Big Data in Accounting: An Overview

TLDR

This paper outlines a comprehensive framework for Big Data in accounting, tracing its evolution from structured ERP data to unstructured environmental sources, highlighting the need for updated standards, new audit analytics opportunities, and the benefits for academics, practitioners, and students. The essays examine Big Data sources, uses, and challenges in accounting and auditing, its interaction with traditional data, and its influence on audit judgment and behavioral research.

Abstract

SYNOPSIS This paper discusses an overall framework of Big Data in accounting, setting the stage for the ensuing collection of essays that presents the ongoing evolution of corporate data into Big Data, ranging from the structured data contained in modern ERPs to loosely connected unstructured and semi-structured information from the environment. These essays focus on the sources, uses, and challenges of Big Data in accounting (measurement) and auditing (assurance). They consider the changing nature of accounting records and the incorporation of nontraditional sources of data into the accounting and auditing domains, as well as the need for changes in the accounting and auditing standards, and the new opportunities for audit analytics enabled by Big Data. Additionally, the papers discuss the interaction of Big Data and traditional sources of data, as well as Big Data's impact on audit judgment and behavioral research. Both accounting academics and accounting practitioners will benefit from learning about the significant potential benefits of Big Data and the inevitable challenges and obstacles in the way of its utilization. Advanced accounting students would also benefit from exposure to these emerging issues to enhance their future career development.