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

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

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

College of Business

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	American English
Journal	Accounting Horizons
Volume	29
DOIs	https://doi.org/10.2308/ACCH-51140
State	Published - 2015

Keywords

AIS meta-theory
data analytics
task processes

Disciplines

Accounting
Technology and Innovation
Business Analytics
Systems Science
Computer Sciences

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Cite this

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title = "Infer, Predict, and Assure: Accounting Opportunities in Data Analytics",

abstract = " 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{\textquoteright}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.",

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AU - Raschke, Robyn L.

N1 - Important User Information: Remote access to EBSCO's databases is permitted to patrons of subscribing institutions accessing from remote locations for personal, non-commercial use. However, remote access to EBSCO's databases from non-subscribing institutions is not allowed if the purpose of the use is for commercial gain through cost reduction or avoidance for a non-subscribing institution.

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N2 - 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.

AB - 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.

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VL - 29

JO - Accounting Horizons

JF - Accounting Horizons

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

Abstract

Keywords

Disciplines

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