Navigating the Future of Finance: How Artificial Intelligence is Transforming Accounting
DOI:
https://doi.org/10.22399/ijcesen.1648Keywords:
AI, Machine learning, Natural Language Processing(NLP), Data analysis, Fraud detectionAbstract
The force that is driving this revolution in the accounting domain is Artificial Intelligence (AI). It holds the power to enhance efficiencies, accuracies, and decision-making virtues. The present article ventures to illustrate how AI is bringing changes to the accounting sector. Moreover, it imparts a granular understanding of the vital armaments of AI that includes machine learning, natural language processing, and data analysis. Incorporating AI into accounting can reap several benefits, among them are productivity increases, better precision, cost-savings, and improved ability for analytics. At the same time, the implementation of AI also throws in challenges: examples include technical problems of interfacing, issues concerning ethics, and the demand for new capabilities and education for accountants. Other articles describe cases where AI has been successfully applied in accounting and detail the lessons learned and effects on business. In these, the future of AI in accounting is described through the crystal ball of emerging trends and technologies, and, moreover, whether accountants will tell their clients differently because of AI. It also considers the greater effects of AI on the financial landscape by surfacing the need for new regulatory standards to guarantee that AI is utilized in an ethical and responsible manner. This paper in total tries to paint a comprehensive picture of how AI will cause a transformation in the accounting profession and why professional adaptation is needed.
References
[1] Appelfeld, D., & Rona, S. (2019). Automated Financial Reporting: The Role of AI in Enhancing Efficiency and Accuracy. Journal of Accounting and Finance, 35(2), 123-135.
[2] Bolton, R., & Hand, D. J. (2002). Statistical Fraud Detection: A Review. Statistical Science, 17(3), 235-255.
[3] Davenport, T. H., & Harris, J. G. (2007). Competing on Analytics: The New Science of Winning. Harvard Business Review Press.
[4] Deloitte. (2019). AI-Driven Audit: Enhancing Efficiency and Accuracy through Machine Learning. Deloitte Insights.
[5] Ernst & Young (EY). (2018). Robotic Process Automation in Accounting: Enhancing Efficiency and Productivity. EY Global.
[6] Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
[7] Jurafsky, D., & Martin, J. H. (2009). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Prentice Hall.
[8] Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. Bitcoin.org.
[9] Shmueli, G., & Koppius, O. (2011). Predictive Analytics in Accounting: Enhancing Decision-Making through Big Data Analysis. Journal of Accounting Research, 49(3), 687-705.
[10] Shor, P. W. (1994). Algorithms for Quantum Computation: Discrete Logarithms and Factoring. Proceedings of the 35th Annual Symposium on Foundations of Computer Science, 124-134.
[11] Van der Aalst, W. M. P., Bichler, M., & Heinzl, A. (2018). Robotic Process Automation. Business & Information Systems Engineering, 60(3), 163-166.
[12] Russell, S., & Norvig, P. (2009). Artificial Intelligence: A Modern Approach. Prentice Hall.
[13] Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.
[14] Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Review Press.
[15] Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company.
[16] Tegmark, M. (2017). Life 3.0: Being Human in the Age of Artificial Intelligence. Knopf.
[17] Chui, M., Manyika, J., & Miremadi, M. (2016). Where Machines Could Replace Humans—And Where They Can’t (Yet). McKinsey & Company.
[18] Bughin, J., Hazan, E., & Ramaswamy, R. (2017). How Artificial Intelligence Will Change Work. McKinsey Global Institute.
[19] Davenport, T. H. (2019). The AI Advantage: How to Put the Artificial Intelligence Revolution to Work. MIT Press.
[20] Marcus, G., & Davis, E. (2019). Rebooting AI: Building Artificial Intelligence We Can Trust. Pantheon Books.
[21] Smith, A., & Anderson, K. (2014). Machine, Platform, Crowd: Harnessing Our Digital Future. W. W. Norton & Company.
[22] Ford, M. (2015). Rise of the Robots: Technology and the Threat of a Jobless Future. Basic Books.
[23] Susskind, R., & Susskind, D. (2015). The Future of the Professions: How Technology Will Transform the Work of Human Experts. Oxford University Press.
[24] Kaplan, A., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53(1), 59-68.
[25] O'Reilly, T., & Battelle, J. (2013). Web Squared: Web 2.0 Five Years On. O'Reilly Media.
[26] Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165-1188.
[27] KPMG. (2019). The Future of Accounting: Embracing Artificial Intelligence. KPMG Insights.
[28] PwC. (2018). Artificial Intelligence in Financial Services: Harnessing the Power of Data. PwC Global.
[29] Accenture. (2017). Artificial Intelligence: The Future of Growth. Accenture Strategy.
[30] McKinsey & Company. (2017). Artificial Intelligence: The Next Digital Frontier? McKinsey Global Institute.
[31] Kokina, J., & Davenport, T. H. (2017). The Emergence of Artificial Intelligence: How Automation is Changing Auditing. Journal of Emerging Technologies in Accounting, 14(1), 115-122.
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