References
Adam, M., Wessel, M., &Benlian, A. (2021).AI-based chatbots in customer service and their effects on user
compliance. Electronic Markets, 31(2), 427-445.
Addo, P. M., Guegan, D., &Hassani, B. (2018).Credit risk analysis using machine and deep learning
models. Risks, 6(2), 38.
Afiouni, R. (2019). Organizational learning in the rise of machine learning.In Proceedings of the 40th
International Conference on Information Systems (ICIS), Munich, Germany, vol 2 15–18
Agidi, R. C. (2019). Artificial intelligence in Nigeria financial sector. International Journal of Electronics
and Information Engineering, 11(1), 40-47.
Alhaddad, M. M. (2018). Artificial intelligence in banking industry: A review on fraud detection, credit
management, and document processing. ResearchBerg Review of Science and Technology, 2(3), 25-
Ali, R., Ali, A., Iqbal, F., Khattak, A. M., &Aleem, S. (2020). A systematic review of artificial intelligence
and machine learning techniques for cyber security. In Big Data and Security: First International
Conference, ICBDS 2019, Nanjing, China, December 20–22, 2019, Revised Selected Papers 1 (pp.
584-593). Springer Singapore.
Alt, M. A., Vizeli, I., &S?pl?can, Z. (2021).Banking with a chatbot–A study on technology
acceptance. StudiaUniversitatis Babes-BolyaiOeconomica, 66(1), 13-35.
Alarfaj, F. K., Malik, I., Khan, H. U., Almusallam, N., Ramzan, M., & Ahmed, M. (2022).Credit card fraud
detection using state-of-the-art machine learning and deep learning algorithms. IEEE Access, 10,
39700-39715
Aminat, A. B., Ezekiel, A. I., &Obafemi, D. S.(2023) The Impact of Internal Control Mechanisms on Fraud
Detection and Prevention in Nigeria Deposit Money Banks
Apruzzese, G., Laskov, P., Montes de Oca, E., Mallouli, W., Brdalo Rapa, L., Grammatopoulos, A. V., & Di
Franco, F. (2023). The role of machine learning in cybersecurity. Digital Threats: Research and
Practice, 4(1), 1-38.
Aschi, M., Bonura, S., Masi, N., Messina, D., &Profeta, D. (2022).Cybersecurity and fraud detection in
financial transactions. In Big Data and Artificial Intelligence in Digital Finance: Increasing
Personalization and Trust in Digital Finance using Big Data and AI (pp. 269-278). Cham: Springer
International Publishing.
Akpanobong, U. E., &Essien, N. P. (2022). Artificial intelligence adoption for financial services
optimizations and innovation by commercial banks in Nigeria. International Journal of Advancement
in Education, Management, Science and Technology, 5(1), 5-15.
Bello, I. H. M. S., &Madaki, A. A. Effect of Control Environment on Fraud Detection in Deposit Money
Banks in Nigeria.
Boshnak, H. A. (2023). Ownership concentration, managerial ownership, and firm performance in Saudi
listed firms. International Journal of Disclosure and Governance, 1-14.
Boulieris, P., Pavlopoulos, J., Xenos, A., &Vassalos, V. (2023).Fraud detection with natural language
processing. Machine Learning, 1-22
Buyuktepe, O., Catal, C., Kar, G., Bouzembrak, Y., Marvin, H., &Gavai, A. (2023).Food fraud detection
using explainable artificial intelligence. Expert Systems, e13387.
Cardona, D.R., Werth, O., Schönborn, S., &Breitner, M.H. (2019).A Mixed Methods Analysis of the
Adoption and Diffusion of Chatbot Technology in the German Insurance Sector. Americas
Conference on Information File:///c:/user/user/downloadsAMCIS-2019-camera-ready -adoption and
diffusion of chatbottechnologyininsurance.pdf
Charity,B.,Agwu.A.,Babatunde,K.,&Oluwafunbi,F.(2023). Awareness,adoption and perception of whatsapp
customer service chatbots in the banking sector:Perspectives from undergraduates students in
Lagos,Nigeria.Nigerian Journal of communication review(NJCR).1(2)
Cheah,S.&Farzana.P.(2020).Usage and impact of artificial intelligence on Accounting: evidence from
Malaysian organizations. Asian journal of business and accounting.13(1), 1-8.https://doi.org/10.22452/ajba.vol13no1.8
Choi, D., & Lee, K. (2018). An artificial intelligence approach to financial fraud detection under IoT environment:
A survey and implementation. Security andCommunication
Networks,2018.https://doi.org/10.1155/2018/5483472
Cîmpeanu, I. A., Dragomir, D. A., &Zota, R. D. (2023).Banking Chatbots: How Artificial Intelligence Helps
the Banks.In Proceedings of the International Conference on Business Excellence (Vol. 17, No. 1,
pp. 1716-1727).
