Big Data in Accounting: An Overview

Author:

Vasarhelyi Miklos A.1,Kogan Alexander1,Tuttle Brad M.1

Affiliation:

1. Miklos A. Vasarhelyi and Alexander Kogan are both Professors at Rutgers, The State University of New Jersey, Newark, and Brad M. Tuttle is a Professor at the University of South Carolina.

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.

Publisher

American Accounting Association

Subject

Accounting

Reference31 articles.

1. The drivers of the adoption and facilitators of the evolution of Big Data by the audit profession;Alles;Accounting Horizons,2015

2. Computational complexity and information asymmetry in financial products;Arora;Communications of the ACM,2011

3. An empirical evaluation of accounting income numbers;Ball;Journal of Accounting Research,1968

4. Behavioral implications of Big Data's impact on audit judgment and decision making and future research directions;Brown-Liburd;Accounting Horizons,2015

5. Brynjolfsson, E., and A. McAfee. 2014. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. New York, NY: W. W. Norton & Company.

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