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A Comprehensive Study on Implementing Big Data in the Auditing Industry

A Comprehensive Study on Implementing Big Data in the Auditing Industry In this study, the implementation of big data techniques in auditing processes is investigated, and it is determined that the practise is not as widespread as it is in other comparable industries. Firstly, we introduce bid data and its technological evolution to promote better understanding of its potential usage. Following that, the research discusses the importance of implementing big data techniques in auditing and also enumerates the existing big data tools that the corporates currently use. Next, we focus on the impact of implementing Big Data Analytics (BDA) in Auditing and the common problems of integrating BDA in the audit context. In addition, we go through existing research on big data approaches and analyse how big data is being used in auditing procedures. Further, the research focuses on the perspectives of the Big Four Auditing firms on the implementation of Big Data technologies in today's auditing environment and its future possibilities. Moreover, this study also looks at the growth of the bid data and auditing industries globally from a quantitative standpoint. Regression analysis is used in conjunction with a moving average estimate for both the industries for the year 2021. This was done in order to quantify the auditing industry's reliance on bid data technology for efficiency. After thorough research a conclusion was made that; in terms of the usage of valuable big data approaches, auditing lags behind the other industries. Possible explanation for a lower acceptance to big data technologies lies in the challenges of implementing bid data. A positive outlook towards bid data technologies can be expected after overcoming the challenges associated with its implementation. Hence, we recommend that further research in this area is necessary. The empirical findings of the study can be used to understand the challenges of implementing big data technologies and can be set as a research agenda for future research on the subject. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Data Science Springer Journals

A Comprehensive Study on Implementing Big Data in the Auditing Industry

Patel, Salonee; Shah, Manan
Annals of Data Science , Volume 10 (3) – Jun 1, 2023
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References (65)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022
ISSN
2198-5804
eISSN
2198-5812
DOI
10.1007/s40745-022-00430-8
Publisher site
See Article on Publisher Site

Abstract

In this study, the implementation of big data techniques in auditing processes is investigated, and it is determined that the practise is not as widespread as it is in other comparable industries. Firstly, we introduce bid data and its technological evolution to promote better understanding of its potential usage. Following that, the research discusses the importance of implementing big data techniques in auditing and also enumerates the existing big data tools that the corporates currently use. Next, we focus on the impact of implementing Big Data Analytics (BDA) in Auditing and the common problems of integrating BDA in the audit context. In addition, we go through existing research on big data approaches and analyse how big data is being used in auditing procedures. Further, the research focuses on the perspectives of the Big Four Auditing firms on the implementation of Big Data technologies in today's auditing environment and its future possibilities. Moreover, this study also looks at the growth of the bid data and auditing industries globally from a quantitative standpoint. Regression analysis is used in conjunction with a moving average estimate for both the industries for the year 2021. This was done in order to quantify the auditing industry's reliance on bid data technology for efficiency. After thorough research a conclusion was made that; in terms of the usage of valuable big data approaches, auditing lags behind the other industries. Possible explanation for a lower acceptance to big data technologies lies in the challenges of implementing bid data. A positive outlook towards bid data technologies can be expected after overcoming the challenges associated with its implementation. Hence, we recommend that further research in this area is necessary. The empirical findings of the study can be used to understand the challenges of implementing big data technologies and can be set as a research agenda for future research on the subject.

Journal

Annals of Data Science – Springer Journals

Published: Jun 1, 2023

Keywords: Big data; Auditing; Prediction

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