Clements, J. M., Xu, D., Yousefi, N., &Efimov, D. (2020). Sequential deep learning for credit risk monitoring
with tabular financial data. arXiv preprint arXiv:2012.15330.
Dasilas, A., &Karanovi?, G. (2023). The impact of FinTech firms on bank performance: evidence from the
UK. EuroMed Journal of Business
Dayyabu, Y. Y., Arumugam, D., &Balasingam, S. (2023). The application of artificial intelligence techniques
in credit card fraud detection: A quantitative study. In E3S Web of Conferences (Vol. 389, p. 07023).
Dhruba, M. I. M., Ghani, N. H., Hossain, S., &Shoumo, S. Z. H. (2018). Application of machine learning in
credit risk assessment: a prelude to smart banking (Doctoral dissertation, BRAC University).
Dongol, P. (2023). Impact of Corporate Board Size on Firm Performance: Evidence from the Nepalese
Banks. Journal of Corporate Finance Management and Banking System (JCFMBS) ISSN: 2799-
1059, 3(02), 1-8.
Ekpa, M., Onuora, J. K., & David, S.(2023) Artificial Brain Power and Corporate Performance of Listed Deposit
Money Banks in Nigeria.Internal Journal of economics and financial
management(IJEFM).8(4)1-97.
Elegunde, A. F., &Osagie, R. (2020).Artificial intelligence adoption and employee performance in the
Nigerian banking industry. International Journal of Management and Administration, 4(8), 189-205.
Eneh, O. M. R., Okeke, F. C., &Amahalu, N. N. (2023). ARTIFICIAL INTELLIGENCE AN
FRAUD DETECTION OF DEPOSIT MONEY BANKS IN AWKA-SOUTH ANAMBRA STATE,
NIGERIA. Global Journal of Artificial Intelligence and Technology Development, 1(2), 8-20
Foote, K. D. (2016). A brief history of artificial intelligence. DATAVERSITY Education, LLC. https://www.
dataversity. net/brief-history-artificial-intelligence/(accessed 2002).
Frederica, D., &Murwaningsari, E. (2019).The effect of the use of artificial intelligence and operational risk
management on banking performance with the implementation of regulation as a moderation
variable. ASBL Degres, 146-158.
Gupta,A., &Sharma, D. (2019). Customers’Attitude towards Chatbots in Banking Industry of
India. International Journal of Innovative technology and exploring Engineering, 8(11),1222-1225.
Hassanzadeh, M., &Bigdeli, T. B. (2019). Return of Investment (ROI) in Research and Development (R&D):
Towards a framework. In Collaboration–Impact on Productivity and Innovation: Proceedings of
14th International Conference on Webometrics, Informetrics and Scientometrics& 19th COLLNET
Meeting 2018, December 5–8, 2018, University of Macau, Macau (pp. 31-39)
Harfouche, A., Quinio, B., Skandrani, S. R., &Marciniak, R. (2017).A framework for artificial knowledge
creation in organizations.In ICIS 2017.
Hambolu, V. O., Omuemu, S. O., &Majeed, A. T. A. (2022).The impact of credit risk on the profitability of
commercial banks in Nigeria. Fuoye Journal of Finance and Contemporary Issues, 3(2). 21-35
Imenda, S. (2014). Is there a conceptual difference between theoretical and conceptual frameworks?. Journal
of social sciences, 38(2), 185-195.
Ikhsan, W. M., Ednoer, E. H., Kridantika, W. S., &Firmansyah, A. (2022).Fraud detection automation
through data analytics and artificial intelligence. Riset:
JurnalAplikasiEkonomiAkuntansidanBisnis, 4(2), 103-119.
Irom, I. M., Joshua, O., Ahmed, M. N., & Emmanuel, A. T. (2018). Effect of firm attributes on return on asset
of listed manufacturing companies in Nigeria.
Jibril, R. S., Usman, A. M., &Abdullahi, A. A. (2023). Impact of firm attribute on financial Performance of
li
