How Big Data will Change Financial Accounting?

Document Type : Review Paper

Authors

1 Professor of Accounting Department, Faculty of Management and Accounting, Allameh Tabatabaei University,

2 Ph.D. Student of Accounting, Faculty of Management and Accounting, Allameh Tabatabaei University

Abstract

Big Data consists of voluminous data sets that they cannot be reasonably analyzed by using Database management systems or traditional software programs. The reason for this popularity is growing amount of information that are available by developments in computing and telecommunications technology, particularly the Internet and environmental sensing. as different types of data become available, Big Data will have significant implication for financial accounting. The textual, video, audio and image information are available via Big Data, could improve financial accounting and financial reporting procedure. Big Data in financial accounting will enhance the quality and relevance of accounting information, cause to increase transparency which results in improvement of stakeholder decision making. In financial reporting, Big Data could be helpful in creation and refinement of accounting standards, furthermore Big Data assure that with the evolution of dynamic, global and real economy; accounting profession will continue to provide useful information

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References

Arora, S. , Boaz, B. , Markus,B. & Rong. Ge (2010). "Computational complexity and information asymmetry in financial products. " In ICS, pp. 49-65.
Association of Certified Fraud Examiners. (2013). "Fraud loss for 2012". http: //www.fraud-magazine.com/upload­files/Fraud_Magazine/Content/ Marketplace/ media-planner. pdf.
Assunção, M. D. Calheiros, R. N. Bianchi, S. Netto, M. A. & Buyya, R. (2015). “Big Data computing and clouds: Trends and future directions". Journal of Parallel and Distributed Computing, 79, 3-15.
Brynjolfsson, E. Hammerbacher, J. & Stevens, B. (2011). "Competing through data: Three experts offer their game plans". McKinsey Quarterly. 4: 36-47.
Bughin, J. Livingston, J & Marwaha, S. (2011). "Seizing the potential of ‘big data". McKinsey Quarterly. 4: 103-109.
Girshick, R. Donahue, J. Darrell, T. & Malik, J. (2014). "Rich feature hierarchies for accurate object detection and semantic segmentation: In Computer Vision and Pattern Recognition (CVPR) ". IEEE Conference on (580-587).
Hobson, J. L, Mayew, W. J. & Venkatachalam, M. (2012). "Analyzing speech to detect financial misreporting". Journal of Accounting Research. 50 (2): 349-392.
http: //www. seo. ir/LoadFile. ashx?Id=1IWJRbDtxDsPAgIAvh3xdQ== .
Kieso, D. J,Weygandt. & T, Warfield. (2013). "Intermediate Accounting”. Hoboken, NJ: John Wiley & Sons, Inc.
Krahel, J. P. , & Titera, W. R. (2015). Consequences of Big Data and Formalization on Accounting and Auditing Standards. Accounting Horizons, 29 (2) , 409-422Lev, B.(2004). Intangibles discussion. Available at: http: //accounting. rutgers. edu/docs/intangibles/Papers/Sharpening%20the%20Int.
Mayew, W. J. & Venkatachalam, M. (2012). "The power of voice: Managerial affective states and future firm performance". The Journal of Finance. 67 (1): 1-43.
Merrit C. (2013) Depreciation discussion available at http: //smallbusiness. chron. com/straightline-depreciation-method-capital-projects-66573. html.
Metaxas, D. & Zhang, S. (2013). "A review of motion analysis methods for human nonverbal communication computing", Image and Vision Computing. 31 (6): 421-433.
Moffitt, K. C. , & Vasarhelyi, M. A. (2013). AIS in an age of big data. Journal of information systems, 27 (2) , 1-19. ‏
Radhakrishnan, R. Ajay,­D. & Paris,­ S. (2005) "Audio analysis for surveillance applications, In Applications of Signal Processing to Audio and Acoustic”s ". IEEE Workshop on, pp. 158-161.
Shannon, C. E. & Weaver, W. (1949). "The mathematical theory of communication”. United States of America: University of Illinois press.
Syed, A. Kumar, Gillela. & C. Venugopal. (2013). "The future revolution on big data. " Future 2 (6).
Torralba, A. Fergus, R. & Freeman, W. T. (2008). "80 million tiny images: A large data set for nonparametric object and scene recognition". Pattern Analysis and Machine Intelligence, IEEE Transactions on. 30 (11): 1958-1970.
Vasarhelyi, M. A. Kogan, A. & Tuttle, B. (2015). "Big data in accounting: An overview". Accounting Horizons. 29 (2): 381-396
Vijayanarasimhan, S. & Grauman, K. (2014). "Large-scale live active learning: Training objects detectors with crawled data and crowds". International Journal of Computer Vision. 108 (1-2): 97-114.
Warren Jr, J. D. Moffitt, K. C. & Byrnes, P. (2015). "How Big Data Will Change Accounting". Accounting Horizons. 29 (2): 397-407
Zhang, J. Yang, X. & Appelbaum, D. (2015). "Toward Effective Big Data Analysis in Continuous Auditing". Accounting Horizons. 29 (2): 469-47
Journal of Accounting and Social Interests
Volume 6, Issue 3 - Serial Number 22
November 2016
Pages 35-50

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History

  • Receive Date: 04 February 2016
  • Revise Date: 03 July 2016
  • Accept Date: 03 July 2016

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