This study utilizes the random forest technique to investigate risk management practices and concerns in Islamic banks using survey data from 2016 to 2021. Findings reveal that larger banks provide more consistent survey responses, driven by their confidence and larger survey budgets. Moreover, a positive link is established between a country’s development, characterized by high GDPs and low inflation and interest rates, and the precision of Islamic banks’ survey responses. Analyzing risk-related concerns, the study notes a significant reduction in credit portfolio risk attributed to improved risk management practices, global economic growth, stricter regulations, and diversified asset portfolios. Concerns related to terrorism financing and cybersecurity risks have also decreased due to the better enforcement of anti-money laundering regulations and investments in cybersecurity infrastructure and education. This research enhances our understanding of risk management in Islamic banks, highlighting the impact of bank size and country development. Additionally, it emphasizes the need for ongoing analysis beyond 2021 to account for potential COVID-19 effects and evolving risk management and regulatory practices in Islamic banking.

中文翻译：

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随机森林在分析伊斯兰银行风险管理中的预测能力

本研究利用随机森林技术，利用 2016 年至 2021 年的调查数据来调查伊斯兰银行的风险管理实践和担忧。研究结果表明，大型银行在信心和较大的调查预算的推动下，提供了更一致的调查答复。此外，以高国内生产总值和低通胀和利率为特征的国家发展与伊斯兰银行调查反应的准确性之间存在正相关关系。通过分析与风险相关的问题，该研究指出，由于风险管理实践的改进、全球经济增长、更严格的监管和多元化的资产组合，信贷投资组合风险显着降低。由于反洗钱法规的更好执行以及对网络安全基础设施和教育的投资，与恐怖主义融资和网络安全风险相关的担忧也有所减少。这项研究增强了我们对伊斯兰银行风险管理的理解，强调了银行规模和国家发展的影响。此外，它还强调需要在 2021 年之后持续进行分析，以考虑 COVID-19 的潜在影响以及伊斯兰银行业不断变化的风险管理和监管实践。