Improving Audit Quality with Data Analytic Visualizations: The Importance of Spatial Abilities and Feedback in Anomaly Identification

Abstract

Public accounting firms and internal audit departments are implementing data analytics to enhance effectiveness and efficiency; however, there is a shortage of professionals with data analysis skills and the ability to derive meaningful insights. We conducted a quasiexperiment to examine whether and how individuals’ spatial abilities and types of feedback are related to anomaly identification performance. We predict and find that those with higher spatial abilities choose better visualizations and, in turn, are more accurate at anomaly identification. Auditors with lower spatial abilities can choose better visualizations and more accurately identify anomalies when they are provided task property feedback (i.e., feedback about the process) rather than outcome feedback or no feedback. Finally, a combination of high spatial abilities and task property feedback significantly reduces the number of false positive anomalies identified for all auditors. Our findings suggest practitioners should consider measuring spatial abilities during recruitment and when assigning visualization tasks.