| Summary: | 碩士 === 東吳大學 === 經濟學系 === 95 === This article studies the bank efficiency considering the operational risk. The research object is 32 banks in Taiwan for the period from 2000 to 2005. The empirical study divides into two stages. In the first stage, we use the GARCH model to estimate the variance of residual of the Top-Down Multi-Factor model, which is used as an operational risk indicator in the efficiency model I. We also use the Basic-Indicator approach to count operational risk capital in order to being operational risk variable in the efficiency model II. In the second stage, we use Battese and Coelli (1995) stochastic frontier cost function to analyze the relationship between two kinds of operational risk variables and the bank efficiency. Moreover, in the inefficiency factorial analysis, in addition to the consideration of two kinds of operational risk indicators, the bank characteristic variables are further taken into consideration, including the capital adequacy rate, loans/assets, the number of branches, bank age and whether joining holding company or not. These variables are employed to analyze the effect on bank operational inefficiency.
The empirical results show that 13 banks in Taiwan have heterogeneity operational risk, and the operational risk will change as time goes by. If the neglect of personnel, improper control or the exterior impact used to occur to banks, then the banks would have higher operational risk exposure value. The banks which develop operational risk management properly, then the exposure value is lower. With regard to the difference and the similarity between the effects of the two operational risk quantification ways on efficiency, the bank efficiency will be lower when facing the operational risk, whether from the perspective of counting the operational risk capital or the direct measure operational risk. The Basic-Indicator approach makes banks have higher operational risk capital, which causes banks in Taiwan worse efficiency performance in average. However, the result of Top-Down computation method shows that banks have better efficiency performance. Furthermore, under two kinds of different operational risk indicators, the ranks of some bank's efficiency are very different, which can be divided into two situations. First, if banks face bigger operational risk impact, the efficiency performances become worse under insufficient operational risk capital. This result explains the shortage of using unit indicator to measure operational risk capital. Second, if banks have higher profit ability, then operational risk capital counted by Basic-Indictor approach is bigger. That causes the ranking of the cost efficiency to fall behind other banks. However, if banks have a good operational risk management conformity mechanism, its operational risk will be lower; therefore the ranking of the cost efficiency will be better.
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