REA Press Null REA Press3042-31043042-3104 REA Press https://doi.org/10.48314/apem.vi.37 Research Article Enterprise architecture, Artificial intelligence, Machine learning, Digital transformation, E-banking processes. A Proposed Hybrid Conceptual Model of Artificial Intelligence and Enterprise Architecture for Digital Transformation in Banks: An Approach to Improving Business ProcessesA Proposed Hybrid Conceptual Model of Artificial Intelligence and Enterprise Architecture for Digital Transformation in Banks: An Approach to Improving Business Processes Rad Saleh Department of Information Technology Engineering, Faculty of Engineering and Computer Science, Shahid Beheshti University, Tehran, Iran. Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran. Darvish Rouhani Babak Department of Computer and Information Technology, Faculty of Engineering, Payame Noor University (PNU), Tehran, Iran. Banaeian Hamid Department of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran. 10 2025 14 10 2025 2 4 © 2025 REA Press 2025

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 A Proposed Hybrid Conceptual Model of Artificial Intelligence and Enterprise Architecture for Digital Transformation in Banks: An Approach to Improving Business Processes

Digital transformation, as a strategic imperative in the banking industry, necessitates the integration of Artificial Intelligence (AI) and Enterprise Architecture (EA) to enhance business processes. This paper presents a hybrid conceptual model wherein various layers of EA are aligned with AI components. The objective of this model is to augment organizational agility and efficiency through improved decision-making, process automation, and data analytics. Furthermore, by identifying the interconnection points between AI and EA, the optimization of banking loan processes is examined as a practical application. The results indicate that this integration can lead to an improved customer experience, reduced processing time, and increased accuracy in credit assessment. Through this model, banks will be able to respond rapidly to environmental changes and enhance their competitiveness in the market.

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