Revolutionizing Organizational Decision-Making for Banking Sector: A Machine Learning Approach with CNNs in Business Intelligence and Management

Abstract

This research investigates the transformative impact of deep learning, particularly Convolutional Neural Networks (CNNs) such as VGG16, ResNet50, and InceptionV3, on organizational management and business intelligence within the banking sector. Employing a comprehensive methodology, the study emphasizes the crucial role of high-quality datasets in harnessing deep learning for improved decision-making. Results reveal the superior performance of CNN models over traditional algorithms, with CNN (VGG16) achieving an impressive accuracy rate of 90%. These findings underscore the potential of deep learning in extracting valuable insights from complex data, presenting a paradigm shift in optimizing various banking processes. The article concludes by highlighting the importance of investing in infrastructure and expertise for successful CNN integration, while also addressing ethical and privacy considerations. This research contributes to the evolving discourse on deep learning applications in organizational management, offering valuable insights for banks navigating the challenges of the global market.