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Measuring operational risk in the ALCO process / by Charmaine Smit

In the last decade, the financial service industry has become increasingly aware of the dangers posed by operational risk. Profound changes in the economic and financial environment have made it necessary for banks in general to adapt their long term strategies as well as their approaches to the management of their assets and liabilities. Regardless of this heightened awareness, banks continue to fail at effective management of these risks. The Asset and Liability Management Committee (ALCO) is responsible for managing a bank's assets and liabilities to balance its many risk exposures and thereby help it achieve its operating objectives e.g. maximising Net Interest Income (Nil). Thus the ALCO process is the crux of the strategic management process performed within a bank. The ALCO process is driven by people, processes and technology which, in essence, is a broad definition of operational risk. Failure in any one of these areas will lead to failure of the ALCO, ALCO processes and, therefore, the strategic Asset and Liability Management (ALM). The focus of this study is, therefore, how to measure and manage operational risk in a bank's ALCO process. A case study was conducted, with the aid of ALCO experts in a specialised niche bank in South Africa, to identify operational risks within this bank's ALCO process. The various risk indicators of operational risk were classified into 5 broad categories. Each category was weighted according to its representative risk indicator and converted into percentages for the interpretation of the overall results. Category 2 (authority levels) has the highest negative impact, while the remaining 4 categories (employee, model, system and other indicators) have a medium negative impact, on the efficiency of the ALCO process. / Thesis (M.Com. (Risk Management))--North-West University, Potchefstroom Campus, 2009.
Date January 2008
CreatorsSmit, Charmaine
PublisherNorth-West University
Source SetsNorth-West University
Detected LanguageEnglish

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