Machine Learning and Artificial Intelligence in Banking
DOI:
https://doi.org/10.18034/ei.v5i2.490Keywords:
Machine Learning, Artificial Intelligence, Financial SectorAbstract
Machine Learning and Artificial Intelligence applications in the financial sector have been thriving in the recent past. Their immense power has been harnessed in these institutions to offer business solutions in front end and back end processes to create efficiency and improve customer experience. This article will lay bare the applications of Machine Learning and Artificial Intelligence and evaluate their utility in different banking industry functional areas and frame how these institutions effectively use computational intelligence to improve their business. While traditional banking institutions are quickly catching up with the computational intelligence technologies with products like Chatbot, fintech companies, which seem to have embrace A.I. a long time ago, plays a critical role through its innovation and contribute substantially to financial intelligence. In conclusion, we can aptly say that Machine Learning and Artificial Intelligence technologies are taking over the banking sector, and it seems like there's nothing we can do about it.
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References
Arthur Samuel (1959). Some Studies in Machine Learning Using the Game of Checkers. IBM Journal 3, (3): 210-229. https://ssrn.com/abstract=3226514
Bauguess, Scott W., The Role of Big Data, Machine Learning, and A.I. in Assessing Risks: A Regulatory Perspective (June 21, 2017). SEC Keynote Address: OpRisk North America 2017. http://dx.doi.org/10.2139/ssrn.3226514
Castelli, M., Manzoni, L., & Popovic, A. (2016). An artificial intelligence system to predict quality of service in banking organizations. Computational Intelligence and Neuroscience: CIN, 2016. http://dx.doi.org/10.1155/2016/9139380
Das, S., Dey, A., Pal, A., & Roy, N. (2015). Applications of artificial intelligence in machine learning: Review and prospect. International Journal of Computer Applications, 115(9) http://dx.doi.org/10.5120/20182-2402
Donepudi, P. (2016). Influence of Cloud Computing in Business: Are They Robust? Asian Journal of Applied Science and Engineering, 5(3), 193-196. https://doi.org/10.5281/zenodo.4110309
Donepudi, P. (2017). AI and Machine Learning in Banking: A Systematic Literature Review. Asian Journal of Applied Science and Engineering, 6(3), 157-162. https://doi.org/10.5281/zenodo.4109672
Kumar, A. S. & Chandrakala, D. (2016). A survey on customer churn prediction using machine learning techniques. International Journal of Computer Applications, 154(10) http://dx.doi.org/10.5120/ijca2016912237
Purdy M. & Daugherty, P. (2016). Why artificial intelligence is the Future of Growth. Accenture, Available online at https://www.accenture.com/t20170524t055435__w__/ca-en/_acnmedia/pdf-52/accenture-why-ai-is-the-future-of-growth.pdf
SEC Speech, Has Big Data Made Us Lazy?, Midwest Region Meeting of the American Accounting Association, October 2016. https://www.sec.gov/news/speech/bauguess-american-accounting-association-102116.html
Taher-Uz-Zaman, M., Ahmed, M. S., Hossain, S., Hossain, S., & Jamal, G. R. A. (2014). Multipurpose Tactical Robot. Engineering International, 2(1), 21-27. https://doi.org/10.18034/ei.v2i1.204
Yu, L., Yang, Z., & Tang, L. (2016). A novel multistage deep belief network based extreme learning machine ensemble learning paradigm for credit risk assessment. Flexible Services and Manufacturing Journal, 28(4), 576-592. http://dx.doi.org/10.1007/s10696-015-9226-2
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