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2021, vol. 69, br. 1-2, str. 65-79
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Analiza sistemske komponente kreditnog rizika u bankarskom sektoru Republike Srbije
Analysis of the systemic credit risk component in the banking sector of the Republic of Serbia
Banca Intesa, Credit Division, Underwriting Sector for Large, Institutional and International Clients, Beograd
Sažetak
Predmet ovog istraživanja je ispitivanje i kvantifikovanje stepena izloženosti sistemskom riziku kreditnog portfelja bankarskog sektora Republike Srbije u periodu od 2008Q4 do 2019Q3, ali i po osnovnim komercijalnim segmentima (privreda i stanovništvo). Bazelski komitet za superviziju banaka, u sklopu regulatornog okvira za utvrđivanje potrebnog nivoa kapitala, pravi razliku u izloženosti sistemskom riziku između kredita odobrenih privredi i kredita odobrenih stanovništvu. Na osnovu navedenog, postavljaju se sledeće hipoteze: a) Postoji značajna razlika u izloženosti sistemskom riziku između kredita odobrenih privredi i kredita odobrenih stanovništvu u bankarskom sektoru Republike Srbije i b) Predikcija izloženosti sistemskom riziku celog bankarskog sektora Republike Srbije može se vršiti na osnovu kredita odobrenih privredi zbog sprecifičnosti ekonomskog i bankarskog sistema Republike Srbije. Rezultati istraživanja su potvrdili istinitost tvrdnje obe hipoteze, što ima višestruki značaj za kreatore makroekonomske politike, nosioce makroprudencijalne politike i nosioce upravljačke funkcije poslovnih banaka. Prvo, bankarska i računovodstvena regulativa zahtevaju izradu stres-testova verovatnoće neizmirenja obaveza dužnika na promenu makroekonomskih agregata i njen uticaj na kapital banke, uvažavajući procikličnost finansijskog sistema. Drugo, osetljivost banke na promene u makroekonomskim agregatima dominantno zavisi od strukture kreditnog portfolia po komercijalnim segmentima. Treće, potvrđen je zaključak akademske elite da bi razvoj tržišta kapitala doveo do povećanja finansijske i makroekonomske stabilnosti Republike Srbije i smanjio procikličnost kreditnog rizika. Korišćen je model autoregresionih distributivnih docnji, tzv. ARDL model (engl. autoregressive distributed lags model), jer postoji razlika u integrisanosti posmatranih vremenskih serija (I(0) i I(1)) i jer ovaj metod daje dobre rezultate na relativno malim uzorcima.
Abstract
The subject of this research paper is quantification of the degree of systemic risk exposure of the Serbian banking sector's loan portfolio in the period from 2008Q4 to 2019Q3, including by main commercial segments (corporate and retail). The Basel Committee on Banking Supervision, under its regulatory framework, makes a distinction between corporate and retail loans regarding the exposure to systemic risk. Based on the above, the following hypotheses are set: a) There is a significant difference in systemic risk exposure between corporate and retail loans in the Serbian banking sector and b) Forecasting the exposure to systemic risk of the entire Serbian banking sector can be performed on the basis of corporate loans due to the specificity of the economic system of the Republic of Serbia. The results of the research corroborated the truthfulness of both hypotheses, which has a multifold significance for commercial banks' management, macroeconomic and macroprudential policy makers. First, banking and accounting regulations require stress-testing of probability of default on the change in macroeconomic aggregates and its impact on the bank's capital. Second, a bank's sensitivity to changes in macroeconomic aggregates predominantly depends on the loan portfolio structure by commercial segments. Third, the conclusion of the academic elite that the development of the capital market would lead to an increase in the macroeconomic stability of the Republic of Serbia and reduce the procyclicality of credit risk was confirmed. We used the autoregressive distributed lags model (ARDL model) because there is a difference in order of integration in the observed time series (I(0) and I(1)), and because this method provides good results for relatively small sample data sizes.
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