Automation and Machine Learning in Transforming the Financial Industry


  • Praveen Kumar Donepudi Cognizant Technology Solutions



Artificial intelligence, Innovation, financial services, virtual assistant, machine learning


The major purpose of this study was to analyze the influence of machine learning on the digital age, particularly in the field of finance. This study involves the application of machine learning, its challenges, opportunities and effect on job openings and operations. This paper is based on the findings of a qualitative study of the text on the subject of machine learning in finance. The theoretical portion of this paper explores the universal framework, such as the past, existing and the next level of the machine learning, with emphasis on its advantages and drawbacks. The study also examines the global recognition of machine learning in the review of artificially intelligent development and start-ups in European countries. The research methodology used in this study was the evaluation of the qualitative methods in the paper. The study also reviewed twenty electronic records and articles on machine learning in finance. During the research on how computer technology transforms the banking sector, the implementation and impact of artificial intelligence in financing was discussed. Research shows that several financial institutions have significantly benefited from the introduction of a variety of machine learning and artificial intelligence. This paper demonstrates that there is a lack of experience in the field of machine learning, even as many unskilled or semi-qualified tasks carried out by individuals are carried out by machines. This study has shown that, through banking and financial valuation, whether it is manufacturing, data analysis or continuing to invest, there will be many more developments that can get the job done.


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Author Biography

Praveen Kumar Donepudi , Cognizant Technology Solutions

Principal Architect, IT Infrastructure Services, Cognizant Technology Solutions, United States


Abedin, M. M., Ahmed, A. A. A., & Neogy, T. K. (2012). Mechanism of Accountability and Auditing: Public Sector Scenarios of Bangladesh. Journal of Business Studies, 4, 131-148.

Ahmed, A. A. A., & Siddique, M. N.-E.-A. (2013). Internet Banking Espousal in Bangladesh: A Probing Study. Engineering International, 1(2), 93-100.

Athey, S. (2018). The impact of machine learning on economics The economics of artificial intelligence: An agenda (pp. 507-547): University of Chicago Press.

Baydin, A. G., Pearlmutter, B. A., Radul, A. A., and Siskind, J. M. (2017). Automatic differentiation in machine learning: a survey. The Journal of Machine Learning Research, 18(1), 5595-5637.

Begum, R., Ahmed, A. A. A., & Neogy. T. K. (2012). Management Decisions and Univariate Analysis: Effects on Corporate Governance in Bangladesh. Journal of Business Studies, 3, 87-115.

Cartea, A., S. Jaimungal, and J. Penalva (2015). ´ Algorithmic and High-Frequency Trading (1st ed.). Cambridge: Cambridge University Press.

Chui, M., Manyika, J., and Miremadi, M. (2015). Four fundamentals of workplace automation. McKinsey Quarterly, 29(3), 1-9.

Chui, M., Manyika, J., and Miremadi, M. (2016). Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly, 30(2), 1-9.

De Prado, M. L. (2018). Advances in financial machine learning: John Wiley & Sons.

Donepudi, P. K. (2015). Crossing Point of Artificial Intelligence in Cybersecurity. American Journal of Trade and Policy, 2(3), 121-128.

Donepudi, P. K. (2018a). AI and Machine Learning in Retail Pharmacy: Systematic Review of Related Literature. ABC Journal of Advanced Research, 7(2), 109-112.

Donepudi, P. K. (2018b). Application of Artificial Intelligence in Automation Industry. Asian Journal of Applied Science and Engineering, 7(1), 7-20.

Gomber, P., Kauffman, R. J., Parker, C., and Weber, B. W. (2018). On the fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems, 35(1), 220-265.

Horowitz, M. C., Allen, G. C., Saravalle, E., Cho, A., Frederick, K., and Scharre, P. (2018). Artificial intelligence and international security: Center for a New American Security.

Kokina, J., and Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), 115-122.

Kuroda, H. (2017). AI and the Frontiers of Finance. Paper presented at the Speech given by the Governor of the Bank of Japan at the Conference on “AI and Financial Services/Financial Markets.

Lu, H., Li, Y., Chen, M., Kim, H., and Serikawa, S. (2018). Brain intelligence: go beyond artificial intelligence. Mobile Networks and Applications, 23(2), 368-375.

Mackenzie, A. (2015). The production of prediction: What does machine learning want? European Journal of Cultural Studies, 18(4-5), 429-445.

Mullainathan, S., and Spiess, J. (2017). Machine learning: an applied econometric approach. Journal of Economic Perspectives, 31(2), 87-106.

Rouhiainen, L. (2018). Artificial Intelligence: 101 things you must know today about our future: Lasse Rouhiainen.

Shabbir, J., and Anwer, T. (2018). Artificial intelligence and its role in near future. arXiv preprint arXiv:1804.01396.

Sharma, R., Mithas, S., and Kankanhalli, A. (2014). Transforming decision-making processes: a research agenda for understanding the impact of business analytics on organisations: Taylor & Francis.

Treleaven, P., and Batrinca, B. (2017). Algorithmic regulation: automating financial compliance monitoring and regulation using AI and blockchain. Journal of Financial Transformation, 45, 14-21.

Turing, A. M., (1950). Computing Machinery and Intelligence, Mind59: 433–460; reprinted in (Copeland, 2004)

Wilson, H. J., and Daugherty, P. R. (2018). Collaborative intelligence: humans and AI are joining forces. Harvard Business Review, 96(4), 114-123.




How to Cite

Donepudi , P. K. . (2019). Automation and Machine Learning in Transforming the Financial Industry. Asian Business Review, 9(3), 129–138.