Investigation of the scoring model for bank borrowers


  • Volodymyr Zubchenko Taras Shevchenko National University of Kyiv
  • A. V. Avramenko Taras Shevchenko National University of Kyiv



credit scoring, creditworthiness, solvency, creditworthiness assessment, borrowers, scoring card, classification of features, creation methods, machine learning, model testing


In the paper we investigate scoring models as a tool for credit risk management, their importance, types, features and applications. We consider the history of scoring models and the development of the modern concepts of creditworthiness and scoring, examine scoring types and their features, methods (logistic regression, decision trees, linear programming, decision trees, and others), strengths and weaknesses of each considered method and stages of building scoring models; we stress the importance of scoring cards for building scoring models, indicate the main quantitative and qualitative features, their classification used for and describe the procedure of creating scoring cards. In the paper we consider the factors needed to be considered for more effective scoring model building process; we indicate the main formulas used to assess the creditworthiness of borrowers and improve the accuracy of scoring models, including Population Stability Index (PSI), R-Square Coefficient, Kolmogorov-Smirnov Coefficient, GINI Coefficient, and others; the practical application of scoring models in banks of Ukraine and their steps after applying scoring models are described on the example of a typical borrower.

Pages of the article in the issue: 44 - 53

Language of the article: Ukrainian


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How to Cite

Zubchenko, V., & Avramenko, A. V. (2023). Investigation of the scoring model for bank borrowers. Bulletin of Taras Shevchenko National University of Kyiv. Physical and Mathematical Sciences, (2), 44–53.



Algebra, Geometry and Probability Theory

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