Assessing the resistance of the bank`s industrial loan portfolio to the effects of the dynamic macroeconomic environment

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Ivan Franko National University of Lviv

ASSESSING THE RESISTANCE OF THE BANK'S INDUSTRIAL LOAN PORTFOLIO TO THE EFFECTS OF THE DYNAMIC MACROECONOMIC ENVIRONMENT

Herasymenko Alina

PhD Student

Annotation

loan portfolio bank macroeconomic

The purpose of the study is to develop scientific and methodological foundations for improving the efficiency of the process of managing a bank's corporate loan portfolio, in particular by segregating the industrial loan portfolio as its important structural part and developing a methodical approach to assessing the resistance of the bank's industrial loan portfolio to the effects of the dynamic macroeconomic environment. The article summarizes the results of research by domestic and foreign scholars on the impact of macroeconomic factors on various aspects of a bank's lending activities. The paper briefly considers certain aspects of development and efficiency of bank lending to industrial enterprises for the period 2010-2022. The author's approach to assessing the resistance of the bank's industrial loan portfolio to fluctuations in the macroeconomic environment is proposed. The proposed methodology for assessing the resistance of the foreign currency industrial loan portfolio of Ukrainian banks to effects of the macroeconomic environment for the period 2010-2022 has been tested.

Key words: bank, industrial enterprise, bank lending to industrial enterprises, industrial loan portfolio of the bank, resistance, macroeconomic environment, macroeconomic factors.

Анотація

ОЦІНКА СТІЙКОСТІ ПРОМИСЛОВОГО КРЕДИТНОГО ПОРТФЕЛЯ БАНКУ ДО ПРОЯВІВ МАКРОЕКОНОМІЧНОГО СЕРЕДОВИЩА

Герасименко Аліна Львівський національний університет імені Івана Франка

Метою дослідження є розвиток науково-методичних засад щодо підвищення ефективності процесу управт ління корпоративним кредитним портфелем банку, зокрема шляхом виокремлення промислового кредитного < портфеля як його важливої структурної частини та розвитку методичного підходу до оцінки стійкості про> мислового кредитного портфеля банку до проявів динамічного макроекономічного середовища. Узагальнено X результати досліджень вітчизняних та зарубіжних науковців щодо впливу макроекономічних чинників на різні Ј аспекти кредитної діяльності банку: зокрема, на ефективність банківського кредитування, на рівень процентІ-- них ставок кредитування, на рівень непрацюючих кредитів, на рівень кредитного ризику тощо. Стисло розглянуто окремі аспекти розвитку та ефективності банківського кредитування промислових підприємств за період 2010-2022 рр. Запропоновано авторський підхід до оцінки стійкості промислового кредитного портфеля банку до коливань макроекономічного середовища. Апробовано запропоновану методику для проведення оо оцінки стійкості валютного промислового кредитного портфеля банків України до проявів макроекономічного середовища за період 2010-2022 р. В якості ключових економічних чинників макроекономічного середовис ща було прийнято: курс долара США; обсяг ВВП (млрд. грн.); індекс споживчих цін (%); рівень безробітО тя (%); зведений бюджет фальдо) у % до ВВП; зведений платіжний баланс (млрд. дол.). В якості проявів < макроекономічного середовища в зазначений період аналізу визначено такі епізоди макроекономічних потрясінь: фінансово-економічна криза 2013-2014 рр.; пандемія COVID-19; повномасштабна війна в Україні, з о 24.02.2022 р. З'ясовано, які макроекономічні чинники здійснювали визначальний вплив на обсяг валютного (5 банківського кредитування промислових підприємств. Обчислено прогнозні значення обсягу валютного кредитування промислових підприємств та частки непрацюючих валютних кредитів промислових підприємств на період 2023-2025 рр. Здійснено висновки про перспективні напрямки поглиблення та розвитку науково-метоlo дичних засад щодо управління промисловим кредитним портфелем банку.

Ключові слова: банк, промислове підприємство, банківське кредитування промислових підприємств, о промисловий кредитний портфель банку, стійкість, макроекономічне середовище, макроекономічні чинники.

Introduction

In recent years, the situation around the development of bank lending to industrial enterprises in Ukraine has become more challenging: banks are making significant efforts to reduce the share of non-performing loans of industrial enterprises; the cost of lending to industrial enterprises is higher than for other non-financial corporations; industrial enterprises are going bankrupt and suffering significant material losses as a result of the war. At the same time, given the significant fluctuations in Ukraine's macroeconomic environment, the issue of its impact on bank lending to industrial enterprises is becoming relevant, and, accordingly, there is a need to develop effective monitoring tools to assess the resistance of the bank's industrial loan portfolio to the effects of the macroeconomic environment.

