Non-Performing Loans, Bank Performance, and Financial Stability: The Moderator Effect of Digitalization
DOI:
https://doi.org/10.47654/v30y2026i3p1-26Keywords:
Non-performing loans, bank performance, financial stability, digitalization, moderating effectAbstract
Purpose- This paper examines how digitalization moderates the relationship between non-performing loans (NPLs), bank performance, and financial stability in the banking sector.
Design/methodology/approach - The study applies panel data regression techniques to banks operating in 18 MENA countries over the period 2000–2023. Bank performance is measured using return on assets (ROA) and return on equity (ROE), while financial stability is proxied by the Z-score. Digitalization indicators are included both directly and through interaction terms with NPLs to capture their moderating effect. Several robustness tests are conducted to validate the results.
Findings - Results show that NPLs negatively affect bank performance and financial stability, highlighting the destabilizing impact of deteriorating credit portfolios. Digitalization exerts a direct positive effect by improving credit monitoring, information processing, and operational efficiency. Interaction results indicate that higher digitalization levels significantly reduce the negative effect of NPLs on profitability and resilience. Managerially, banks investing in advanced credit-risk analytics, automated loan monitoring, and digital customer screening tools are better able to mitigate NPL-related losses, detect early loan deterioration, and improve recovery strategies. These findings contribute to Decision Sciences by demonstrating how technological adoption enhances risk prediction, managerial decision-making, and strategic resource allocation.
Originality/value - This study offers new empirical evidence on the moderating role of digitalization in the NPL–performance–financial stability nexus through one of the first long-term panel analyses of the MENA banking sector spanning more than two decades. It extends existing literature by quantifying the impact of technological adoption on credit risk–performance dynamics in emerging markets.
Practical implications - The findings provide actionable insights for managers and policymakers. Banks should prioritize investments in (1) AI and machine learning for predictive credit scoring and early-warning systems, (2) integrated digital loan management platforms for improved monitoring and recovery, and (3) digital customer data infrastructures to reduce information asymmetry. Regulators can support digital transformation through regulatory sandboxes and fintech partnerships to strengthen financial stability. Overall, targeted digitalization strategies can reduce NPL accumulation, enhance efficiency, and improve long-term resilience.
References
Ahmed, S., & Sur, S. (2023). Change in the uses pattern of digital banking services by Indian rural MSMEs during demonetization and Covid-19 pandemic-related restrictions. Vilakshan-XIMB Journal of Management, 20(1), 166–192. https://doi.org/10.1108/XJM-09-2020-0138
Albaity, M., Shah, S. F., Al-Tamimi, H. A. H., Rahman, M., & Thangavelu, S. (2023). Country risk and bank returns: Evidence from MENA countries. The Journal of Economic Asymmetries, 28, e00329. https://doi.org/10.1016/j.jeca.2023.e00329
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/10.1111/j.1540-6261.1968.tb00843.x
Athanasoglou, P. P., Brissimis, S. N., & Delis, M. D. (2008). Bank-specific, industry-specific and macroeconomic determinants of bank profitability. Journal of International Financial Markets, Institutions and Money, 18(2), 121–136. https://doi.org/10.1016/j.intfin.2006.07.001
Awdeh, A., El Moussawi, C., & Hamadi, H. (2024). The impact of inflation on bank stability: Evidence from the MENA banks. International Journal of Islamic and Middle Eastern Finance and Management, 17(2), 379–399. https://doi.org/10.1108/IMEFM-10-2023-0388
Ayinuola, T. F., & Gumel, B. I. (2023). The impact of cost-to-income ratio on bank performance in Nigeria. International Journal of Multidisciplinary and Current Educational Research, 5(2), 125–137.
Babalos, V., Caporale, G. M., & Philippas, N. (2015). Gender, style diversity, and their effect on fund performance. Research in International Business and Finance, 35, 57–74.
Beck, R., Jakubik, P., & Piloiu, A. (2013). Non-performing loans: What matters in addition to the economic cycle.
Boussaada, R., Hakimi, A., & Karmani, M. (2023). Non-performing loans and bank performance: What role does corporate social responsibility play? A system GMM analysis for European banks. Journal of Applied Accounting Research, 24(5), 859–888.
Boyd, J. H., & Runkle, D. E. (1993). Size and performance of banking firms: Testing the predictions of theory. Journal of Monetary Economics, 31(1), 47–67. https://doi.org/10.1016/0304-3932(93)90016-9
Chen, I.-J., Tsai, H., Chen, Y.-S., Lin, W.-C., & Li, T.-Y. (2024). Bank performance and liquidity management. Review of Quantitative Finance and Accounting. https://doi.org/10.1007/s11156-024-01342-9
Chen, Z., Li, H., Wang, T., & Wu, J. (2023). How digital transformation affects bank risk: Evidence from listed Chinese banks. Finance Research Letters, 58, 104319. https://doi.org/10.1016/j.frl.2023.104319
Cheng, Y., Hui, Y., McAleer, M., & Wong, W. K. (2021). Spurious relationships for nearly non-stationary series. Journal of Risk and Financial Management, 14(8), 366.
