<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">esp</journal-id><journal-title-group><journal-title xml:lang="ru">Economy: strategy and practice</journal-title><trans-title-group xml:lang="en"><trans-title>Economy: strategy and practice</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1997-9967</issn><issn pub-type="epub">2663-550X</issn><publisher><publisher-name>Институт экономики</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.51176/1997-9967-2026-1-65-78</article-id><article-id custom-type="elpub" pub-id-type="custom">esp-1839</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>МЕНЕДЖМЕНТ И МАРКЕТИНГ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>MANAGEMENT AND MARKETING</subject></subj-group></article-categories><title-group><article-title>Проектный подход к управлению проблемными  ипотечными кредитами: сравнительный анализ  Европы и Азии</article-title><trans-title-group xml:lang="en"><trans-title>A Project-Based Approach to Managing Non-Performing  Mortgage Loans: Evidence from Europe and Asia</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0003-8955-7840</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Мухамедов</surname><given-names>Ж. Ш.</given-names></name><name name-style="western" xml:lang="en"><surname>Mukhamedov</surname><given-names>J. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Мухамедов Ж.Ш. – PhD докторант</p><p>про. Аль-Фараби 71, Алматы</p></bio><bio xml:lang="en"><p>Javokhir S. Mukhamedov – PhD candidate</p><p>Almaty</p></bio><email xlink:type="simple">javokhir.mukhamedov@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4825-1189</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Сокира</surname><given-names>Т. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Sokira</surname><given-names>T. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Сокира Т.С. – к.э.н., доцент </p><p>про. Аль-Фараби 71, Алматы</p></bio><bio xml:lang="en"><p>Tatyana S. Sokira – Cand. Sc. (Econ.), Associate Professor</p><p>Almaty</p></bio><email xlink:type="simple">t_sokira@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6367-2192</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кулдашева</surname><given-names>З.</given-names></name><name name-style="western" xml:lang="en"><surname>Kuldasheva</surname><given-names>Z.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Кулдашева З. – д.э.н., доцент </p><p>ул. Ислама Каримова 49, Ташкент</p></bio><bio xml:lang="en"><p>Zebo Kuldasheva – Doc. Sc. (Econ.), Associate Professor</p><p>Tashkent</p></bio><email xlink:type="simple">z.kuldasheva@tsue.uz</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Казахский национальный университет им. аль-Фараби<country>Казахстан</country></aff><aff xml:lang="en">Al‑Farabi Kazakh National University<country>Kazakhstan</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru">Ташкентский государственный экономический университет<country>Узбекистан</country></aff><aff xml:lang="en">Tashkent State University of Economics<country>Uzbekistan</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>05</day><month>04</month><year>2026</year></pub-date><volume>21</volume><issue>1</issue><fpage>65</fpage><lpage>78</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Мухамедов Ж.Ш., Сокира Т.С., Кулдашева З., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Мухамедов Ж.Ш., Сокира Т.С., Кулдашева З.</copyright-holder><copyright-holder xml:lang="en">Mukhamedov J.S., Sokira T.S., Kuldasheva Z.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://esp.ieconom.kz/jour/article/view/1839">https://esp.ieconom.kz/jour/article/view/1839</self-uri><abstract><p>В условиях усиления макроэкономической нестабильности и роста кредитных рисков особую актуальность приобретает анализ факторов формирования проблемных ипотечных кредитов в банковской системе. Данное исследование направлено на разработку и предложение концептуальной проектной модели управления проблемной задолженностью (NPL), которая рассматривает управление проблемными ипотечными кредитами как интегрированный проектный цикл. Методологическую основу исследования составляют методы описательной статистики, корреляционного анализа