Analysis of recent researches and publications

The theoretical and methodological foundations and practical aspects of the impact of the macroeconomic environment on the lending activities of banks are the focus of scientific interest for many scholars and practitioners. Thus, the impact of macroeconomic factors on the lending activities of banks was studied by L. Smaha and O. Hnativ. [9] In particular, the scientists identified the most sensitive areas of lending activity that undergo significant transformations in the face of changes in the macroeconomic environment, namely: the share of long-term loans in the loan portfolios of banks; the level of liberalization of lending conditions; the level of sectoral concentration of loan portfolios of banks. The impact of a number of macroeconomic factors on the cost of bank loans in Ukraine was studied by S. Ivakhnenkov, S. Glushchenko, and K. Sverenko [3]. The researchers concluded that interest rates on loans are most influenced by inflation and the ease of doing business and least influenced by GDP per capita and the share of loans in GDP. D. Odnorog [4] studied the impact of macroeconomic factors on the efficiency of commercial bank loans on the example of HFC Bank of Ghana and concluded that the determining influence of inflation and Treasury bond rates on the efficiency of bank lending is crucial. Another group of researchers, including S. Ahmed, M. Ejaz, E. Thalassinos and J. Thalassinos, studied the impact of macroeconomic factors on the level of NPLs of banks in Pakistan. The researchers concluded that any increase in GDP is vital for reducing NPLs, while higher interest rates and exchange rates increase NPLs [1]. Similar results regarding the impact of macroeconomic factors on the level of NPLs were obtained by M. Foglia. Using the example of the Italian banking system, the researcher found that GDP and public debt have the greatest impact on the level of NPLs [2].

Identification of previously unresolved parts of the general problem

Paying tribute to and appreciating the contribution of scholars to the development of the issue of the impact of the macroeconomic environment on the lending activities of banks, we believe that certain issues have not yet been highlighted. In particular, it is necessary to highlight the peculiarities of the macroeconomic environment's influence on the development of bank lending to industrial enterprises as the basis of the real sector of the economy. In this segment of the study, it is important to develop methods for assessing the resistance of the bank's industrial loan portfolio to the effects of the dynamic macroeconomic environment.

Formulation of the article's objectives

The purpose of the study is to develop a method for assessing the resistance of the bank's industrial loan portfolio to the effects of the dynamic macroeconomic environment.

Summary of the main research material

Industrial loans account for a significant share of the total bank loan portfolio of non-financial corporations. Over the past ten years, bank loans of industrial enterprises have, on average, accounted for at least one third of the corporate loan portfolio of Ukrainian banks, with a ratio of industrial loans to industrial deposits of more than 290% (Figure 1).

At the same time, foreign currency bank loans of industrial enterprises accounted for about half of the foreign currency corporate loan portfolio of banks. On average, during the period 2014-2022, non-performing loans accounted for a 1/3 of the total volume of industrial enterprise loans. The share of foreign currency nonperforming loans in the total amount of foreign currency industrial loans, on average, for the same period was no less than 40%. It should also be noted that the share of bank lending to industrial enterprises in the gross added value of industrial enterprises of Ukraine averaged no more than 51% for the period 2009-2022 and had a steady downward trend [6].

Given the above, it can be pointed out that there is no properly developed methodical approach to assessing the resistance of the bank's industrial loan portfolio to the effects of the dynamic macroeconomic environment.

The development of a methodical approach to assessing the resistance of a bank's industrial loan portfolio to the effects of macroeconomic environment is primarily aimed at improving the decision-making process of banks in lending to industrial enterprises in a dynamic macroeconomic environment.

Figure 1 Dynamics of specific indicators of efficiency of bank lending to industrial enterprises in Ukraine, % (2009-2022)

Source: compiled by the author on the basis of [6]

A methodical approach to assessing the resistance of a bank's industrial loan portfolio should be considered as an important component of the process of monitoring the bank's overall corporate portfolio, as the results of such an assessment provide the bank's management with an important information and analytical resource on the impact of specific economic factors of the macroeconomic environment on the quality and resistance of the industrial loan portfolio.

