[1] Shankar, A. and Jebarajakirthy, C. (2019), “The influence of e-banking service quality on customer loyalty: A moderated mediation approach”, International Journal of Bank Marketing, Vol. 37 No. 5, pp. 1119-1142. https://doi.org/10.1108/IJBM-03-2018-0063.

[2] Garepasha, A., Aali, S., Bafandeh Zendeh, A.R. and Iranzadeh, S. (2020), “Relationship dynamics in customer loyalty to online banking services”, Journal of Islamic Marketing, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JIMA-09-2019-0183.

[3] Zohra Ghali (2021) Motives of customers’ e-loyalty towards e-banking services: a study in Saudi Arabia, Journal of Decision Systems, DOI: 10.1080/12460125.2020.1870063

[4] Ramesh V., Jaunky V.C., Roopchund R., Oodit H.S. (2020) ‘Customer Satisfaction’, Loyalty and ‘Adoption’ of E-Banking Technology in Mauritius. In: Bhateja V., Satapathy S., Satori H. (eds) Embedded Systems and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 1076. Springer, Singapore. https://doi.org/10.1007/978-981-15-0947-6_82.

 [5 Fadaei Noghani, F., Moattar, M. (2017). Ensemble Classification and Extended Feature Selection for Credit Card Fraud Detection. Journal of AI and Data Mining, 5(2), 235-243. doi: 10.22044/jadm.2016.788.

[6 Moslehi, F., Haeri, A., Moini, A. (2018). Analyzing and Investigating the Use of Electronic Payment Tools in Iran using Data Mining Techniques. Journal of AI and Data Mining, 6(2), 417-437. doi: 10.22044/jadm.2017.5352.1643

[7] Feng Li, Hui Lu, Meiqian Hou, Kangle Cui, Mehdi Darbandi,”Customer satisfaction with bank services: The role of cloud services, security, e-learning and service quality,Technology in Society,Volume 64,2021,101487,ISSN 0160-791X, https://doi.org/10.1016/j.techsoc.2020.101487.

[8] Mulia, D., Usman, H. and Parwanto, N.B. (2020), “The role of customer intimacy in increasing Islamic bank customer loyalty in using e-banking and m-banking”, Journal of Islamic Marketing, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JIMA-09-2019-0190

[9] Ahmed, R. R., Vveinhardt, J., Štreimikienė, D., Ashraf, M., & Channar, Z. A. (2017). Modified SERVQUAL model and effects of customer attitude and technology on customer satisfaction in banking industry: mediation, moderation and conditional process analysis. Journal of Business Economics and Management, 18(5). https://doi: 10.3846/16111699.2017.1368034

[10] Andrii Skirka, Bogdan Adamyk, Oksana Adamyk, Mariana Valytska, “Trust in the European Central Bank: Using Data Science and predictive Machine Learning Algorithms”, Advanced Computer Information Technologies (ACIT) 2020 10th International Conference on, pp. 356-361, 2020.

[11] Viktorija Skvarciany & Daiva Jurevičienė (2017) Factors affecting personal customers’ trust in traditional banking: case of the Baltics, Journal of Business Economics and Management, 18:4, 636-649, https://doi: 10.3846/16111699.2017.1345784

[12] Moslehi, F., Haeri, A. A novel hybrid wrapper–filter approach based on genetic algorithm, particle swarm optimization for feature subset selection. J Ambient Intell Human Comput 11, 1105–1127 (2020). https://doi.org/10.1007/s12652-019-01364-5.

[13] XI, Y.-p. and C. Min(2017),Application of Data Mining Technology in CRM System of Commercial Banks, DEStech Transactions on Engineering and Technology Research (eeta),https:// doi:10.12783/dtetr/eeta2017/7759

[14] Behnaz, S., Hosseini, R. (2019). Classification of Customer Services in Terms of the Use of Shetab Network Services Based on Ensemble Classification. Modern Research in Decision Making, 3(4), 51-70.

[15] Moslehi, F., Haeri, A., Gholamian, M. (2019). Investigation of effective factors in expanding electronic payment in Iran using datamining techniques. Journal of Industrial and Systems Engineering, 12(2), 61-94.

 [16] Nuha M., Mahmud S., Sattar A. (2021) A Case Study and Fraud Rate Prediction in e-Banking Systems Using Machine Learning and Data Mining. In: Borah S., Pradhan R., Dey N., Gupta P. (eds) Soft Computing Techniques and Applications. Advances in Intelligent Systems and Computing, vol 1248. Springer, Singapore. https://doi.org/10.1007/978-981-15-7394-1_6

[17] Keramati, A., Ghaneei, H. & Mirmohammadi, S.M. Developing a prediction model for customer churn from electronic banking services using data mining. Financ Innov 2, 10 (2016). https://doi.org/10.1186/s40854-016-0029-6

 [18] Shewangu Dzomira (2016)- Financial consumer protection: Internet banking fraud awareness by the banking sector [9]Journal of Internet Banking and Commerce An open access Journal of Internet Banking and Commerce, April 2016, vol. 21, no.2

[19] Mousa, Ayad Hameed; Mousa, Sundus Hameed; Aljshamee, Mustafa; Nasir, Intedhar Shakir.” Determinants of customer acceptance of e-banking in Iraq using technology acceptance model”; Yogyakarta Vol. 19, Iss. 2,  (Apr 2021): 421-431. DOI:10.12928/TELKOMNIKA.v19i2.16068