и множественного регрессионного моделирования. Эмпирическую базу исследования составляют данные, собранные из Бюро национальной статистики и Национального банка Республики Казахстан за период 2020–2024 гг., включая показатели доходов населения, валового внутреннего продукта, уровня инфляции, процентных ставок, объема депозитов и просроченной задолженности. Результаты анализа показывают, что средний уровень проблемных кредитов в Европейском союзе снизился с 2,6% в 2020 г. до 1,9% в 2024 г., что отражает повышение эффективности систем управления кредитным риском. В странах Центральной Азии уровень проблемных кредитов в Казахстане сократился с 6,9% в 2020 г. до 3,1% в 2024 г., что свидетельствует о частичном улучшении качества кредитного портфеля, однако сохраняется чувствительность к росту ипотечного кредитования. Перспективы дальнейших исследований включают эмпирическую проверку модели на основе кейс-исследований банков развивающихся рынков, количественную оценку ее влияния на показатели кредитного портфеля, а также адаптацию подхода к другим сегментам кредитования, не связанным с ипотекой. </p></abstract><trans-abstract xml:lang="en"><p>In the context of increasing macroeconomic instability and increasing credit risks, the analysis of the factors of formation of problem mortgage loans in the banking system is becoming particularly relevant. This study aims to develop and propose a conceptual project-based framework, the NPL Project Approach that conceptualizes the management of non-performing mortgage loans as an integrated project cycle. The methodological basis of the research consists of methods of descriptive statistics, correlation analysis and multiple regression modeling. The empirical basis of the study consists of data collected from the Bureau of National Statistics and the National Bank of the Republic of Kazakhstan for the period 2020-2024, including indicators of household income, gross domestic product, inflation, interest rates, deposits and overdue debt. The analysis results show that the average level of problem loans in the European Union decreased from 2.6% in 2020 to 1.9% in 2024, reflecting an increase in the effectiveness of credit risk management systems. In Central Asian countries, the level of problem loans in Kazakhstan decreased from 6.9% in 2020 to 3.1% in 2024, indicating a partial improvement in the quality of the loan portfolio, but sensitivity to the growth of mortgage lending remains. The prospects for further research include empirical verification of the model based on case studies of emerging market banks, quantification of its impact on loan portfolio performance, as well as adaptation of the approach to other non-mortgage lending segments.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>проблемный кредит</kwd><kwd>кредит</kwd><kwd>кредитный риск</kwd><kwd>банк</kwd><kwd>банковская стратегия</kwd><kwd>финансовая стабильность</kwd><kwd>финансовое регулирование</kwd><kwd>экономическая устойчивость</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Non-Performing Loan</kwd><kwd>Credit</kwd><kwd>Credit Risk</kwd><kwd>Bank</kwd><kwd>Banking Strategy</kwd><kwd>Financial Stability</kwd><kwd>Financial Regulation</kwd><kwd>Economic Sustainability</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–609. https://doi.org/10.2307/2978933</mixed-citation><mixed-citation xml:lang="en">Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589–609. https://doi.org/10.2307/2978933</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Altman, E. I., Iwanicz Drozdowska, M., Laitinen, E. K., &amp; Suvas, A. (2017). Financial distress prediction in an international context: A review and empirical analysis of Altman’s Zscore model. Journal of International Financial Management &amp; Accounting, 28(2), 131–171. https://doi.org/10.1111/jifm.12053</mixed-citation><mixed-citation xml:lang="en">Altman, E. I., Iwanicz Drozdowska, M., Laitinen, E. K., &amp; Suvas, A. (2017). Financial distress prediction in an international context: A review and empirical analysis of Altman’s Zscore model. Journal of International Financial Management &amp; Accounting, 28(2), 