Do corruption and political connections drive bank risk-taking behavior? The moderating role of governance across Asian economies

Abstract

Background: Existing literature has analyzed the effect of corruption and political connections on bank risk-taking; however, the findings differ regarding their role as grease or sand the wheels. This study aims to examine the effects of corruption, political connections, and the role of corporate governance in moderating the relationship between corruption and banking risk, considering the income classification of Asian countries. Methods: This study uses descriptive analysis and panel data regression with a random-effects model to examine the relationship between variables. The study was conducted on 95 banks in Asia over the period 2019-2024. Findings: The results indicate a negative and significant effect of corruption on banking stability. Corruption increases the risk of bank insolvency. Testing of subsamples of middle-income and high-income countries shows that corruption increases the risk of bank insolvency in middle-income countries but has a different effect on banks in high-income countries. The positive and significant effect of political connections on bank stability is only observed in middle-income countries. Governance, proxied by gender composition and educational qualifications, moderates the effect of corruption on the dependent variable in middle-income countries. The findings indicate that increasing the proportion of women in the board structure increases the risk of bank insolvency. Conclusion: The findings reveal that corruption decreases banking stability and increases risks in middle-income countries. Political connections and governance variables demonstrate different effects in countries with different levels of income categorization. Novelty/Originality of this article: This study offers a novel contribution by integrating the variables of corruption, political connections, and corporate governance into banking risk analysis, while also considering heterogeneity in income levels across countries.