Infer, Predict, and Assure: Accounting Opportunities in Data Analytics

Gary P Schneider; Jun Dai; Diane J Janvrin; Kemi Ajayi; Robyn L Raschke

doi:10.2308/acch-51140

Back

Infer, Predict, and Assure: Accounting Opportunities in Data Analytics

Journal article

Peer reviewed

Infer, Predict, and Assure: Accounting Opportunities in Data Analytics

Gary P Schneider, Jun Dai, Diane J Janvrin, Kemi Ajayi and Robyn L Raschke

Accounting horizons, Vol.29(3), pp.719-742

09/01/2015

DOI: https://doi.org/10.2308/acch-51140

Handle:

https://hdl.handle.net/20.500.12741/rep:7365

Abstract

SYNOPSIS The business use of data analytics is growing rapidly in the accounting environment. Similar to many new systems that involve accounting information, data analytics has fundamentally changed task processes, particularly those tasks that provide inference, prediction, and assurance to decision-makers. Thus, accounting researchers and practitioners must consider data analytics and its impact on accounting practice in their work. This paper uses the organizing principles from Mauldin and Ruchala's (1999) meta-theory of accounting information systems (AIS) to identify current data analytics use, examine how data analytics impacts the accounting environment, and discuss challenges and research opportunities.

Metrics

82 Record Views

Details

Title: Infer, Predict, and Assure: Accounting Opportunities in Data Analytics
Creators: Gary P Schneider - Gary P. Schneider is a Professor at Quinnipiac University; Jun Dai is an Assistant Professor at Southwestern University of Finance and Economics and a Ph.D. student at Rutgers, The State University of New Jersey, Newark; Diane J. Janvrin is an Associate Professor at Iowa State University; Kemi Ajayi is an Assistant Professor at the University of Colorado Denver; and Robyn L. Raschke is an Associa
Jun Dai - Gary P. Schneider is a Professor at Quinnipiac University; Jun Dai is an Assistant Professor at Southwestern University of Finance and Economics and a Ph.D. student at Rutgers, The State University of New Jersey, Newark; Diane J. Janvrin is an Associate Professor at Iowa State University; Kemi Ajayi is an Assistant Professor at the University of Colorado Denver; and Robyn L. Raschke is an Associa
Diane J Janvrin - Gary P. Schneider is a Professor at Quinnipiac University; Jun Dai is an Assistant Professor at Southwestern University of Finance and Economics and a Ph.D. student at Rutgers, The State University of New Jersey, Newark; Diane J. Janvrin is an Associate Professor at Iowa State University; Kemi Ajayi is an Assistant Professor at the University of Colorado Denver; and Robyn L. Raschke is an Associa
Kemi Ajayi - Gary P. Schneider is a Professor at Quinnipiac University; Jun Dai is an Assistant Professor at Southwestern University of Finance and Economics and a Ph.D. student at Rutgers, The State University of New Jersey, Newark; Diane J. Janvrin is an Associate Professor at Iowa State University; Kemi Ajayi is an Assistant Professor at the University of Colorado Denver; and Robyn L. Raschke is an Associa
Robyn L Raschke - Gary P. Schneider is a Professor at Quinnipiac University; Jun Dai is an Assistant Professor at Southwestern University of Finance and Economics and a Ph.D. student at Rutgers, The State University of New Jersey, Newark; Diane J. Janvrin is an Associate Professor at Iowa State University; Kemi Ajayi is an Assistant Professor at the University of Colorado Denver; and Robyn L. Raschke is an Associa
Academic Unit: Computer Science Department
Publication Details: 09/01/2015
Identifiers: 99257880109401671; https://hdl.handle.net/20.500.12741/rep:7365; https://doi.org/10.2308/acch-51140
Language: English

Infer, Predict, and Assure: Accounting Opportunities in Data Analytics

Abstract

Related links

Metrics

Details