131–171. https://doi.org/10.1111/jifm.12053</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Ari, A., Chen, S., &amp; Ratnovski, L. (2019). The dynamics of non performing loans during banking crises: A new database (IMF Working Paper 19/272). International Monetary Fund. https://doi.org/10.5089/9781513521152.001</mixed-citation><mixed-citation xml:lang="en">Ari, A., Chen, S., &amp; Ratnovski, L. (2019). The dynamics of non performing loans during banking crises: A new database (IMF Working Paper 19/272). International Monetary Fund. https://doi.org/10.5089/9781513521152.001</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">ADB. (2025). Nonperforming loans watch in Asia 2025. https://doi.org/10.22617/TCS250316-2</mixed-citation><mixed-citation xml:lang="en">ADB. (2025). Nonperforming loans watch in Asia 2025. https://doi.org/10.22617/TCS250316-2</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Asian Development Bank, &amp; European Central Bank. (2021). Nonperforming loans in Asia and Europe—Causes, impacts, and resolution strategies. Asian Development Bank. http://dx.doi.org/10.22617/TCS210412-2</mixed-citation><mixed-citation xml:lang="en">Asian Development Bank, &amp; European Central Bank. (2021). Nonperforming loans in Asia and Europe—Causes, impacts, and resolution strategies. Asian Development Bank. http://dx.doi.org/10.22617/TCS210412-2</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Balcılar, M., Usman, O., Yülek, M., Ağan, B., &amp; Er dal, B. (2024). House price connectedness and consumer sentiment in an era of destabilizing macroeconomic conditions: Empirical evidence from Türkiye. Borsa Istanbul Review, 24(1), 14–34. https://doi.org/10.1016/j.bir.2023.08.006</mixed-citation><mixed-citation xml:lang="en">Balcılar, M., Usman, O., Yülek, M., Ağan, B., &amp; Er dal, B. (2024). House price connectedness and consumer sentiment in an era of destabilizing macroeconomic conditions: Empirical evidence from Türkiye. Borsa Istanbul Review, 24(1), 14–34. https://doi.org/10.1016/j.bir.2023.08.006</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">BCBS. (1999). Credit risk modeling: Current practices and applications. Bank for International Settlements. Retrieved January 30, 2026 https://www.bis.org/publ/bcbs49.pdf</mixed-citation><mixed-citation xml:lang="en">BCBS. (1999). Credit risk modeling: Current practices and applications. Bank for International Settlements. Retrieved January 30, 2026 https://www.bis.org/publ/bcbs49.pdf</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Bauze, K. (2021). NPL resolution: Country cases. Regulatory framework for NPL resolution and private sector participation [Conference presentation]. IFC Workshop on NPL Resolution, FinSAC, World Bank Group, Vietnam. Retrieved January 30, 2026 https://www.ifc.org/content/dam/ifc/doc/mgrt/2-npl-resolution country-cases-karlis-bauze-eng.pdf</mixed-citation><mixed-citation xml:lang="en">Bauze, K. (2021). NPL resolution: Country cases. Regulatory framework for NPL resolution and private sector participation [Conference presentation]. IFC Workshop on NPL Resolution, FinSAC, World Bank Group, Vietnam. Retrieved January 30, 2026 https://www.ifc.org/content/dam/ifc/doc/mgrt/2-npl-resolution country-cases-karlis-bauze-eng.pdf</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Bermpei, T., Degl’Innocenti, M., Kalyvas, A. N., &amp; Zhou, S. (2023). Lender individualism and monitoring: Evidence from syndicated loans. Journal of Financial Stability, 66, 101123. https://doi.org/10.1016/j.jfs.2023.101123</mixed-citation><mixed-citation xml:lang="en">Bermpei, T., Degl’Innocenti, M., Kalyvas, A. N., &amp; Zhou, S. (2023). Lender individualism and monitoring: Evidence from syndicated loans. Journal of Financial Stability, 66, 101123. https://doi.org/10.1016/j.jfs.2023.101123</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Bertay, A. C., &amp; Huizinga, H. (2021). Non-performing loans – New risks and policies? NPL resolution after COVID 19: Main differences to previous crises [In-depth analysis]. Economic Governance Support Unit, European Parliament. Retrieved January 30, 2026 https://www.europarl.europa.eu/RegData/etudes/IDAN/2021/659648/IPOL_IDA(2021)659648_EN.pdf</mixed-citation><mixed-citation