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dc.contributor.advisorCullen, Andrea J.
dc.contributor.advisorNeagu, Daniel
dc.contributor.authorOchuko, Rita E.*
dc.date.accessioned2013-12-02T17:09:59Z
dc.date.available2013-12-02T17:09:59Z
dc.date.issued2013-12-02
dc.identifier.urihttp://hdl.handle.net/10454/5733
dc.description.abstractThis study investigates E-banking Operational Risk Assessment (ORA) to enable the development of a new ORA framework and methodology. The general view is that E-banking systems have modified some of the traditional banking risks, particularly Operational Risk (OR) as suggested by the Basel Committee on Banking Supervision in 2003. In addition, recent E-banking financial losses together with risk management principles and standards raise the need for an effective ORA methodology and framework in the context of E-banking. Moreover, evaluation tools and / or methods for ORA are highly subjective, are still in their infant stages, and have not yet reached a consensus. Therefore, it is essential to develop valid and reliable methods for effective ORA and evaluations. The main contribution of this thesis is to apply Fuzzy Inference System (FIS) and Tree Augmented Naïve Bayes (TAN) classifier as standard tools for identifying OR, and measuring OR exposure level. In addition, a new ORA methodology is proposed which consists of four major steps: a risk model, assessment approach, analysis approach and a risk assessment process. Further, a new ORA framework and measurement metrics are proposed with six factors: frequency of triggering event, effectiveness of avoidance barriers, frequency of undesirable operational state, effectiveness of recovery barriers before the risk outcome, approximate cost for Undesirable Operational State (UOS) occurrence, and severity of the risk outcome. The study results were reported based on surveys conducted with Nigerian senior banking officers and banking customers. The study revealed that the framework and assessment tools gave good predictions for risk learning and inference in such systems. Thus, results obtained can be considered promising and useful for both E-banking system adopters and future researchers in this area.en_US
dc.language.isoenen_US
dc.rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.eng
dc.subjectE-bankingen_US
dc.subjectOperational risk assessmenten_US
dc.subjectSoft computing toolsen_US
dc.subjectFuzzy logicen_US
dc.subjectBayesian networksen_US
dc.subjectNaïve Bayes classifieren_US
dc.subjectFactor analysisen_US
dc.subjectRisk matricesen_US
dc.subjectNigeria banksen_US
dc.titleE-banking operational risk assessment. A soft computing approach in the context of the Nigerian banking industry.en_US
dc.type.qualificationleveldoctoralen_US
dc.publisher.institutionUniversity of Bradfordeng
dc.publisher.departmentSchool of Computing, Informatics and Mediaen_US
dc.typeThesiseng
dc.type.qualificationnamePhDen_US
dc.date.awarded2012
refterms.dateFOA2018-07-19T12:27:28Z


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