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Corporate Credit Risk Modelling in the Supervisory Stress Test of the Magyar Nemzeti Bank

Author

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  • Gergõ Horváth

    (Magyar Nemzeti Bank)

Abstract
As a regulatory and decision-supporting tool, the stress test framework plays an important role in assessing the vulnerability of the domestic financial system and the individual institutions. Consequently, continuous development of the models used in parameter estimation is of crucial importance. This study aims to improve credit risk loss estimation, which is one of the most important components of the supervisory stress test framework, by making the estimation of corporate default and transition probability more accurate. The study is based on a client-level default database, which contains various actors in the Hungarian banking sector and covers an entire economic cycle (2007-2017). It is unique as it introduces a uniform stage classification rule for determining the transition probabilities which attempts to create harmony with domestic institutions' loan loss provision policies under IFRS 9. Based on the research findings, it can be concluded that - relying on a wide-ranging set of macroeconomic and client-level variables - it is possible to separate corporate debtors with adequate discriminatory power as well as to estimate point-in-time probability of default (PIT PD) and transition probabilities at the corporate level relevant in terms of the stress test, and thus to approximate the loan loss provisioning requirement arising in a stress situation. Of the factors capturing the cyclical nature of corporate default probability, the state of the labour market and the income position of the household sector were identified as the main determinants by the study.

Suggested Citation

  • Gergõ Horváth, 2021. "Corporate Credit Risk Modelling in the Supervisory Stress Test of the Magyar Nemzeti Bank," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 20(1), pages 43-73.
    • Handle: RePEc:mnb:finrev:v:20:y:2021:i:1:p:43-73
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    References listed on IDEAS

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    1. György Inzelt & Gábor Szappanos & Zsolt Armai, 2016. "Supervision by robust risk monitoring – a cycle-independent Hungarian corporate credit rating system," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 15(3), pages 51-78.
    2. Péter Bauer & Marianna Endrész, 2016. "Modelling Bankruptcy Using Hungarian Firm-Level Data," MNB Occasional Papers 2016/122, Magyar Nemzeti Bank (Central Bank of Hungary).
    3. Budnik, Katarzyna & Balatti, Mirco & Dimitrov, Ivan & Groß, Johannes & Hansen, Ib & Kleemann, Michael & Sanna, Francesco & Sarychev, Andrei & Siņenko, Nadežda & Volk, Matjaz & Covi, Giovanni & di Iasi, 2019. "Macroprudential stress test of the euro area banking system," Occasional Paper Series 226, European Central Bank.
    4. Anderson, Raymond, 2007. "The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation," OUP Catalogue, Oxford University Press, number 9780199226405.
    5. Márk Szenes & Zsófia Dabi, 2020. "Modelling Corporate Probability of Default – A Possible Supervisory Benchmark Model," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 19(3), pages 52-77.
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    Cited by:

    1. Balint Vargedo, 2022. "Climate Stress Test: The Impact of Carbon Price Shock on the Probability of Default in the Hungarian Banking System," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 21(4), pages 57-82.

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    More about this item

    Keywords

    stress test; credit risk; PD; bank; corporate loans; forecast;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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