xml:lang="en">Bertay, A. C., &amp; Huizinga, H. (2021). Non-performing loans – New risks and policies? NPL resolution after COVID 19: Main differences to previous crises [In-depth analysis]. Economic Governance Support Unit, European Parliament. Retrieved January 30, 2026 https://www.europarl.europa.eu/RegData/etudes/IDAN/2021/659648/IPOL_IDA(2021)659648_EN.pdf</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Bianco, T., Cornwall, G., &amp; Sauley, B. (2025). Financial reform and mortgage lending by systemically important financial institutions. Economics Letters, 256, 112633. https://doi.org/10.1016/j.econlet.2025.112633</mixed-citation><mixed-citation xml:lang="en">Bianco, T., Cornwall, G., &amp; Sauley, B. (2025). Financial reform and mortgage lending by systemically important financial institutions. Economics Letters, 256, 112633. https://doi.org/10.1016/j.econlet.2025.112633</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Bosker, J., Gürtler, M., &amp; Zöllner, M. (2025). Machine learning–based variable selection for clustered credit risk modeling. Journal of Business Economics, 95, 617–652. https://doi.org/10.1007/s11573-024-01213-8</mixed-citation><mixed-citation xml:lang="en">Bosker, J., Gürtler, M., &amp; Zöllner, M. (2025). Machine learning–based variable selection for clustered credit risk modeling. Journal of Business Economics, 95, 617–652. https://doi.org/10.1007/s11573-024-01213-8</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Cenzon, J., &amp; Szabó, B. E. (2024). Mortgage choice and inflation experiences in the Eurozone. Journal of Monetary Economics, 147, 103611. https://doi.org/10.1016/j.jmoneco.2024.103611</mixed-citation><mixed-citation xml:lang="en">Cenzon, J., &amp; Szabó, B. E. (2024). Mortgage choice and inflation experiences in the Eurozone. Journal of Monetary Economics, 147, 103611. https://doi.org/10.1016/j.jmoneco.2024.103611</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Chai, N., Shi, B., &amp; Dong, Y. (2023). Default feature selection in credit risk modeling: Evidence from Chinese small enterprises. SAGE Open, 13(2). https://doi.org/10.1177/21582440231165224</mixed-citation><mixed-citation xml:lang="en">Chai, N., Shi, B., &amp; Dong, Y. (2023). Default feature selection in credit risk modeling: Evidence from Chinese small enterprises. SAGE Open, 13(2). https://doi.org/10.1177/21582440231165224</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Chen, G., Chutiman, N., Suraphee, S., Busababodhin, P., &amp; Volodin, A. (2025). Gradient Descent Decision Tree Algorithm and Nonlinear Programming for Credit Risk Assessment and Credit Strategy. Emerging Science Journal, 9(4), 04–05. https://doi.org/10.28991/ESJ-2025-0904-05</mixed-citation><mixed-citation xml:lang="en">Chen, G., Chutiman, N., Suraphee, S., Busababodhin, P., &amp; Volodin, A. (2025). Gradient Descent Decision Tree Algorithm and Nonlinear Programming for Credit Risk Assessment and Credit Strategy. Emerging Science Journal, 9(4), 04–05. https://doi.org/10.28991/ESJ-2025-0904-05</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Christou, I., Ponis, S., &amp; Palaiologou, E. (2010). Using the Agile Unified Process in banking. IEEE Software, 27(3), 72–79. https://doi.org/10.1109/MS.2009.156</mixed-citation><mixed-citation xml:lang="en">Christou, I., Ponis, S., &amp; Palaiologou, E. (2010). Using the Agile Unified Process in banking. IEEE Software, 27(3), 72–79. https://doi.org/10.1109/MS.2009.156</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Crosato, L., Domenech, J., &amp; Liberati, C. (2024). Websites’ data: A new asset for enhancing credit risk modeling. Annals of Operations Research, 342, 1671– 1686. https://doi.org/10.1007/s10479-023-05306-5</mixed-citation><mixed-citation xml:lang="en">Crosato, L., Domenech, J., &amp; Liberati, C. (2024). Websites’ data: A new asset for enhancing credit risk modeling. Annals of Operations Research, 342, 1671– 1686. https://doi.org/10.1007/s10479-023-05306-5</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Crouhy, M., Galai, D., &amp; Mark, R. (2000). A comparative analysis of current