Applying Artificial Intelligence in the Digital Transformation of Banking Sector †
Belgrade Banking Academy—Faculty of Banking, Insurance, and Finance, Union University Belgrade, 11000 Belgrade, Serbia
*
Author to whom correspondence should be addressed.
†
Presented at the Digital Transformation in Business: Challenges and New Opportunities, West Mishref, Kuwait, 17 November 2022.
Proceedings 2023, 85(1), 19; https://doi.org/10.3390/proceedings2023085019
Published: 15 March 2023
(This article belongs to the Proceedings of International Scientific Conference on Digital Transformation in Business: Challenges and New Opportunities)
Abstract
:This paper presents the process of digital transformation of banking sector aiming to emphasize the impact of applying artificial intelligence in order to enable chatbot customer service, robo advice, predictive analytics, cybersecurity, as well as credit scoring, and direct lending. The proposed framework is composed of three levels of application the artificial intelligence in digital banking. The application of artificial intelligence platforms in the banking sector is essential to meet the needs of today’s digital-first customers as well as to stay a step ahead of tomorrow’s digital banking challenges.
1. Objectives
It is a fact that the main competitors in the banking sector are not the banks that still have the branch networks, but the fasting growing companies such as the digital banks and fintech companies that are geared towards highly scalable digital acquisition [1,2,3,4]. The main objective of this paper is to present the impact of applying artificial intelligence in the banking sector, focusing on the process of digital transformation in banking.
2. Methodology
One of the key technologies that change the banking sector is artificial intelligence [5,6,7,8,9,10]. Four digital disruptors imply the application of artificial intelligence in the banking sector: intelligent data analysis, robotics, embedded banking, as well as smart infrastructure. We propose the methodology for applying artificial intelligence in banking in order to enable chatbot customer service, Robo advice, predictive analytics, cybersecurity, as well as credit scoring, and direct lending. The model is given in order to facilitate the process of digital transformation in the banking sector.
3. Results
According to the proposed framework for the digital transformation of the banking sector, there are three levels of application the artificial intelligence in digital banking. The first level refers to the use of machine learning in the process of teaching machines to learn patterns for the realization of digital banking. The second level relates to general intelligence, which could convince the customers and staff in digital banking they communicate with a human if they did not have the knowledge it was a computer. The third level refers to using artificial intelligence in digital banking that is smarter than banking staff.
4. Implications
The application of artificial intelligence in the banking sector is a long process and needs to fulfill many requirements to become operational. By using the proposed framework, it is necessary to digitally transform half of the jobs in banking today. Due to artificial intelligence, many old jobs in banking will disappear in the near future. On the other hand, there are new jobs such as data scientist, behavioral psychologist, the experience designer that are necessary for the process of realizing digital banking.
5. Originality Value
The application of artificial intelligence in the digital transformation of the banking sector is an unstoppable process. The proposed framework could help the banks that are at a crossroads. On the one hand, they can focus on the creation of infrastructure for the application of artificial intelligence in banking through both the transformation of business processes in banking and the employment of highly qualified staff who would know both technology and banking. On the other hand, they can come to the point they will operate in a world of branches until they are completely marginalized.
6. Contribution
Artificial intelligence is a prerequisite for the digital transformation of the banking sector. The proposed framework for the application of artificial intelligence in the banking sector can help the banks in seeking to balance in maintaining the level of trust they have built with their customers, delivering engaging and user-friendly digital banking experiences. In the digital banking era, going back to traditional banking practices, like requiring in-person visits for onboarding or manual reviews, is off the table. Having artificial intelligence platforms in place is essential for banks to meet the needs of today’s digital-first customers as well as to stay a step ahead of tomorrow’s digital banking challenges.
