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Fuzzy Logic Model of Soft Data Analysis for Corporate Client Credit Risk Assessment in Commercial Banking

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  • Brkic, Sabina
  • Hodzic, Migdat
  • Dzanic, Enis

Abstract

This paper deals with the use of fuzzy logic as a support tool for evaluation of corporate client credit risk in a commercial banking environment. It defines possibilistic distribution of soft data used for corporate client credit risk assessment by applying fuzzy logic modeling, with a major goal to develop a new expert decisionmaking fuzzy model for evaluating credit risk of corporate clients in a bank. Currently, predicting a credit risk of companies is inaccurate and ambiguous, as well as affected by many internal and external factors that cannot be precisely defined. Unlike traditional methods for credit risk assessment, fuzzy logic can easily incorporate linguistic terms and expert opinions which makes it more adapted to cases with insufficient and imprecise hard data, as well as for modeling risks that are not fully understood. Fuzzy model of soft data, presented in this paper, is created based on expert experience of corporate lending of a commercial bank in Bosnia and Herzegovina. This market is very small and it behaves irrationally and often erratically and therefore makes the risk assessment and management decision making process very complex and uncertain which requires new methods for risk modeling to be evaluated. Experts were interviewed about the types of soft variables used for credit risk assessment of corporate clients, as well as for providing the inputs for generating membership functions of these soft variables. All identified soft variables can be grouped into following segments: stability, capability and readiness/willingness of the client to repay a loan. The results of this work represent a new approach for soft data usage/assessment with an aim of being incorporated into a new and superior soft-hard data fusion model for client credit risk assessment.

Suggested Citation

  • Brkic, Sabina & Hodzic, Migdat & Dzanic, Enis, 2017. "Fuzzy Logic Model of Soft Data Analysis for Corporate Client Credit Risk Assessment in Commercial Banking," MPRA Paper 83028, University Library of Munich, Germany, revised Nov 2017.
  • Handle: RePEc:pra:mprapa:83028
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    File URL: https://mpra.ub.uni-muenchen.de/83028/1/MPRA_paper_83028.pdf
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    References listed on IDEAS

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    1. Bennett, Joanna C. & Bohoris, George A. & Aspinwall, Elaine M. & Hall, Richard C., 1996. "Risk analysis techniques and their application to software development," European Journal of Operational Research, Elsevier, vol. 95(3), pages 467-475, December.
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    Cited by:

    1. Bogdan Włodarczyk & Marek Szturo & George Ionescu & Daniela Firoiu & Ramona Pirvu & Roxana Badircea, 2018. "The impact of credit availability on small and medium companies," Post-Print hal-01773998, HAL.
    2. Waseem Ahmed Abbasi & Zongrun Wang & Yanju Zhou & Shahzad Hassan, 2019. "Research on measurement of supply chain finance credit risk based on Internet of Things," International Journal of Distributed Sensor Networks, , vol. 15(9), pages 15501477198, September.
    3. Brkic, Sabina & Hodzic, Migdat & Dzanic, Enis, 2018. "Soft Data Modeling via Type 2 Fuzzy Distributions for Corporate Credit Risk Assessment in Commercial Banking," MPRA Paper 87652, University Library of Munich, Germany.
    4. Bogdan Włodarczyk & Marek Szturo & George H. Ionescu & Daniela Firoiu & Ramona Pirvu & Roxana Badircea, 2018. "The impact of credit availability on small and medium companies," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 5(3), pages 565-580, March.

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    More about this item

    Keywords

    fuzzy logic; credit risk; default risk; commercial banking;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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