credit risk models. Journal of Banking &amp; Finance, 24(1–2), 59–117. https://doi.org/10.1016/S0378-4266(99)00053-9</mixed-citation><mixed-citation xml:lang="en">Crouhy, M., Galai, D., &amp; Mark, R. (2000). A comparative analysis of current credit risk models. Journal of Banking &amp; Finance, 24(1–2), 59–117. https://doi.org/10.1016/S0378-4266(99)00053-9</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">EBRD. (2025). NPL monitor: H1 2025. Vienna Initiative. Retrieved January 30, 2026 https://npl.vienna-initiative.com/assets/Uploads/2025/NPL-Monitor-H1-2025fv.pdf</mixed-citation><mixed-citation xml:lang="en">EBRD. (2025). NPL monitor: H1 2025. Vienna Initiative. Retrieved January 30, 2026 https://npl.vienna-initiative.com/assets/Uploads/2025/NPL-Monitor-H1-2025fv.pdf</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Forster, R., &amp; Sun, X. (2022). Taming the housing crisis: An LTV macroprudential policy. Economic Modeling, 108, 105761. https://doi.org/10.1016/j.econmod.2022.105761</mixed-citation><mixed-citation xml:lang="en">Forster, R., &amp; Sun, X. (2022). Taming the housing crisis: An LTV macroprudential policy. Economic Modeling, 108, 105761. https://doi.org/10.1016/j.econmod.2022.105761</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Gutkowski, V. A. (2021). Sovereign debt restructuring and credit recovery. Economía LACEA Journal, 23(1), 230–258. https://doi.org/10.31389/eco.409</mixed-citation><mixed-citation xml:lang="en">Gutkowski, V. A. (2021). Sovereign debt restructuring and credit recovery. Economía LACEA Journal, 23(1), 230–258. https://doi.org/10.31389/eco.409</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Han, X., Yang, Y., Chen, J., Wang, M., &amp; Zhou, M. (2025). Symmetry-Aware Credit Risk Modeling: A Deep Learning Framework Exploiting Financial Data Balance and Invariance. Symmetry, 17(3), 341. https://doi.org/10.3390/sym17030341</mixed-citation><mixed-citation xml:lang="en">Han, X., Yang, Y., Chen, J., Wang, M., &amp; Zhou, M. (2025). Symmetry-Aware Credit Risk Modeling: A Deep Learning Framework Exploiting Financial Data Balance and Invariance. Symmetry, 17(3), 341. https://doi.org/10.3390/sym17030341</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Holtermans, R., Kahn, M. E., &amp; Kok, N. (2024). Climate risk and commercial mortgage delinquency. Journal of Regional Science, 64(4), 994–1037. https://doi.org/10.1111/jors.12681</mixed-citation><mixed-citation xml:lang="en">Holtermans, R., Kahn, M. E., &amp; Kok, N. (2024). Climate risk and commercial mortgage delinquency. Journal of Regional Science, 64(4), 994–1037. https://doi.org/10.1111/jors.12681</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Iljins, J., &amp; Skvarciany, V. (2015). The role of change management in trust formation in commercial banks. Business: Theory and Practice, 16(4), 373–378. https://doi.org/10.3846/btp.2015.557</mixed-citation><mixed-citation xml:lang="en">Iljins, J., &amp; Skvarciany, V. (2015). The role of change management in trust formation in commercial banks. Business: Theory and Practice, 16(4), 373–378. https://doi.org/10.3846/btp.2015.557</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Instefjord, N., &amp; Nakata, H. (2022). Micro-prudential regulation and loan monitoring. Journal of Financial Services Research, 63, 339–362. https://doi.org/10.1007/s10693-021-00376-7</mixed-citation><mixed-citation xml:lang="en">Instefjord, N., &amp; Nakata, H. (2022). Micro-prudential regulation and loan monitoring. Journal of Financial Services Research, 63, 339–362. https://doi.org/10.1007/s10693-021-00376-7</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">IPAF Asia. (2025). NPLs in Asia: 2024 Data Analysis. International Public AMC Forum. Retrieved from https://ipafasia.org/news-and-data/npl-data&amp;rid=4</mixed-citation><mixed-citation xml:lang="en">IPAF Asia. (2025). NPLs in Asia: 2024 Data Analysis. International Public AMC Forum. Retrieved from https://ipafasia.org/news-and-data/npl-data&amp;rid=4</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Jakubik, P., &amp; Teleu, S. (2025). Improving Credit Risk Assessment in Uncertain Times: Insights