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The Relationship Between the Financial Performance of Banks and the Quality of Credit Scoring Models

Author

Listed:
  • Roman Tikhonov

    (Sberbank)

  • Aleksey Masyutin

    (Sberbank)

  • Vadim Anpilogov

    (Sberbank)

Abstract

Model risk in credit scoring can be understood as the bank’s losses associated with a model quality deterioration. Deterioration in model quality entails an incorrect assessment of the creditworthiness of borrowers and leads to an increase in potentially defaulting applications in the loan portfolio, as the bank relies on the model performance when making lending decisions. The relationship between model quality and financial performance is embedded in the confusion matrix, where the value of a type I error indicates the bank’s lost profit, and the value of a type II error is equivalent to losses in the event of a default. We propose estimating model risk based on the scenario forecast of model quality or the ranking ability of the Gini model over a given time interval. The result of the analysis is the assessment of the bank’s net present value for the current and modified models, depending on the approval level. The proposed approach allows us to solve the problem of the optimal choice of a Gini model and answer the question of how model quality affects financial performance.

Suggested Citation

  • Roman Tikhonov & Aleksey Masyutin & Vadim Anpilogov, 2021. "The Relationship Between the Financial Performance of Banks and the Quality of Credit Scoring Models," Russian Journal of Money and Finance, Bank of Russia, vol. 80(2), pages 76-95, June.
  • Handle: RePEc:bkr:journl:v:80:y:2021:i:2:p:76-95
    DOI: 10.31477/rjmf.202102.76
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    References listed on IDEAS

    as
    1. Fortunato Pesarin & Luigi Salmaso, 2010. "The permutation testing approach: a review," Statistica, Department of Statistics, University of Bologna, vol. 70(4), pages 481-509.
    2. Valeriane Jokhadze & Wolfgang M. Schmidt, 2020. "Measuring Model Risk In Financial Risk Management And Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 1-37, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Henry Penikas, 2023. "Unaccounted model risk for Basel IRB models deemed acceptable by conventional validation criteria," Risk Management, Palgrave Macmillan, vol. 25(4), pages 1-25, December.
    2. Henry Penikas, 2022. "Model Risk for Acceptable, but Imperfect, Discrimination and Calibration in Basel PD and LGD Models," Bank of Russia Working Paper Series wps92, Bank of Russia.

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    More about this item

    Keywords

    model risk; quantitative estimation; bank risk management; credit scoring; machine learning; model; model quality;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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