Corporate Risk Management Practices – Journal of Research Innovation and Implications in Education https://www.jriiejournal.com Mon, 02 Mar 2026 04:02:05 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.1 https://www.jriiejournal.com/wp-content/uploads/2019/02/cropped-JRIIE-LOGO-1-32x32.jpg Corporate Risk Management Practices – Journal of Research Innovation and Implications in Education https://www.jriiejournal.com 32 32 194867206 Influence of Corporate Risk Management Practices on Commercial Bank Financial Performance in Rwanda https://www.jriiejournal.com/influence-of-corporate-risk-management-practices-on-commercial-bank-financial-performance-in-rwanda/?utm_source=rss&utm_medium=rss&utm_campaign=influence-of-corporate-risk-management-practices-on-commercial-bank-financial-performance-in-rwanda https://www.jriiejournal.com/influence-of-corporate-risk-management-practices-on-commercial-bank-financial-performance-in-rwanda/#comments Mon, 02 Mar 2026 03:59:45 +0000 https://www.jriiejournal.com/?p=9211 Read More Read More

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Mossembaye Ndemra Felicite
University of Kigali
https://orcid.org/0009-0003-0552-0638
Email: mossembayef@gmail.com

Abstract: The general objective of this study was to examine influence of corporate risk management practices on commercial bank financial performance in Rwanda. The study sought to achieve the following specific objectives: to evaluate the influence of Risk Identification, Risk Assessment and Measurement, Risk Monitoring and Control and Risk Mitigation Strategies on bank performance at Bank of Kigali. The data were analyzed using statistical methods, primarily through the calculation of frequencies and percentages, to identify patterns and effectively summarize the findings. For this study, the sample comprised 133 employees from Bank of Kigali. The study relied on secondary data for measurements and scaling, which were applied during the data analysis process. The researcher employed quantitative methods for this study, specifically utilizing a questionnaire to collect data. The collected data were systematically analyzed using the Statistical Package for the Social Sciences (SPSS) software. The ANOVA results assessed the overall significance of the regression model in explaining variability in bank performance. The resulting F-statistic of 91.136 tests whether the model fits significantly better than one without predictors. The p-value of .000, well below the 0.05 threshold, indicates the model is highly statistically significant. Overall, the findings confirm a statistically robust, cohesive risk management system that critically supports operational efficiency and financial stability, with Risk Identification and Risk Mitigation Strategies identified as the most impactful factors.

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