from IFRS 9. Risks, 13(2), 38. https://doi.org/10.3390/risks13020038</mixed-citation><mixed-citation xml:lang="en">Jakubik, P., &amp; Teleu, S. (2025). Improving Credit Risk Assessment in Uncertain Times: Insights from IFRS 9. Risks, 13(2), 38. https://doi.org/10.3390/risks13020038</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Li, Y., Ni, Z., &amp; Xiao, B. (2025). Domain Knowledge-Enhanced Process Mining for Anomaly Detection in Commercial Bank Business Processes. Systems, 13(7), 545. https://doi.org/10.3390/systems13070545</mixed-citation><mixed-citation xml:lang="en">Li, Y., Ni, Z., &amp; Xiao, B. (2025). Domain Knowledge-Enhanced Process Mining for Anomaly Detection in Commercial Bank Business Processes. Systems, 13(7), 545. https://doi.org/10.3390/systems13070545</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance, 29(2), 449–470. https://doi.org/10.2307/2978814</mixed-citation><mixed-citation xml:lang="en">Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance, 29(2), 449–470. https://doi.org/10.2307/2978814</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Noriega, J., Rivera, L., Castañeda, J., &amp; Herrera, J. (2025). From Crisis to Algorithm: Credit Delinquency Prediction in Peru Under Critical External Factors Using Machine Learning. Data, 10(5), 63. https://doi.org/10.3390/data10050063</mixed-citation><mixed-citation xml:lang="en">Noriega, J., Rivera, L., Castañeda, J., &amp; Herrera, J. (2025). From Crisis to Algorithm: Credit Delinquency Prediction in Peru Under Critical External Factors Using Machine Learning. Data, 10(5), 63. https://doi.org/10.3390/data10050063</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Rahman, H. U., Arian, A., &amp; Sands, J. (2023). Does fiscal consolidation affect non-performing loans? Global evidence from heavily indebted countries (HICs). Journal of Risk and Financial Management, 16(9), 417. https://doi.org/10.3390/jrfm16090417</mixed-citation><mixed-citation xml:lang="en">Rahman, H. U., Arian, A., &amp; Sands, J. (2023). Does fiscal consolidation affect non-performing loans? Global evidence from heavily indebted countries (HICs). Journal of Risk and Financial Management, 16(9), 417. https://doi.org/10.3390/jrfm16090417</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Rodrigues, L. F., Oliveira, A., &amp; Rodrigues, H. (2023). Technology management has a significant impact on digital transformation in the banking sector. International Review of Economics &amp; Finance, 88, 1375–1388. https://doi.org/10.1016/j.iref.2023.07.040</mixed-citation><mixed-citation xml:lang="en">Rodrigues, L. F., Oliveira, A., &amp; Rodrigues, H. (2023). Technology management has a significant impact on digital transformation in the banking sector. International Review of Economics &amp; Finance, 88, 1375–1388. https://doi.org/10.1016/j.iref.2023.07.040</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Sanz-Guerrero, M., &amp; Arroyo, J. (2025). Credit Risk Meets Large Language Models: Building a Risk Indicator from Loan Descriptions in P2P Lending. Inteligencia Artificial, 28(75), 220–247. https://doi.org/10.4114/intartif.vol28iss75pp220-247</mixed-citation><mixed-citation xml:lang="en">Sanz-Guerrero, M., &amp; Arroyo, J. (2025). Credit Risk Meets Large Language Models: Building a Risk Indicator from Loan Descriptions in P2P Lending. Inteligencia Artificial, 28(75), 220–247. https://doi.org/10.4114/intartif.vol28iss75pp220-247</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Sarfraz, M., Qun, W., Hui, L., &amp; Abdullah, M. I. (2018). Environmental risk management strategies and the moderating role of corporate social responsibility in project financing decisions. Sustainability, 10(8), 2771. https://doi.org/10.3390/su10082771</mixed-citation><mixed-citation xml:lang="en">Sarfraz, M., Qun, W., Hui, L., &amp; Abdullah, M. I. (2018). Environmental risk management strategies and the moderating role of corporate social responsibility in project financing decisions. Sustainability, 10(8), 2771. https://doi.org/10.3390/su10082771</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Scope Ratings GmbH. (2025). European Bank NPL Monitor. Retrieved January 