Risk management and managerial efficiency in Chinese banks: A network DEA framework

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractRisk Management in Chinese banks has traditionally been the Cinderella of its internal functions. Political stricture and developmental imperative have often overridden standard practice of risk management resulting in large non-performing loan (NPL) ratios. One of the stated aims of opening up the Chinese banks to foreign strategic investment is the development of risk management functions. In recent years NPL ratios have declined through a mixture of recovery, asset management operation and expanded balance sheets. However, the training and practice of risk managers remain second class compared with foreign banks operating in China. This paper evaluates bank performance using a Network DEA approach where an index of risk management practice and an index of risk management organisation are used as intermediate inputs in the production process. The two indices are constructed from a survey of risk managers in domestic banks and foreign banks operating in China. The use of network DEA can aid the manager in identifying the stages of production that need attention.

The Sustainability Performance of Chinese Banks: A New Network Data Envelopment Analysis Approach and Panel Regression

“…These observations imply that the performance of different commercial banks varies. Furthermore, competition among Chinese banks, along with competition between domestic and foreign banks, has become fierce [1]. To increase competitiveness, it is therefore necessary to improve bank performance in China.…”

“…Second, improving the efficiency of commercial banks is an important part of banking reform in China. Finally, the inefficiency of commercial banks 1 , λ (t) 2 , · · · , λ (t) N ) ∈ R N + and for the second stage the intensity column vector is γ (t) = (γ (t) 1 , γ (t) 2 , · · · , γ (t) N ) ∈ R N + . Assuming that there are H(H > 1) technology-heterogeneous groups and N h DMUs in group h, where for each period we have H ∑ h=1 N h = N. As shown in Figure 1, let x (t) i 1 j , i 1 = 1, 2, · · · , m 1 , denote the original input to the deposit stage in period t. In the deposit stage, each bank produces intermediate products z (t) p (1,2) j (p (1,2) = 1, 2, · · · , q (1,2) ) by using the original input x (t) i 1 j in period t. The undesirable outputs produced in a previous period have the effect of reducing the subsequent period's production possibilities since non-performing loans require the bank to raise more equity Sustainability 2019, 11, 1622 4 of 25 capital or reduce their production of deposits.…”

“…Similarly, we used non-performing loans as undesirable carryovers. The undesirable output from period t − 1 is b (t−1,t) p (2,1) j (p (2,1) = 1, 2, · · · , q (2,1) ), where b (t−1,t) p (2,1) j are undesirable carryovers from the preceding (current) period to the current (subsequent) period and superscripts (1,2) and (2,1) indicate that these indicators are from the deposit (loan) stage to the loan (deposit) stage, respectively. In the loan stage, each bank in period t uses intermediate products z (t) p (1,2) j obtained from the deposit stage and c (t−1,t) p 2 j (p 2 = 1, 2, · · · , q 2 ) to produce output y (t) r 2 j (r 2 = 1, 2, · · · , s 2 ), c (t,t+1) p 2 j and b (t,t+1) p (2,1) j , where c (t,t+1) p 2 j and b (t,t+1) p (2,1) j are desirable and undesirable carryovers from the current period to the subsequent period, respectively.…”

Evaluating Canadian Bank Branch Operational Efficiency from Staff Allocation: A DEA Approach

“…There are a few studies that have compared multiple approaches in bank performance evaluation (Knaup & Wagner, 2012;Lee et al, 2011;Wang et al, 2014;Matthews, 2013;Barros, Managi, & Matousek, 2012); however, there is no simple way to determine which of the various methods best evaluate bank performance. The choice of measurement methods appears to strongly affect the calculated efficiency, and results have shown differences in ranking and inefficient unit percentages depending on the method employed.…”

Relative Efficiency of Canadian Banks: A Three-Stage Network Bootstrap DEA

“…Similarly, Ebrahimnejad et al (2014) considered non-performing loans as a measure of risk and evaluated the performance of the branches of a local bank in the US. Matthews (2013) interviewed 24 banking executives to identify the risks that the banking industry is facing and, accordingly, developed some indexes to measure the risk. Furthermore, they incorporated these indexes in their DEA model and concluded that, in this approach, return on investment can be considered as a proxy for the measured efficiencies.…”