AI-Driven Financial Optimization in Emerging Economies: A Technology–Organization–Regulation Perspective
DOI:
https://doi.org/10.66635/3msx1095Keywords:
Algorithmic Finance, Computational Finance, Digital Transformation, Explainable AI, Risk Management TechnologiesAbstract
The world is becoming more and more dependent on Artificial Intelligence (AI) to transform the operational and strategic basis of financial services. Although previous literature has critically evaluated AI technologies and applications, little has been done to offer qualitative and theoretically based research to elaborate on how the adoption of AI results in financial optimization in various institutional settings. In this paper, the conceptual analysis of AI-based financial optimization through the prism of a particular argument, i.e., emerging economies will be in the form of qualitative analysis. The paper, based on the interpretive synthesis of the recent academic literature and industry perspectives, discusses the adoption of AI in an integrated approach that would consider the technological capability, organizational readiness, and regulatory-ethical alignment. The analysis also points out the fact that the quality of results of optimization in the new financial markets is not only dependent on the sophistication of the algorithms but also heavily dependent on the governance structure, explainability needs, and the institutional setting. This paper can help in providing a more in-depth insight into the application of AI-based responsible and efficient deployment to create sustainable value in financial services through creating a conceptual framework specific to the emerging economies. The results provide theoretical insights to future studies and operational recommendations to financial institutions that are going through the AI-driven change.
References
1.Agarwal, R., Guodong, G., DesRoches, C., Jha, A. K., & Kachalia, A. (2010). Research commentary—The digital transformation of healthcare: Current status and the road ahead. Information Systems Research, 21(4), 796–809. https://doi.org/10.1287/isre.1100.0327.
2.Arner, D. W., Barberis, J. N., & Buckley, R. P. (2017). FinTech, RegTech, and the reconceptualization of financial regulation. Northwestern Journal of International Law & Business, 37(3), 371–413.
3.Baker, J. (2012). The technology–organization–environment framework. In Y. K. Dwivedi et al. (Eds.), Information systems theory (pp. 231–245). Springer. https://doi.org/10.1007/9781-4419-6108-2_12.
4.Brennen, S., & Kreiss, D. (2016). Digitalization. In K. B. Jensen et al. (Eds.), The international encyclopedia of communication theory and philosophy. Wiley. https://doi.org/10.1002/9781118766804.wbiect111.
5.Dwivedi, Y. K., Hughes, L., Ismagilova, E., et al. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002.
6.Gomber, P., Koch, J. A., & Siering, M. (2017). Digital finance and FinTech: Current research and future research directions. Journal of Business Economics, 87(5), 537–580. https://doi.org/10.1007/s11573-017-0852-x.
7.Kraus, S., Feuerriegel, S., & Oztekin, A. (2020). Deep learning in business analytics and operations research: Models, applications and managerial implications. European Journal of Operational Research, 281(3), 628–641. https://doi.org/10.1016/j.ejor.2019.09.018.
8.Rai, A., Constantinides, P., & Sarker, S. (2019). Next-generation digital platforms: Toward human–AI hybrids. MIS Quarterly, 43(1), iii–ix. https://doi.org/10.25300/MISQ/2019/13795.
9.Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428.
10.Zetzsche, D. A., Buckley, R. P., Arner, D. W., & Barberis, J. N. (2017). From FinTech to TechFin: The regulatory challenges of data-driven finance. New York University Journal of Law & Business, 14(2), 393–446.