Dietrich, A., & Wanzenried, G. (2011). Determinants of bank profitability before and during the crisis: Evidence from Switzerland. Journal of International Financial Markets, Institutions and Money, 21(3), 307–327. https://doi.org/10.1016/j.jifmim.2010.10.001
Garcia, M. T. M., & Abreu, S. R. (2024). Banking stability determinants: Evidence from Portugal. Journal of Banking Regulation, 25(2), 160–178.
Granger, C. W. J., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111–120. https://doi.org/10.1016/0304-4076(74)90034-7
Grassi, L., Figini, N., & Fedeli, L. (2022). How does a data strategy enable customer value? The case of FinTechs and traditional banks under the open finance framework. Financial Innovation, 8(1), 75.
Gupta, S., & Bansal, R. (2024). Understanding bank lending and its relationship with profitability and non-performing loans: A meta-analysis. Journal of Economic and Administrative Sciences. https://doi.org/10.1108/jeas-03-2023-0060
Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271. https://doi.org/10.2307/1913827
Hui, Y., Wong, W. K., Bai, Z., & Zhu, Z. Z. (2017). A new nonlinearity test to circumvent the limitation of Volterra expansion with application. Journal of the Korean Statistical Society, 46, 365-374.
Jia, K., & Liu, X. (2023). Bank digital transformation, bank competitiveness and systemic risk. Frontiers in Physics, 11, 1297912. https://doi.org/10.3389/fphy.2023.1297912
Khan, M. A., Siddique, A., & Sarwar, Z. (2020). Determinants of non-performing loans in the banking sector in developing state. Asian Journal of Accounting Research, 5(1), 135–145.
Khan, N., Biswas, S., & Kumari, N. (2024). Banking 4.0 and its role in Fintech. In the Adoption of Fintech (pp. 144–159). Productivity Press.
Kosmidou, K., Pasiouras, F., & Tsaklanganos, A. (2007). Domestic and multinational determinants of foreign bank profits: The case of Greek banks operating abroad. Journal of Multinational Financial Management, 17(1), 1–15.
Kou, M., Yang, Y., & Chen, K. (2024). Financial technology research: Past and future trajectories. International Review of Economics & Finance. https://doi.org/10.1016/j.iref.2024.03.032
Laeven, L., & Levine, R. (2009). Bank governance, regulation and risk taking. Journal of Financial Economics, 93(2), 259–275.
Lee, C. C., Wang, C. S., He, Z., Xing, W. W., & Wang, K. (2023). How does green finance affect energy efficiency? The role of green technology innovation and energy structure. Renewable Energy, 219, 119417.
Lee, J. W. (2023). Influence of technological innovation characteristics on the survival period of SMEs in the service industry: Evidence from Korea. Journal of Innovation & Knowledge, 8(4), 100422.
Lim, J., McCormick, M., Roche, S., & Smith, E. (2023). Financial stability risks from commercial real estate.
Marouli, A. Z., Giannini, E. N., & Caloghirou, Y. D. (2023). A non-performing loans (NPLs) portfolio pricing model based on recovery performance: The case of Greece. Risks, 11(5), 96.
Ok, Y., Kim, J., & Park, Y. J. (2019). The effect of housing prices on bank performance in Korea. Sustainability, 11(22), 6242. https://doi.org/10.3390/su11226242
Olson, D., & Zoubi, T. A. (2011). Efficiency and bank profitability in MENA countries. Emerging Markets Review, 12(2), 94–110.
Phillips, P. C. B. (1986). Understanding spurious regressions in econometrics. Journal of Econometrics, 33(3), 311–340. https://doi.org/10.1016/0304-4076(86)90001-1
Restrepo-Morales, J. A., Valencia-Cárdenas, M., & García-Pérez-de-Lema, D. (2024). The role of technological innovation in the mitigation of the crisis generated by COVID-19: An empirical study of small and medium-sized businesses (SMEs) in Latin America. International Studies of Management & Organization, 54(2), 120–136.
Saidi, H., Hakimi, A., & Rachdi, H. (2024). On the technology-growth relationship: Does the institutional quality matter? A panel simultaneous equation framework. Journal of the Knowledge Economy, 15(1), 3439–3465.
Van Horen, N. (2007). Foreign banking in developing countries; origin matters. Emerging Markets Review, 8(2), 81–105. https://doi.org/10.1016/j.ememar.2007.01.002
Wong, W. K., Cheng, Y., & Yue, M. (2024). Could regression of stationary series be spurious? Asia-Pacific Journal of Operational Research, 2440017.
Zaman, S. I., Khan, S. A., Qabool, S., & Gupta, H. (2023). How digitalization in banking improves service supply chain resilience of e-commerce sector? A technological adoption model approach. Operations Management Research, 16(2), 904–930.
Published
Issue
Section
Categories
License
Copyright (c) 2026 Amir SAADAOUI (Corresponding Author); Mohamed Naceur SOUISSI (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Scientific and Business World