Digitalization, AI and organizational performance: The case of the banking sector

Abstract

This article presents a comprehensive literature review on the impact of Big Data and Artificial Intelligence (AI) on marketing strategies in the banking sector. It aims to identify the opportunities, challenges, and ethical considerations related to integrating these technologies into banking practices. The study adopts a qualitative methodology based on a carefully selected body of academic and professional publications spanning from 1997 to 2024, chosen for their relevance, methodological rigor, and innovative insights. Findings show that Big Data and AI enable banks to deliver personalized services, enhance customer satisfaction, and increase loyalty. Predictive analytics further empowers banks to anticipate customer needs, resulting in more targeted marketing approaches. However, the integration of these technologies raises concerns, especially in terms of data privacy, algorithmic bias, and transparency in automated decision-making. A major limitation identified is the rapid pace of technological change, requiring constant updates to knowledge and strategies. As a result, the article emphasizes the need for continued empirical research to assess the long-term implications and sustainability of these tools in banking marketing. From a practical standpoint, banks are encouraged to invest in robust data management systems and develop clear ethical frameworks for the responsible use of AI. The originality of this article lies in its integrative approach, combining technological, ethical, and strategic dimensions. It provides a comprehensive perspective valuable to both practitioners and researchers aiming to navigate the digital transformation of the banking industry.

Classification JEL : M31

Paper type : Theoretical Research