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Fuzzy Relational Compositions Can Be Useful for Customers Credit Scoring in Financial Industry

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications (IPMU 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 855))

Abstract

Fuzzy relational compositions is an important topic in fuzzy mathematics and many researchers have applied that in various fields which the classification problem was more and less accounted for the significant part. Related to this problem, in this paper, we will show that fuzzy relational compositions assist in evaluating customers creditability (credit scoring) which is one of the most important problems in the financial industry. The purpose is to classify a given customer into two classes of accepted or rejected and to help loan officers to make a better decision. We will illustrate an experimental example with initial values provided by an bank expert and use LFL R-package as the practical tool to calculate the compositions for our application. The concept of so-called generalized quantifiers and excluding features incorporating in the compositions will be employed as well.

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Authors and Affiliations

  1. Centre of Excellence IT4Innovations, Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, 30. dubna 22, 701 03, Ostrava 1, Czech Republic

    Soheyla Mirshahi & Nhung Cao

Authors
  1. Soheyla Mirshahi
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  2. Nhung Cao
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Corresponding authors

Correspondence to Soheyla Mirshahi or Nhung Cao .

Editor information

Editors and Affiliations

  1. Universidad de Cádiz, Cádiz, Cadiz, Spain

    Jesús Medina

  2. Universidad de Málaga, Málaga, Málaga, Spain

    Manuel Ojeda-Aciego

  3. Universidad de Granada, Granada, Spain

    José Luis Verdegay

  4. Institute for Research and Applications, University of Ostrava, Ostrava, Czech Republic

    Irina Perfilieva

  5. LIP6, Université Pierre et Marie Curie, CNRS, Paris, France

    Bernadette Bouchon-Meunier

  6. Iona College, New Rochelle, New York, USA

    Ronald R. Yager

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Mirshahi, S., Cao, N. (2018). Fuzzy Relational Compositions Can Be Useful for Customers Credit Scoring in Financial Industry. In: Medina, J., Ojeda-Aciego, M., Verdegay, J., Perfilieva, I., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2018. Communications in Computer and Information Science, vol 855. Springer, Cham. https://doi.org/10.1007/978-3-319-91479-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-91479-4_3

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  • Print ISBN: 978-3-319-91478-7

  • Online ISBN: 978-3-319-91479-4

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