Commercial Bank operational risk management: Exploratory study on selected Ethiopian Commercial Banks
| dc.contributor.advisor | Takele, Yitbarek (PhD) | |
| dc.contributor.author | Firew, Fasika | |
| dc.date.accessioned | 2018-10-30T05:25:56Z | |
| dc.date.accessioned | 2023-11-04T09:02:41Z | |
| dc.date.available | 2018-10-30T05:25:56Z | |
| dc.date.available | 2023-11-04T09:02:41Z | |
| dc.date.issued | 2011 | |
| dc.description.abstract | The purpose of this study is to analyze operational risk management (ORM) of selected Ethiopian commercial banks. As operational risk differs from the other banking risks in terms of its quantification and prediction ability, banks need to measure and manage it carefully as it will have detrimental effect on its entire performance and profitability eventually. The types of data used were both primary and secondary as the research design employed was mixed-mode (Qualitative and quantitative) design. The variables were affirmed reliable fulfilling the minimum 70% requirement of Cronbach‟s alpha value. As the study was conducted at institutional level the non probability purposive sampling technique was used to select the banks. Hence, 12 commercial banks have been selected and contacted, where the sample respondents‟, staffs of risk management section (Risk experts and officers) and internal auditors were used as “key informant” or “Proxy” for the study unit of analysis (Banks). And 96 respondents‟ for the unit analysis were considered for this study. As the study was constituted a data having an ordinal scale of measurement, the Spearman correlation (Rho) coefficient and principal component analysis (PCA) were used as methods of data analysis. Besides, the descriptive analysis has been used for an interpretation of close ended questions. Analysis of Spearman Correlation (Rho) coefficient findings has resulted into existence of significant positive correlation coefficient between the variables tough the degree of strength differs. Principal component analysis as factor analysis method has resulted into an extraction of 6 factors as useful factors out of the initial 20 factors considered based on an Eigen value, λ>1.0 which all together accounts for about 64% of variance. The descriptive analysis of the board approval of policies and procedures of banks operational risk has shown the presence of board approval on the different issues of banks operational risk, based on majority of the responses though it wouldn‟t guarantee the presence of effective ORM. It is highly recommended to have committed management and strong internal control mechanisms for an effective ORM. Key Words: Operational risk, Operational Risk Management, Operational risk factors (Loss events), Operational risk effect, Operational risk contributory factors, Basel II Framework (Capital Accord) | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/123456789/13369 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Operational risk | en_US |
| dc.subject | Operational Risk Management | en_US |
| dc.subject | Operational risk factors | en_US |
| dc.subject | (Loss events) | en_US |
| dc.subject | Operational risk effect | en_US |
| dc.subject | Operational risk contributory factors | en_US |
| dc.subject | Basel II Framework | en_US |
| dc.subject | (Capital Accord) | en_US |
| dc.title | Commercial Bank operational risk management: Exploratory study on selected Ethiopian Commercial Banks | en_US |
| dc.type | Thesis | en_US |