We propose to assess the resistance of the bank's industrial loan portfolio to the effects of macroeconomic environment using the method based on the application of mathematical and economic modeling according to the following algorithm:

1. Consideration of a multiple linear regression equation of the following form [8]:

2. Developing the working equation, taking into account that Y - this is the volume of loans of industrial enterprises (monetary units), explanatory variables x1,..x_m - macroeconomic indicators. The macroeconomic indicators included in the equation should have significant correlations with the outcome variable Y and have available forecast values. As a general rule, the forecast values of key macroeconomic indicators are published on the official website of the Central Bank or on the official website of the relevant ministry. To perform macro-stress testing, the working equation incorporates dummy factors that correspond to periods of financial and economic shocks (crises) that are considered to be macroeconomic effects and/or shocks. Thus, the working equation of a multiple linear regression with dummy variables is as follows:

3. Assessment of the statistical significance of the equation: the significance level F should be less than 0.05 (1-0.95); p-values for the calculated coefficients p1...p_g should be less than 0.05 (1-0.95); the value of R should be close to "1". When calculating the predicted value of Y, p-values can be ignored.

4. Based on the calculated coefficients p„ for the relevant explanatory variables -x1,..x_m, and the dummy explanatory variables - F_n, calculate the forecast value of the output variable for the relevant forecast period using the formula:

The input data for the construction and estimation of a multiple linear regression with dummy variables are summarized in Table 1.

Table 1

Input Data for Multiple Linear Regression

Note: *forecast values

Source: compiled by the author on the basis of [5-7]

Figure 2 Regression statistics of the multiple linear regression equation Source: computed by the author in EViews

Assessing the results of the constructed multiple linear regression equation (Fig. 2), it should be noted that this equation is statistically significant (F-statistic 0.025 < 0.05) and describes the influence of explanatory variables on the output variable by 91%. The influence of dummy variables did not show statistical significance, and their values will be used to calculate the predicted value of Y.

Based on the results of the constructed model of multiple linear regression with dummy variables, in order to assess the resistance of the foreign currency industrial loan portfolio of Ukrainian banks to fluctuations in the macroeconomic environment during 2010-2022, it is found that:

- the impact of the dummy variables included in the regression equation, which denote macroeconomic fluctuations, is not statistically significant, so macroeconomic fluctuations were not the determining factors in the volume of foreign currency loans of industrial enterprises;

- the key macroeconomic factor that influenced the volume of foreign currency loans of industrial enterprises in 2010-2022 was the USD exchange rate;

- based on the calculated coefficients of the regression equation and forecast indicators of macroeconomic development, the forecast value of foreign currency lending to industrial enterprises was obtained: an increase of UAH 7.034 billion in 2023, UAH 2.37 billion in 2024, and UAH 75.45 billion in 2025;

- additional calculation of the predicted share of non-performing loans in the total volume of foreign currency loans of industrial enterprises yielded the following results: an increase in the share of non-performing foreign currency loans to 62.48% in 2023, to 70% in 2024, and even to 80% in 2025.

In view of the above, we believe that foreign currency lending to industrial enterprises in future periods should be guided by a conservative credit policy. We support these considerations with the fact that over the period 2010-2022, the share of non-performing foreign currency loans in the total volume of foreign currency loans of industrial enterprises averaged 32%, and during periods of macroeconomic fluctuations and shocks - 45% (starting after the 2013-2014 crisis and before the outbreak of a full-scale war in Ukraine in 2022) [6]. In addition, given the level of dollarization of Ukraine's economy and the geopolitical and military conflicts that are spreading around the world, the scenario of an appreciation of the USD against UAH may become even more pessimistic for Ukraine, and thus trigger a high level of risk of foreign currency lending to industrial enterprises.

Figure 3 Dynamics of factual and predicted values of foreign currency loans of industrial enterprises and key macroeconomic indicators (2010-2025)

Source: compiled by the author on the basis of [5-7]

Conclusions

Thus, we can conclude that it is important and necessary to develop specifically targeted tools for analyzing and assessing individual components of the bank loan portfolio of non-financial corporations. We believe that the dichotomy of the bank's loan portfolio into retail and corporate loan portfolios needs to be revised. Given that the loan portfolio of nonfinancial corporations consists of loans directed to industries that are interrelated and constitute a separate sector of the economy, we believe that this pool of loans should be segregated for the purpose of in-depth analysis and assessment. Given the sizeable share of industrial loans in the loan portfolio of non-financial corporations and their low quality, an individual approach to analyzing and assessing the pool of industrial loans seems to be rational. The paper proposes the author's approach to assessing the resistance of the bank's industrial loan portfolio to fluctuations in the macroeconomic environment. The proposed methodology has been adapted to assess the resistance of the foreign currency industrial loan portfolio of Ukrainian banks to fluctuations in the macroeconomic environment in 2010-2022, and it has been found that the determining macroeconomic factor that disrupted the resistance of the foreign currency industrial loan portfolio of Ukrainian banks was the USD exchange rate.

We believe that a promising field of research is the development of scientific and methodological foundations for assessing the overall quality of the industrial loan portfolio of banks.

