ABSTRACT

It is well-known that any risk management activity is a cost to the organization. However, optimized risk management practices satisfy regulatory capital requirements and gain the confidence of investors who take calculated risks. A bank's risk management division will generate a profit if it can develop methodologies to decrease the nonworking regulatory capital. This may be achieved only when the risks are measured using data from internal and external sources in conjunction with scenario analysis. One such method of measuring operational risk (OR) is the advanced measurement approach. This involves quantifying ORs across the various nodes within a bank following the loss distribution approach, in which the frequency and severity distributions of the loss-generating OR events are estimated from the data sources. These distributions are then used to generate the scenarios for frequency and its associated severity for estimating the OR capital. In our approach, the various levels of loss severity are mapped to a percentage of total trade exposure, and the occurrence frequency of an OR event is assumed to follow a binomial distribution.