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Visual Exploration and Analysis of Bank Performance Using Self Organizing Map

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Proceedings of the 8th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT’18), Vol.1 (SETIT 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 146))

Abstract

The visualization of high dimensional data has an important role to play as an artifact supporting exploratory data analysis. There is growing evidence of the effectiveness of information visualization as it provides help in understanding data, increases the level of cognitive functioning and performs pattern recognition. This paper deals with the usefulness of Self-Organizing Map (SOM) neural network in the area of the banking sector. We want to show how SOM can be useful to convert huge amounts of financial data into valuable information used to speed up the decision-making process and facilitate data analysis for deeper understanding

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Authors and Affiliations

  1. Research Center on Industry, The Institutions and The Economical Systems of Amiens (CRIISEA), University of Picardie Jules Verne, 10 Placette Lafleur, 80027, Amiens Cédex, France

    Mouna Kessentini & Esther Jeffers

Authors
  1. Mouna Kessentini
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  2. Esther Jeffers
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Corresponding authors

Correspondence to Mouna Kessentini or Esther Jeffers .

Editor information

Editors and Affiliations

  1. SETIT Lab, University of Sfax, Sfax, Tunisia

    Med Salim Bouhlel

  2. DIBRIS - University of Genoa, Genova, Genova, Italy

    Stefano Rovetta

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Kessentini, M., Jeffers, E. (2020). Visual Exploration and Analysis of Bank Performance Using Self Organizing Map. In: Bouhlel, M., Rovetta, S. (eds) Proceedings of the 8th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT’18), Vol.1. SETIT 2018. Smart Innovation, Systems and Technologies, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-030-21005-2_41

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