The impact of management performance on risk-taking behavior in a dual banking system: A cross-country analysis

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In an era defined by global economic uncertainty, the role of management performance in influencing bank risk-taking has become pivotal. This urgency stems from the evolving dynamics of the banking sector and the need for robust risk management strategies. This study investigates the relationship between management performance and banks’ risk-taking behavior, drawing data from 248 banks across eight countries comprising Indonesia, Malaysia, Bangladesh, Pakistan, Saudi Arabia, Oman, Bahrain, and the United Arab Emirates spanning 2013–2021 using panel data analysis. The study reveals that management performance measured by a cost-to-income ratio (β = –0.44, p < 0.01) has a negative and significant relationship with bank risk-taking behavior. In essence, a bank with superior management performance, indicated by a lower cost-to-income ratio, tends to have greater financial stability, as evidenced by a higher Z-score. Notably, external factors like the financial crisis and institutional development as moderating variables do not significantly alter the relationship between management performance and banks’ risk-taking behavior. The study also discovers that Islamic banks (β = 0.31, p < 0.01) outperform their conventional counterparts in risk management and management performance. However, it is worth noting that the results of regional analysis demonstrate variations across the Southeast, South, and Middle East regions. After conducting several robustness check tests, the findings of this study remain consistent, offering valuable implications for both policymakers and bank management. These insights emphasize the importance of formulating appropriate regulations and frameworks to enhance management performance at the banking level.

Acknowledgment
The authors gratefully acknowledge the support from Direktorat Penelitian dan Pengabdian Masyarakat (DPPM) Universitas Islam Indonesia No: 006/Dir/DPPM/70/Pen.Unggulan/III/2023 for providing a research grant to this study.

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    • Table 1. Explanation of variables
    • Table 2. Data description
    • Table 3. Correlation
    • Table 4. Baseline result
    • Table 5. The baseline result at the regional level
    • Table 6. Robustness checks
    • Conceptualization
      Faaza Fakhrunnas, Katiya Nahda
    • Data curation
      Faaza Fakhrunnas, Katiya Nahda
    • Formal Analysis
      Faaza Fakhrunnas
    • Funding acquisition
      Faaza Fakhrunnas, Katiya Nahda
    • Investigation
      Faaza Fakhrunnas, Katiya Nahda
    • Methodology
      Faaza Fakhrunnas
    • Project administration
      Faaza Fakhrunnas, Katiya Nahda
    • Resources
      Faaza Fakhrunnas
    • Software
      Faaza Fakhrunnas
    • Supervision
      Faaza Fakhrunnas, Katiya Nahda
    • Validation
      Faaza Fakhrunnas
    • Visualization
      Faaza Fakhrunnas
    • Writing – original draft
      Faaza Fakhrunnas
    • Writing – review & editing
      Faaza Fakhrunnas, Katiya Nahda