Trends and Patterns of Accumulation of Non-Performing Loans in the Banking Sector of Uzbekistan

Abstract

This article provides a comprehensive overview of the banking sector in Uzbekistan, with a particular focus on the trend and patterns of non-performing loans (NPLs) accumulation. The data in the article offer insights into the share of NPLs in total loans across banks over several periods, underscoring the importance of assessing asset quality and risk management practices of banks in order to support policy decisions and investment strategies. The analysis reveals that banks generally exhibit a slightly higher ratio of NPLs to total loans compared to the pre-pandemic period, highlighting the fluctuation of NPL ratios over time, particularly during the pandemic. Furthermore, it provides a breakdown of NPL accumulation by sector, indicating the industrial sector as the largest contributor to NPLs, followed by the agricultural sector. Especially, the mean of quarterly NPL ratios for Uzbek banks from 2017 to 2023 is discussed, revealing an increase in the NPL ratios in 2021 as compared to the previous year. The data in the article describe the relationship between quarterly outstanding loans and NPLs for banks over the same period. The analysis particularly focuses on NPL accumulation trends and sector-specific contributions, which are of significant concern. The study's findings are of paramount importance for stakeholders, policymakers, and investors, as they offer crucial insights into the credit risk, asset quality, and performance of banks in Uzbekistan.

Özbekistan Bankacılık Sektöründe Takipteki Kredilerin Birikim Eğilimleri ve Modelleri

Özet

Bu makale, özellikle takipteki kredi birikiminin meyil ve şekillerine odaklanarak, Özbekistan'daki bankacılık sektörüne kapsamlı bir genel bakış sunmaktadır. Makaledeki veriler, çeşitli dönemlerde bankalar arasında takipteki kredilerin, toplam krediler içindeki payına ilişkin içgörüler sunarak politika kararlarını ve yatırım stratejilerini desteklemek için bankaların varlık kalitesini ve risk yönetimi uygulamalarını değerlendirmenin öneminin altını çizmektedir. Analiz, bankalarda genel olarak pandemi öncesi döneme kıyasla takipteki kredilerin toplam kredilere oranının biraz daha yüksek olduğunu ortaya koymakta, ve özellikle pandemi sırasında takipteki kredi oranlarının zaman içindeki dalgalanmasına dikkat çekmektedir. Ayrıca makalede, takipteki kredi birikiminin sektörlere göre bir dağılımı sunulmakta, ve sanayi sektörünün takipteki kredilere en büyük katkıyı sağlayan sektör olduğu, bunu tarım sektörünün izlediği gösterilmektedir. Çalışmada özellikle, Özbek bankaları için 2017'den 2023'e kadar olan üç aylık takipteki kredi oranlarının ortalaması tartışılmakta, ve 2021'de bir önceki yıla göre takipteki kredi oranlarında bir artış olduğunu ortaya konmaktadır. Makaledeki veriler, aynı dönemde bankalar için üç aylık ödenmemiş krediler ile takipteki krediler arasındaki ilişkiyi açıklamaktadır. Analiz özellikle takipteki kredilerin birikme eğilimlerine ve sektöre özgü katkılara odaklanmaktadır. Çalışmanın bulgularının Özbekistan'daki bankaların kredi riski, varlık kalitesi ve performansı hakkında önemli bilgiler sunması dolayısıyla bu makale paydaşlar, politika yapıcılar ve yatırımcılar için büyük önem taşımaktadır.

Ph.D. candidate Jonibek Rustamov (Banking and Finance Academy, Tashkent, Uzbekistan)
0009-0006-6361-5987  paradise.enough.me@gmail.com

Submitted on: 2024-11-22 Accepted on: 2025-01-24

Year:2025 - Volume:4 Issue:1 Pages: 31-37

DOI: https://doi.org/10.36880/J04.1.0144

Download as PDF

APA style citation: Rustamov, J. (2025). Trends and Patterns of Accumulation of Non-Performing Loans in the Banking Sector of Uzbekistan. Journal of Eurasian Economies, 4(1), 31-37.

