Impact of liquidity and operational risks on Jordanian banks’ stability: A comparative study of conventional and Islamic banks
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DOIhttp://dx.doi.org/10.21511/bbs.21(1).2026.01
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Article InfoVolume 21 2026, Issue #1, pp. 1-15
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Type of the article: Research Article
Abstract
The study examines the impact of liquidity risk and operational risk on the financial stability in both commercial and Islamic banks in Jordan. The study utilizes secondary data covering a period of ten years, from 2012 to 2022, as it offers a holistic and uninterrupted period that includes the key regulatory, economic, and structural changes in Jordan’s banking sector. The study employs panel data analysis to assess these relationships. Liquidity risks are measured using the cash-to-asset ratio and the liabilities-to-deposit ratio, while operational risks are assessed through two indicators: the operational cost-to-income ratio and the operational cost-to-total-assets ratio. The findings reveal that the liabilities-to-deposit ratio, as represented by liquidity risk, and the operating cost-to-income ratio, as represented by operational risks, have significant negative impacts on the financial stability of conventional banks, which emphasizes the need for effective cost and liquidity management. In Islamic banks, financial stability improves significantly due to liquidity indicators: higher liabilities-to-deposit ratios and cash-to-asset ratios, highlighting how essential liquidity is. The operational risk indicators have no impact on Islamic banks. Moreover, control variables such as return on assets (ROA) positively influence stability in conventional and Islamic banks. However, the stability of conventional and Islamic banks faces negative influences from their size, which indicates that bigger banks could become exposed to operational risks and financial vulnerabilities. The research demonstrates that financial stability elements operate differently between conventional and Islamic banking systems. Financial institutions, together with governments, need to establish solutions to fill these gaps.
- Keywords
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JEL Classification (Paper profile tab)G28, G21, G32
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References40
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Tables10
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Figures0
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- Table 1. Variables description
- Table 2. Descriptive statistics of study variables for conventional and Islamic banks
- Table 3. Correlation matrix
- Table 4. Unit root test results
- Table 5. Results of the variance inflation factor (VIF)
- Table 6. Breusch-Pagan test results
- Table 7. Comparison between study models
- Table 8. Random effects model
- Table 9. Pooled (OLS) regression model for Islamic banks
- Table A1. Conventional and Islamic Jordanian banks listed on the Amman Stock Exchange
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