A cost benefit analysis of operational risk quantification methods for regulatory capital

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dc.contributor.advisorRajaratnam, Kanshukanen_ZA
dc.contributor.advisorToerien, Francoisen_ZA
dc.contributor.authorNyathi, Mandlaen_ZA
dc.date.accessioned2016-09-14T12:51:04Z
dc.date.available2016-09-14T12:51:04Z
dc.date.issued2016en_ZA
dc.description.abstractOperational risk has attracted a sizeable amount of attention in recent years as a result of massive operational losses that headlined financial markets across the world. The operational risk losses have been on the back of litigation cases and regulatory fines, some of which originated from the 2008 global financial crisis. As a result it is compulsory for financial institutions to reserve capital for the operational risk exposures inherent in their business activities. Local financial institutions are free to use any of the following operational risk capital estimation methods: Advanced Measurement Approach (AMA), the Standardized (TSA) and/ the Basic Indicator Approach (BIA). The BIA and TSA are predetermined by the Reserve Bank, whilst AMA relies on internally generated methodologies. Estimation approaches employed in this study were initially introduced by the BCBS, largely premised on an increasingly sophisticated technique to incentivise banks to continually advance their management and measurement methods while benefiting from a lower capital charge through gradating from the least to the most sophisticated measurement tool. However, in contrast to BCBS's premise, Sundmacher (2007), whilst using a hypothetical example, finds that depending on a financial institution's distribution of its Gross Income, the incentive to move from BIA to TSA is nonexistent or marginal at best. In this thesis I extend Sundmacher (2007)'s work, and I test one instance of AMA regulatory capital (RegCap) against that of TSA in a bid to crystalise the rand benefit that financial institutions stand to attain (if at all) should they move from TSA to AMA. A Loss Distribution Approach (LDA), coupled with a Monte Carlo simulation, were used in modelling AMA. In modelling the loss severities, the Lognormal, Weibull, Burr, Generalized Pareto, Pareto and Gamma distributions were considered, whilst the Poisson distribution was used for modelling operational loss frequency. The Kolmogorov-Smirnov and Akaike information criterion tests were respectively used for assessing the level of distribution fit and for model selection. The robustness and stability of the model were gauged using stress testing and bootstrap. The TSA modelling design involved using predetermined beta values for different business lines specified by the BCBS. The findings show that the Lognormal and Burr distributions best describes the empirical data. Additionally, there is a substantial incentive in terms of the rand benefit of migrating from TSA to AMA in estimating operational risk capital. The initial benefit could be directed towards changes in information technology systems in order to effect the change from TSA to AMA. Notwithstanding that the data set used in this thesis is restricted to just one of the "big four banks" (owing to proprietary restrictions), the methodology is representable (or generalisable) to the other big banks within South Africa. The scope of this study can further be extended to cover Extreme Value Theory, Non-Parametric Empirical Sampling, Markov Chain Monte Carlo, and Bayesian Approaches in estimating operational risk capital.en_ZA
dc.identifier.apacitationNyathi, M. (2016). <i>A cost benefit analysis of operational risk quantification methods for regulatory capital</i>. (Thesis). University of Cape Town ,Faculty of Commerce ,Department of Finance and Tax. Retrieved from http://hdl.handle.net/11427/21756en_ZA
dc.identifier.chicagocitationNyathi, Mandla. <i>"A cost benefit analysis of operational risk quantification methods for regulatory capital."</i> Thesis., University of Cape Town ,Faculty of Commerce ,Department of Finance and Tax, 2016. http://hdl.handle.net/11427/21756en_ZA
dc.identifier.citationNyathi, M. 2016. A cost benefit analysis of operational risk quantification methods for regulatory capital. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Nyathi, Mandla AB - Operational risk has attracted a sizeable amount of attention in recent years as a result of massive operational losses that headlined financial markets across the world. The operational risk losses have been on the back of litigation cases and regulatory fines, some of which originated from the 2008 global financial crisis. As a result it is compulsory for financial institutions to reserve capital for the operational risk exposures inherent in their business activities. Local financial institutions are free to use any of the following operational risk capital estimation methods: Advanced Measurement Approach (AMA), the Standardized (TSA) and/ the Basic Indicator Approach (BIA). The BIA and TSA are predetermined by the Reserve Bank, whilst AMA relies on internally generated methodologies. Estimation approaches employed in this study were initially introduced by the BCBS, largely premised on an increasingly sophisticated technique to incentivise banks to continually advance their management and measurement methods while benefiting from a lower capital charge through gradating from the least to the most sophisticated measurement tool. However, in contrast to BCBS's premise, Sundmacher (2007), whilst using a hypothetical example, finds that depending on a financial institution's distribution of its Gross Income, the incentive to move from BIA to TSA is nonexistent or marginal at best. In this thesis I extend Sundmacher (2007)'s work, and I test one instance of AMA regulatory capital (RegCap) against that of TSA in a bid to crystalise the rand benefit that financial institutions stand to attain (if at all) should they move from TSA to AMA. A Loss Distribution Approach (LDA), coupled with a Monte Carlo simulation, were used in modelling AMA. In modelling the loss severities, the Lognormal, Weibull, Burr, Generalized Pareto, Pareto and Gamma distributions were considered, whilst the Poisson distribution was used for modelling operational loss frequency. The Kolmogorov-Smirnov and Akaike information criterion tests were respectively used for assessing the level of distribution fit and for model selection. The robustness and stability of the model were gauged using stress testing and bootstrap. The TSA modelling design involved using predetermined beta values for different business lines specified by the BCBS. The findings show that the Lognormal and Burr distributions best describes the empirical data. Additionally, there is a substantial incentive in terms of the rand benefit of migrating from TSA to AMA in estimating operational risk capital. The initial benefit could be directed towards changes in information technology systems in order to effect the change from TSA to AMA. Notwithstanding that the data set used in this thesis is restricted to just one of the "big four banks" (owing to proprietary restrictions), the methodology is representable (or generalisable) to the other big banks within South Africa. The scope of this study can further be extended to cover Extreme Value Theory, Non-Parametric Empirical Sampling, Markov Chain Monte Carlo, and Bayesian Approaches in estimating operational risk capital. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - A cost benefit analysis of operational risk quantification methods for regulatory capital TI - A cost benefit analysis of operational risk quantification methods for regulatory capital UR - http://hdl.handle.net/11427/21756 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/21756
dc.identifier.vancouvercitationNyathi M. A cost benefit analysis of operational risk quantification methods for regulatory capital. [Thesis]. University of Cape Town ,Faculty of Commerce ,Department of Finance and Tax, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/21756en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Finance and Taxen_ZA
dc.publisher.facultyFaculty of Commerceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherFinancial Managementen_ZA
dc.titleA cost benefit analysis of operational risk quantification methods for regulatory capitalen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMComen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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