A new internal data measure for operational risk: a case study of a South African bank
| dc.contributor.author | Hoohlo, Mphekeleli | |
| dc.date.accessioned | 2015-03-12T09:43:53Z | |
| dc.date.available | 2015-03-12T09:43:53Z | |
| dc.date.issued | 2015-03-12 | |
| dc.description | Thesis (M.M. (Finance & Investment))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Graduate School of Business Administration, 2014. | en_ZA |
| dc.description.abstract | This study examines the e ect of automation on operational risk (OpRisk) measurement in a South African bank. It uses historical process risk loss data from the rst quarter (2013Q1) derived from the automated trade amendment tracker (ATAT) database { a computerised tool designed to automate the collection of internally generated OpRisk events at the bank in question. The results indicate that a Value{at{Risk (VaR) estimate for OpRisk largely depends on the accuracy of the loss data. Capital adequacy is determined using this estimate of VaR, suggesting that the ATAT device used in operational risk measurement improves on investment services activity in South Africa. Finally, it appears that risk management practices in the South African banking industry are more concerned about traditional operational risk management (ORM) rather than the determination of OpRisk VaR as it becomes a matter of great concern for nancial institutions (FI's) across the globe. | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/10539/17271 | |
| dc.language.iso | en | en_ZA |
| dc.title | A new internal data measure for operational risk: a case study of a South African bank | en_ZA |
| dc.type | Thesis | en_ZA |