Robotic Process Automation for the Extraction of Audit Information: A Use Case

Abstract

SUMMARY The reconciliation of audit evidence to the audit subject matter is a key and recurring audit procedure. Before reconciling information, data needs to be extracted from the audit subject matter, which is often in a Portable Document Format (PDF). Reconciliations are a recurring task for every new version of the audit subject matter. Large audit firms typically “offshore” simple and repetitive audit tasks such as reconciliations to shared service centers. Offshoring however comes at the expense of coordination costs, delays in the process, and challenges regarding the liability risk to the auditor. This paper presents an open-source algorithm to extract data from (draft) annual reports (PDF files) using Python to automate, rather than outsource, the data extraction for reconciliations. The algorithm resulted in a significant time saving for the audit of a large Dutch asset management firm. Researchers apply the algorithm to minimize hand-collection of financial statement data. Data Availability: The algorithm this paper presents is open-source and publicly available. JEL Classifications: M42; G23; G29.