The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Big Data Analytics in Financial Statement Audits
Abstract
SYNOPSIS: Big Data analytics is the process of inspecting, cleaning, transforming, and modeling Big Data to discover and communicate useful information and patterns, suggest conclusions, and support decision making. Big Data has been used for advanced analytics in many domains but hardly, if at all, by auditors. This article hypothesizes that Big Data analytics can improve the efficiency and effectiveness of financial statement audits. We explain how Big Data analytics applied in other domains might be applied in auditing. We also discuss the characteristics of Big Data analytics, which set it apart from traditional auditing, and its implications for practical implementation.
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Cites
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Big data in accounting: an overview
Vasarhelyi, M. A., Kogan, A., & Tuttle, B. M. (2015) · Accounting Horizons · doi:10.2308/acch-51071 · Cited by 641
The digital transformation of external audit and its impact on corporate governance
Manita, R., Elommal, N., Baudier, P., & Hikkerova, L. (2020) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2019.119751 · Cited by 533
A survey towards an integration of big data analytics to big insights for value-creation
Saggi, M. K., & Jain, S. (2018) · Information Processing & Management · doi:10.1016/j.ipm.2018.01.010 · Cited by 494
Is artificial intelligence improving the audit process?
Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022) · Review of Accounting Studies · doi:10.1007/s11142-022-09697-x · Cited by 461
Metadata
- Authors
- Cao, M., Chychyla, R., & Stewart, T.
- Venue
- Accounting Horizons
- Publisher
- American Accounting Association
- Published
- 2015-06-01
- Volume
- 29
- Issue
- 2
- Pages
- 423-429
- ISSN
- 0888-7993 (ISSN-L)
- 1558-7975
- OpenAlex
- W2088535455
- Cited by
- 434
- References
- 1
- FWCI
- 43.74
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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