent behavior, conceptualized based on aspect rational choice, and proposes an transaction detection model variables identified as indicating fraud. A two-phase experiment analyzing a real-world set from retailer in Taiwan was designed evaluate performance variables. The findings demonstrate that these could slightly improve results analysis machine learning is applicable detection. addition, this contributes choice theory validate applicability industry reduce losses by adopting proposed approach, implemented Weka software, anomalies.