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Evaluating the performance of banking under risk regulations: a slacks‐based Data Envelopment Analysis assessment framework
Author(s) -
Yang ChihChing
Publication year - 2014
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12020
Subject(s) - data envelopment analysis , computer science , profit (economics) , efficiency , empirical research , soundness , industrial organization , deregulation , operational efficiency , business , econometrics , risk analysis (engineering) , economics , macroeconomics , microeconomics , marketing , mathematical optimization , philosophy , statistics , mathematics , epistemology , estimator , programming language
Despite increasing deregulation and globalization in financial markets worldwide, banking is still one of the most regulated industries in many countries. The contribution of the present article is to introduce a slacks‐based Data Envelopment Analysis assessment framework for assessing bank efficiency and soundness in a risk regulation setting, which is missing from the banking performance literature. Two main sub‐processes within the service flow of a typical bank are considered – the primary banking business for making profit and dealing with the compliance requirements of risk regulations. A Data Envelopment Analysis model is applied to measure the performance of the two sub‐processes, that is, profit‐making efficiency and risk‐controlling efficiency. The research framework and models are applied to an empirical study of the banking sector in Taiwan covering the period 2007 – 2010. We demonstrate how to use the empirical results to monitor the efficiency status for individual banks from 1 year to another, providing an early warning for those with low efficiency. Our empirical results show that there is considerable potential for efficiency improvement in Taiwan's banking industry, and the room for risk‐controlling efficiency improvement is even larger. The two efficiency estimates are positively correlated with each other, and both have been improved year by year. However, an economic recession can lower efficiency estimates.