Conversational Artificial Intelligence (AI) and Bank Operational Efficiency

https://doi.org/10.35912/ijamis.v1i2.1915
Published: Aug 6, 2024

Abstract:

Purpose: The main objective of the research was to analyse the effects of conversational artificial intelligence (AI) on bank operational efficiency. The emergency of conversational artificial intelligence (AI) has revolutionised the way business interacts with its customers.

Methodology: The study employed a mixed- method approach where interviews and questionnaires were used to collect qualitative and quantitative data. A sample of 92 bank employees was drawn from ten Zimbabwean banks.

Findings: Conversational AI has a positive impact on banking operational efficiency. Specifically, conversational AI improves customer services by providing faster and more accurate responses to customer inquiries, reduces operational costs by automating routine tasks and improve workflow efficiency

Limitation: The study concentrated on the banking industry of one particular country.

Contribution: The study makes a significant contribution in understanding the advantages of adopting conversational artificial intelligence in banking operations.

Keywords:
1. Artificial intelligence
2. Conversational artificial intelligence
3. financial technology
4. Chatbot
5. Operational efficiency
Authors:
1 . Lilian Gumbo
Midlands State University, Zimbabwe
2 . Margaret Mashizha
University of Zimbabwe, Zimbabwe
3 . Chosani Simon
Midlands State University, Zimbabwe
4 . Phillipa Phiri
Midlands State University, Zimbabwe
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How to Cite
Gumbo, L., Mashizha, M., Simon, C., & Phiri, P. (2024). Conversational Artificial Intelligence (AI) and Bank Operational Efficiency. International Journal of Accounting and Management Information Systems, 1(2), 109–121. https://doi.org/10.35912/ijamis.v1i2.1915
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Issue & Section
Vol. 1 No. 2 (2023): August
Articles
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

References

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  1. Armstrong, S. (2019). Conversational AI: The Future of Customer Service. Harvard Business Review. Retrieved from https://hbr.org/2019/11/conversational-ai-the-future-of-customer-service
  2. Basole, R. C., & Accenture, A. I. (2021, January). Visualizing the Evolution of the AI Ecosystem. In HICSS (pp. 1-10).
  3. Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., & Dahlström, P. (2018). Artificial intelligence: The next digital frontier? McKinsey Global Institute.
  4. Capgemini Digital Transformation Institute. (2017). The digital talent gap: are companies doing enough?.
  5. Deloitte, A. B. (2021). 2021 Transparency Report.
  6. Folstad, A. & Nordheim, Cecilie & Bjorkli, Cato. (2018). What Makes Users Trust a Chatbot for Customer Service? An Exploratory Interview Study. 194-208. 10.1007/978-3-03001437-7_16.
  7. Gao, Y., & Bai, X. (2020). Exploring the impact of chatbots on customer satisfaction: A case of the banking industry. International Journal of Information Management, 50, 156-166.
  8. Gavrilova, S., Baburin, V., Danilina, A., Gryaznova, V., Perov, V., & Shnyparkov, A. (2014, May). The economic risk of the landslides on Northern Caucases. In EGU General Assembly Conference Abstracts (p. 13357).
  9. Gomber, P. et al. (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.
  10. Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS quarterly, 213-236.
  11. Gupta, A., & George, J. F. (2019). Artificial Intelligence and Customer Experience Management in Banking: A Conceptual Framework. International Journal of Bank Marketing, 37(1), 146-164.
  12. Gupta, A., & George, J. F. (2019). Artificial Intelligence and Customer Experience Management in Banking: A Conceptual Framework. International Journal of Bank Marketing, 37(1), 146-164.
  13. Gupta, R., Srivastava, D., Sahu, M., Tiwari, S., Ambasta, R. K., & Kumar, P. (2021). Artificial intelligence to deep learning: machine intelligence approach for drug discovery. Molecular diversity, 25, 1315-1360.
  14. Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of service research, 21(2), 155-172.
  15. Jalali, F., & Khamseh, A. (2014). Identification and comparison of structural factors of innovation capability in ESCO with desirable status. International Journal of Organizational Leadership, 3, 103-113.
  16. Khan, I., Ahmad, A. R., Jabeur, N., & Mahdi, M. N. (2021). An artificial intelligence approach to monitor student performance and devise preventive measures. Smart Learning Environments, 8(1), 1-18.
  17. Lee, S. H., & Lee, Y. K. (2019). The impact of chatbots on customer satisfaction: A case study of Korean banks. Sustainability, 11(20), 5861.
  18. Li, X., Chen, Z., & Li, K. (2020). Enhancing customer relationship management with artificial intelligence: An overview. Journal of Business Research, 113, 25-36.
  19. Li, Y., & Huang, T. (2020). Exploring the Impact of Artificial Intelligence on Customer Experience in Banking Industry. Journal of Retailing and Consumer Services, 52, 101924.
  20. Liao, M., & Yao, Y. (2021). Applications of artificial intelligence?based modeling for bioenergy systems: A review. GCB Bioenergy, 13(5), 774-802.
  21. Liu, C., & Lu, L. (2020). The effects of chatbot anthropomorphism on customer responses in service encounters. Journal of Business Research, 116, 421-433.
  22. McKinsey and Company (2018) The executive’s AI playbook, Analytics, McKinsey.
  23. Ostagar, A. M. (2018). Impact of technology and innovation in insurance sector. International Journal of Management, IT and Engineering, 8(12), 253-258.
  24. Pereira, P. J. (2019). Accenture PLC-information technology services (Doctoral dissertation).
  25. Saunders, M., Lewis, P., Thornhill, A. and Wilson, J., 2009. Business research methods. Financial Times, Prentice Hall: London
  26. Shnyparkov, A. L., Petrova, E. G., Vashchalova, T. V., Gavrilova, S. A., Danilina, A. V., & Gryaznova, V. V. (2012, April). Influence of natural and technological emergency situations on tourism and sustainable development in St. Petersburg and Leningrad region (Russia). In EGU General Assembly Conference Abstracts (p. 6400).
  27. Vlahos, J. (2019). Talk to me: How voice computing will transform the way we live, work, and think. Eamon Dolan Books.
  28. Zhang, Y., Xu, Y., & Liu, F. (2019). How Artificial Intelligence Transforms Banking: Evidence from Chatbots. Journal of Business Research, 98, 365-380.