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Comparison Between Neural Network, Genetic Algorithm and Logit Models in Evaluating Consumer Credit Risk

Author

Listed:
  • Tari, Fethullah

    (Allame Tabatabaei University)

  • Ebrahimi, seyed Ahmad

    (Researcher at National Research Institute For Science Policy)

  • Mousavi, Seyed Jafar

    (Entrepreneurship Education)

  • Kalantari, Mahmoud

    (Iran University of Economic Science)

Abstract

The purpose of this study is to assess the credit rating methods of real customers (micro-credit recipients) of banks, by reviewing the financial records and characteristics of the applicant's characteristics. In this research, the effectiveness of some methods (logit model, neural network, and genetic algorithm) is evaluated for accurate measurement

Suggested Citation

  • Tari, Fethullah & Ebrahimi, seyed Ahmad & Mousavi, Seyed Jafar & Kalantari, Mahmoud, 2018. "Comparison Between Neural Network, Genetic Algorithm and Logit Models in Evaluating Consumer Credit Risk," Journal of Monetary and Banking Research (فصلنامه پژوهش‌های پولی-بانکی), Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 10(34), pages 680-657, January.
    • Handle: RePEc:mbr:jmbres:v:10:y:2018:i:34:p:680-657
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