Author Contributions
Conceptualization, S.D.R. and H.H.; methodology, S.D.R. and H.H.; software, S.D.R.; validation, S.D.R., H.H. and M.B.; formal analysis, S.D.R.; investigation, M.B.; resources, S.D.R. and H.H.; data curation, S.D.R. and H.H.; writing—original draft preparation, S.D.R., H.H. and M.B.; writing—review and editing, S.D.R., H.H. and M.B.; visualization, M.B.; supervision, H.H.; project administration, S.D.R. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Belgrade Banking Academy (protocol code 06-1/22, date of approval: 12 June 2022).
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
References
- King, B. Bank 4.0: Banking Everywhere, Never at a Bank; Willey: Hoboken, NJ, USA, 2020; ISBN 978-1119506508. [Google Scholar]
- Deloitte. Artificial Intelligence in Banks. Available online: https://www2.deloitte.com/content/dam/Deloitte/ca/Documents/audit/ca-audit-abm-scotia-ai-in-banking.pdf (accessed on 20 July 2022).
- Dumas, J. 5 Applications of Artificial Intelligence in Banking. IBS Intelligence. Available online: https://ibsintelligence.com/ibsi-news/5-applications-of-artificial-intelligence-in-banking/ (accessed on 20 July 2022).
- Intone. Impact of Artificial Intelligence in the Banking Sector: How Is AI Transforming the Banking Industry? Available online: https://intone.com/impact-of-artificial-intelligence-in-banking-sector/ (accessed on 20 July 2022).
- Business Insider Intelligence. Artificial Intelligence in Banking 2022. Available online: https://www.businessinsider.com/ai-in-banking-report (accessed on 19 July 2022).
- Feedzai. A Guide to Community Banks: Democratizing Machine Learning. Available online: https://feedzai.com/aptopees/2021/01/Solutions_A_Guide_for_Community_Banks.pdf (accessed on 20 July 2022).
- Kaya, O. Artificial Intelligence in Banking: A Lever for Profitability with Limited Implementation to Date. Available online: https://www.dbresearch.com/PROD/RPS_ENPROD/PROD0000000000495172/Artificial_intelligence_in_banking%3A_A_lever_for_pr.pdf?undefined&realload=XLYNC7V1bc5zJCotlrfJmWQqkfB~SEHMjIG3VUu0mRXoFfTcI9cX4Voyv9dl9NrS (accessed on 20 July 2022).
- McKinsey. AI-Bank of the Future: Can Banks Meet the AI Challenge? Available online: https://www.mckinsey.com/industries/financial-services/our-insights/ai-bank-of-the-future-can-banks-meet-the-ai-challenge (accessed on 20 July 2022).
- Pega. AI, Open Banking, and Client Lifecycle Management—Differentiation Opportunities Abound. A PEGA/FINEXTRA REPORT. Available online: https://www.pega.com/ai-and-open-banking (accessed on 20 July 2022).
- Vedapradha, R.; Hariharan, R. Application of Artificial Intelligence in Investment Banks. Rev. Econ. Bus. Stud. 2018, 11, 131–136. [Google Scholar] [CrossRef] [Green Version]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Radenković, S.D.; Hanić, H.; Bugarčić, M. Applying Artificial Intelligence in the Digital Transformation of Banking Sector. Proceedings 2023, 85, 19. https://doi.org/10.3390/proceedings2023085019
AMA Style
Radenković SD, Hanić H, Bugarčić M. Applying Artificial Intelligence in the Digital Transformation of Banking Sector. Proceedings. 2023; 85(1):19. https://doi.org/10.3390/proceedings2023085019
Chicago/Turabian StyleRadenković, Sonja D., Hasan Hanić, and Milica Bugarčić. 2023. "Applying Artificial Intelligence in the Digital Transformation of Banking Sector" Proceedings 85, no. 1: 19. https://doi.org/10.3390/proceedings2023085019
APA StyleRadenković, S. D., Hanić, H., & Bugarčić, M. (2023). Applying Artificial Intelligence in the Digital Transformation of Banking Sector. Proceedings, 85(1), 19. https://doi.org/10.3390/proceedings2023085019