30, 2026 https://www.scoperatings.com/ScopeRatingsApi/api/download study?id=a4f8e84c-d1d8-4446-90ad-9cb1b0e1dc92</mixed-citation><mixed-citation xml:lang="en">Scope Ratings GmbH. (2025). European Bank NPL Monitor. Retrieved January 30, 2026 https://www.scoperatings.com/ScopeRatingsApi/api/download study?id=a4f8e84c-d1d8-4446-90ad-9cb1b0e1dc92</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">Silva, S. A., de Abreu, P. H. C., de Amorim, F. R., &amp; Santos, D. F. L. (2019). Application of Monte Carlo simulation for analysis of costs and economic risks in a banking agency. IEEE Latin America Transactions, 17(3), 418–425. https://doi.org/10.1109/TLA.2019.8863311</mixed-citation><mixed-citation xml:lang="en">Silva, S. A., de Abreu, P. H. C., de Amorim, F. R., &amp; Santos, D. F. L. (2019). Application of Monte Carlo simulation for analysis of costs and economic risks in a banking agency. IEEE Latin America Transactions, 17(3), 418–425. https://doi.org/10.1109/TLA.2019.8863311</mixed-citation></citation-alternatives></ref><ref id="cit37"><label>37</label><citation-alternatives><mixed-citation xml:lang="ru">Simonović, I., &amp; Todorović, M. (2019). Banking product and services development projects: The way to implement innovations. European Project Management Journal, 9(1), 3–9. https://doi.org/10.18485/epmj.2019.9.1.1</mixed-citation><mixed-citation xml:lang="en">Simonović, I., &amp; Todorović, M. (2019). Banking product and services development projects: The way to implement innovations. European Project Management Journal, 9(1), 3–9. https://doi.org/10.18485/epmj.2019.9.1.1</mixed-citation></citation-alternatives></ref><ref id="cit38"><label>38</label><citation-alternatives><mixed-citation xml:lang="ru">Smith, B. C., &amp; Yezer, A. M. (2025). A Lucas Critique of Mortgage Lending: Theory, Evidence, and Implications. The Journal of Real Estate Finance and Economics, 70, 637–676. https://doi.org/10.1007/s11146-02309951-2</mixed-citation><mixed-citation xml:lang="en">Smith, B. C., &amp; Yezer, A. M. (2025). A Lucas Critique of Mortgage Lending: Theory, Evidence, and Implications. The Journal of Real Estate Finance and Economics, 70, 637–676. https://doi.org/10.1007/s11146-02309951-2</mixed-citation></citation-alternatives></ref><ref id="cit39"><label>39</label><citation-alternatives><mixed-citation xml:lang="ru">Suryanto, H., Mahidadia, A., Bain, M., Guan, C., &amp; Guan, A. (2022). Credit Risk Modeling Using Transfer Learning and Domain Adaptation. Frontiers in Artificial Intelligence, 5, 868232. https://doi.org/10.3389/frai.2022.868232</mixed-citation><mixed-citation xml:lang="en">Suryanto, H., Mahidadia, A., Bain, M., Guan, C., &amp; Guan, A. (2022). Credit Risk Modeling Using Transfer Learning and Domain Adaptation. Frontiers in Artificial Intelligence, 5, 868232. https://doi.org/10.3389/frai.2022.868232</mixed-citation></citation-alternatives></ref><ref id="cit40"><label>40</label><citation-alternatives><mixed-citation xml:lang="ru">Van Zwieten, K. (2019). Managing Non-Performing Loans in Banks: A Review of the Evidence of the Impact of Insolvency and Creditor Rights Regimes (English). Washington, D.C.: World Bank Group. Retrieved January 30, 2026 http://documents.worldbank.org/curated/en/389811561742153005</mixed-citation><mixed-citation xml:lang="en">Van Zwieten, K. (2019). Managing Non-Performing Loans in Banks: A Review of the Evidence of the Impact of Insolvency and Creditor Rights Regimes (English). Washington, D.C.: World Bank Group. Retrieved January 30, 2026 http://documents.worldbank.org/curated/en/389811561742153005</mixed-citation></citation-alternatives></ref><ref id="cit41"><label>41</label><citation-alternatives><mixed-citation xml:lang="ru">Witzany, J., &amp; Kozina, A. (2022). Recovery process optimization using survival regression. Operational Research, 22, 5269–5296. https://doi.org/10.1007/s12351022-00703-3</mixed-citation><mixed-citation xml:lang="en">Witzany, J., &amp; Kozina, A. (2022). Recovery process optimization using survival regression. Operational Research, 22, 5269–5296. https://doi.org/10.1007/s12351022-00703-3</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