References

1. Ahmed, S.; Majeed, M. Ejaz; Thalassinos, E.; Thalassinos, Y (2021) The impact of bank specific and macro-economic factors on non-performing loans in the banking sector: Evidence from an emerging economy. Journal of Risk and Financial Management, Vol. 14, Iss. 5, 1-14. DOI: https://doi.org/10.3390/jrfm14050217

2. Foglia, M. (2022) Non-Performing Loans and Macroeconomics Factor: The Italian Case. Risks, 10, 21. DOI: https://doi.org/10.3390/risks10010021

3. Ivakhnenkov, S., Hlushchenko, S. & Sverenko, K. (2020) Macroeconomic factors that influence the bank loans rate in international and Ukrainian practice. Economics of Development, 19(4), 35-47. DOI: https://doi.org/10.21511/ ed.19(4).2020.04

4. Odnoroh, D. (2019) Makroekonomichni faktory ta efektyvnist kredytiv komertsiinykh bankiv u Hani [Macroeconomic factors and the effectiveness of commercial bank lending in Ghana]. Naukovyi zhurnal «A'OHOX. Mystetstvo naukovoi dumky» - Scientific journal «ЛОГОХ. The Art of Scientific Thought», 3, 32-36. Available at: https://www.researchgate.net/publication/308044960_Bank-Speciflc_and_Macroeconomic_Determinants_of_Commercial_Banks_Profitability_in_Ghana (in Ukrainian)

5. Official website of the National Bank of Ukraine. Available at: https://bank.gov.ua/

6. Official website of the State Statistics Service of Ukraine. Available at: http://www.ukrstat.gov.ua

7. Official website of the Independent Association of the Banks of Ukraine (IABU) Available at: https://nabu.ua/ua

8. Rohalskyi, F (2001) Matematycheskye metody analyza ekonomycheskykh system [Mathematical methods of analysing economic systems]. Kyiv: “Scientific thought”, 422 p.

9. Smaha, L. & Hnativ, O. (2007) Vplyv makroekonomichnykh chynnykiv na kredytnu diialnist bankiv [Influence of macroeconomic factors on credit activity of banks]. Problemy i perspektyvy rozvytku bankivskoi systemy Ukrainy: zbirnyk naukovykh prats - Problems and prospects of development of the banking system of Ukraine: a collection of scientific papers. Sumy: UABS NBU. Available at: https://essuir.sumdu.edu.ua/bitstream-download/123456789/53883/5/Smaha_economic_crisis.pdf;jsessionid=733FE4F3E2ABF84F7D7BD8CFC7E06351 (in Ukrainian)

Список використаних джерел

1. Ahmed, S.; Majeed, M. Ejaz; Thalassinos, E.; Thalassinos, Y. The impact of bank specific and macro-economic factors on non-performing loans in the banking sector: Evidence from an emerging economy. Journal of Risk and Financial Management. 2021. Vol. 14. Iss. 5. 1-14. DOI: https://doi.org/10.3390/jrfm14050217

2. Foglia, M.. Non-Performing Loans and Macroeconomics Factor: The Italian Case. Risks. 2022. 10, 21. DOI: https://doi.org/10.3390/risks10010021

3. Ivakhnenkov, S., Hlushchenko, S. and Sverenko, K. Macroeconomic factors that influence the bank loans rate in international and Ukrainian practice. Economics of Development. 2020. 19(4). 35-47. DOI: 10.21511/ ed.19(4).2020.04

4. Однорог Д. А. Макроекономічні фактори та ефективність кредитів комерційних банків у Гані. Науковий журнал «Л'ОГОХ. Мистецтво наукової думки». 2019. № 3. C. 32-36. URL: https://www.researchgate.net/ publication/308044960_Bank-Specific_and_Macroeconomic_Determinants_of_Commercial_Banks_Profitability_ in_Ghana

5. Державна служба статистики України. URL: http://www.ukrstat.gov.ua

6. Національний банк України. URL: https://bank.gov.ua/ua/

7. Незалежна асоціація банків України. URL: https://nabu.ua/

8. Рогальський Ф. Математические методы анализа экономических систем. Київ: «Наукова думка», 2001. 422 с.

9. Смага Л. М., Гнатів О. А. Вплив макроекономічних чинників на кредитну діяльність банків. Проблеми і перспективи розвитку банківської системи України: збірник наукових праць. Суми: УАБС НБУ, 2007. URL: https://essuir.sumdu.edu.ua/bitstream-download/123456789/53883/5/Smaha_economic_crisis.pdf;jsessionid=733FE4F3E2ABF84F7D7BD8CFC7E06351

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