References

• Ari, A., Chen, S., & Ratnovski, L. (2021). The dynamics of non-performing loans during banking crises: A new database with post-COVID-19 implications. Journal of Banking & Finance, 133, 106140.
• Ari, M.A., Chen, S., & Ratnovski, M.L. (2019). The dynamics of non-performing loans during banking crises: a new database. International Monetary Fund. https://www.imf.org/en/Publications/WP/Issues/2019/12/06/The-Dynamics-of-Non-Performing-Loans-during-Banking-Crises-A-New-Database-48839
• Barr, R.S., & Siems, T. (1994). Predicting bank failure using DEA to quantify management quality. Federal Reserve Bank of Dallas, Financial Industry Studies Working Paper No. 1-94.
• Bending, T., Berndt, M., Betz, F., Brutscher, P., Nelvin, O., Revoltella, D., Slacik, T. & Wolski, M. (2014). Unlocking lending in Europe. Regional Studies and Roundtables. https://www.eib.org/attachments/efs/economic_report_unlocking_lending_in_europe_en.pdf
• Berg, S. A., Førsund, F. R., & Jansen, E. S. (1992). Malmquist indices of productivity growth during the deregulation of Norwegian banking, 1980-89. The Scandinavian Journal of Economics, 94, 211-228.
• Berger, A. N., & DeYoung, R. (1997). Problem loans and cost efficiency in commercial banks. Journal of banking & finance, 21(6), 849-870.
• DeYoung, R. (1997). X-efficiency and management quality in national banks. Journal of Financial Services Research, 15(2).
• Demirgüç-Kunt, A. (1989). Deposit-institution failures: a review of empirical literature. Economic Review, 25(4), 2-19.
• Hughes, J. P., & Mester, L. J. (1993). A quality and risk-adjusted cost function for banks: Evidence on the “too-big-to-fail” doctrine. Journal of productivity analysis, 4(3), 293-315.
• Keeton, W. R. (1999). Does faster loan growth lead to higher loan losses? Economic review-Federal reserve bank of Kansas City, 84(2), 57-75.
• Keeton, W. R., & Morris, C. S. (1987). Why do Banks’ Loan Losses Differ? Economic review, 72(5), 3-21.
• Klein, N. (2013). Non-Performing Loans in CESEE: Determinants and Impact on Macroeconomic Performance. IMF Working Paper 13/72. https://www.imf.org/external/pubs/ft/wp/2013/wp1372.pdf
• Kryzanowski, L., Liu, J., & Zhang, J. (2023). Effect of COVID-19 on non-performing loans in China. Finance Research Letters, 52, 103372.
• Kwan, S., & Eisenbeis, R. A. (1997). Bank risk, capitalization, and operating efficiency. Journal of Financial Services Research, 12(2), 117-131.
• Louzis, D.P., Vouldis, A.T., & Metaxas, V.L. (2012). Macroeconomic and bank-specific determinants of non-performing loans in Greece: A comparative study of mortgage, business and consumer loan portfolios. Journal of Banking & Finance, 36(4), 1012-1027.
• Marcucci, J., & Quagliariello, M. (2008). Is bank portfolio riskiness procyclical? Evidence from Italy using a vector autoregression. Journal of International Financial Markets, Institutions and Money, 18(1), 46-63.
• Meeker, L.G., & Gray, L. (1987). A note on non-performing loans as an indicator of asset quality. Journal of Banking & Finance, 11(1), 161-168.
• Mohaddes, K., Raissi, M., & Weber, A. (2017). Can Italy grow out of its NPL overhang? A panel threshold analysis. Economics Letters, 159, 185-189. https://www.imf.org/en/Publications/WP/Issues/2017/03/24/Can-Italy-Grow-Out-of-Its-NPL-Overhang-A-Panel-Threshold-Analysis-44761
• Resti, A. (1996). Linear programming and econometric methods for bank efficiency evaluation: An empirical comparison based on a panel of Italian banks (pp. 111-139). Physica-Verlag HD.
• Salas, V., & Saurina, J. (2002). Credit risk in two institutional regimes: Spanish commercial and savings banks. Journal of Financial Services Research, 22(3), 203-224.
• Sinkey Jr, J. F., & Greenawalt, M. B. (1991). Loan-loss experience and risk-taking behavior at large commercial banks. Journal of Financial Services Research, 5(1), 43-59.
• Whalen, G. (1991). A proportional hazards model of bank failure: an examination of its usefulness as an early warning tool. Economic Review, 27(1), 21-31.