Are Auditors' Reliance on Conclusions from Data Analytics Impacted by Different Data Analytic Inputs?

ABSTRACT Global stakeholders have expressed interest in increasing the use of data analytics throughout audit process. While offer great promise identifying audit-relevant information, auditors may not uniformly incorporate this information into their decision making. This study examines whether conclusions from two analytic inputs, type analytical model (anomaly versus predictive) and analyzed (financial nonfinancial), result different auditors' decisions. Findings suggest that models jointly impact budgeted hours. Specifically, when financial are analyzed, increase hours more predictive used than anomaly used. The opposite occurs nonfinancial analyzed; compared to models. These findings provide initial evidence with inputs do judgments. Data Availability: available upon request. JEL Classifications: M41; M42; C53; C55.