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Research Article

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

Authors

  • Md Abu Sufian Mozumder College of Business, Westcliff University, Irvine, California, USA
  • Md Murshid Reja Sweet Department of Management Science and Quantitative Methods, Gannon University, USA
  • Norun Nabi Department of Information Technology, Washington University of Science and Technology, Alexandria, Virginia, USA
  • Mazharul Islam Tusher Department of Computer Science, Monroe College, New Rochelle, New York, USA
  • Chinmoy Modak Information Technology, Craven Community College, USA
  • Mehedi Hasan Master of Science, Management- Business Analytics, St. Francis College, USA
  • Mohammed Nazmul Islam Miah Department of Management Science and Quantitative Methods, Gannon University, USA
  • Ayon Mazumder Master of Information Technology, Gannon University, Erie, Pennsylvania, USA
  • Syeda Farjana Farabi Doctor of Business Administration, Westcliff University, Irvine, California
  • Mani Prabha Department of Business Administration, International American University, Los Angeles, California

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.

Article information

Journal

Journal of Business and Management Studies

Volume (Issue)

6 (3)

Pages

111-118

Published

2024-05-23

How to Cite

Md Abu Sufian Mozumder, Md Murshid Reja Sweet, Norun Nabi, Mazharul Islam Tusher, Chinmoy Modak, Mehedi Hasan, Mohammed Nazmul Islam Miah, Ayon Mazumder, Syeda Farjana Farabi, & Mani Prabha. (2024). Revolutionizing Organizational Decision-Making for Banking Sector: A Machine Learning Approach with CNNs in Business Intelligence and Management. Journal of Business and Management Studies, 6(3), 111-118. https://doi.org/10.32996/jbms.2024.6.3.12

References

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Keywords:

Organizational Decision-Making; Banking Sector; Machine Learning Approach; Business Intelligence and Management