An analysis of the efficiency of Malaysian banks

¶ … Malaysia is characterized by the World Bank as being a middle-income country. Modeled after the Anglo-American system, Malaysian banks are restricted in their operation to accepting deposits, granting loans and other specified activities, and they are kept at an arm's length from corporate governance and management; however, beginning in the 1970s, the soundness of the Malaysian banking system was increasingly compromised by the political leadership's policy that used financial policy as an instrument for inter-ethnic income redistribution. Since 1970, though, the nation has transformed itself from a producer of raw materials into an emerging multi-sector economy with much of the credit for the progress to date being attributed to the country's recent political leadership. An efficient banking system plays an important role in the economic development of any country. Commercial banks, which are the main component of the banking system, have to be efficient otherwise they will create maladjustments and impediments in the process of development in any economy. The purpose of this study was to identify the optimum approach and metrics for measuring the efficiency of Malaysian banks and to analyze archival financial performance data using the optimum approach for measuring the efficiency of Malaysian banks to determine historic efficiency levels in an effort to identify opportunities for improvement in the future.

Table of Contents

1.0

Chapter 1: Introduction

1.1

Problem Statement

1.2

Purpose of the Study

1.3

Importance of the Study

1.4

Rationale of the Study

1.5

Overview of the Study

Chapter 2: Literature Review

2.1. Introduction

2.2 Overview of the Malaysian banking system

2.3. SFA in Malaysia

2.4. SFA in Other Countries

2.5. DFA in Malaysia

2.6. DFA in Other Countries

2.7. DEA in Malaysia

2.8. DEA in Other Countries

2.9. NBIFs Research

2.10 BFIs Research

2.11. Other Research

2.12. Conclusion

Chapter 3: Methodology

3.1. Introduction

3.2. Description of the Study Approach

3.3. Data-gathering Method

3.4. Research Method and Database of Study

3.5. Research Variables

3.6. Research Hypothesis

3.7. Conclusion

4.0. Data Analysis

5.0. Summary and Conclusion

An Analysis of the Efficiency of Malaysian Banks

1.0 Introduction

The past two centuries have been fateful ones for Malaysia. After the United Kingdom established colonies and protectorates in what is modern Malaysia during the 18th and 19th centuries, the mid-20th century witnessed these regions being occupied by Japan during World War II, only to revert to British control after the war (Malaysia 2010). By 1948, other events swept across what is now modern Malaysia when the territories under British control, including Singapore, established the Federation of Malaya until 1957 when they achieved their independence (Malaysia 2010). The modern country of Malaysia was created in 1963, but the country's early history was far from uneventful as well, with fundamental changes in organization taking place that culminated in Singapore's withdrawal from the confederation in 1965 (Malaysia 2010). More recently, a series of economic reforms and an emphasis on diversifying the nation's economic base have succeeded in providing a number of value-added industries for Malaysia that have included manufacturing and services industries, and increasingly, the travel and tourism trade (Malaysia 2010).

Today, Malaysia is characterized by the World Bank as being a middle-income country that has transformed itself from a producer of raw materials into an emerging multi-sector economy with much of the credit for the progress to date being attributed to the country's political leadership. For example, following his accession to office in 2003, former Prime Minister Abdullah attempted to transform the Malaysian economy by introducing initiatives designed to improve the value-added production chain through increased investments in high technology industries, medical technology, and pharmaceuticals; these initiatives have been continued under the nation's current Prime Minister Najib, as well (Malaysia, 2010). The Najib administration has continued to implement initiatives that are intended to increase foreign demand for Malaysian products while increasing the self-sufficiency of the country to reduce the need for high levels of imported goods (Malaysia 2010).

On the one hand, the central bank in Malaysia continues to enjoy solid foreign exchange reserves and the nation's mature regulatory system has reduced Malaysia's exposure to higher-risk financial instruments as well as the lingering global economic downturn (Malaysia 2010). On the other hand, though, the country has not been immune to these economic forces and demand for Malaysia's products in the international community has hampered economic growth for the past two years or so (Malaysia 2010). There are signs, though, that the worst is over and that Malaysian exports and economic growth are on the rebound today. These trends were further amplified most recently in June 2010 when Prime Minister Najib launched the Tenth Malaysia Plan that contained further economic reforms, several of which have already been implemented in order to attract new sources of foreign direct investment in response to a lull in recent years (Malaysia, 2010).

In his book, Financial Liberalization and the Economic Crisis in Asia, Lee (2003) states that compared with other developing countries, Malaysia has a highly developed financial system with its history dating back to the 18th and 19th century British colonial era. Not surprisingly, being one of the legacies of the country's colonial era, the modern Malaysian financial system follows the Anglo-American system in which Malaysian banking operations are limited to accepting deposits, issues loans and other financial services activities that are characteristic of the Anglo-American model (Lee 2003), but this traditional role has expanded in recent years. According to Rao and Tiwari, "Since the process of liberalization and reform of the financial sector were set in motion in 1991, banking has undergone significant changes. The underlying objectives of these were to make the system more competitive, efficient and profitable" (2008:73).

Although there remains a dearth of relevant studies concerning the efficiency of Malaysian banks per se, an earlier study by Katib found that Malaysian banks during the period 1989 to 1995 were not operating efficiently to combine their inputs and on average, technical efficiency languished at just 68 per cent to 80 per cent. Moreover, Katib also determined that banks that had elevated levels of technical efficiency were characterized by lower labor costs, suggesting that efficient Malaysian banks are more conscious of controlling costs than those which are not. Further complicating the analysis of efficiency in Malaysian banks has been their changing role in Malaysian society. For instance, according to Katib and Matthews, "While maintaining its traditional role in financial intermediation, offering the basic banking products and services, banks have been moving towards offering more and more nonbanking financial services" (89). There have been also some signs that political imperatives have adversely affected the ability of the Malaysia banking industry to operate efficiently (Lee 2003), an issue that directly relates to the problem to be considered in this study which is discussed further below.

1.1

Problem Statement

Given the importance of an efficient banking system to a country economic development, it is not surprising that the topic has received a great deal of attention in recent years. For example, according to Katib and Matthews, "Efficiency in the banking sector has the subject of numerous investigations" (89). Moreover, Dietsch and Vivas emphasize that there is a basic lack of research devoted to this issue: "There appears to be only six studies in the efficiency the effects of the expected literature that attempts to determine and compare banking performances differences across-countries" (1996: 3).

Since that writing, though, there have been a number of other analyses concerning how best to define and analyze the efficiency of banks in different countries. For example, in their recent study, "Evaluating Efficiency of Malaysian Banks Using Data Envelopment Analysis," Tahir, Bakar and Haron (2009) emphasize that an efficient banking system is an essential element for the economic development of any country. According to these authorities, "Commercial banks, which are the main component of the banking system, have to be efficient otherwise they will create maladjustments and impediments in the process of development in any economy" (Tahir et al. 2009:96). Since the late 20th century, there have been a number of forces at work that have made efficiency in the commercial banking sector more important than ever, but also more challenging. In this regard, Tahir and his associates emphasize that, "Technological advancements and globalisation have added to the pressure on the part of the banks to maintain market shares so as to survive and remain competitive. Competition from foreign banks as well from domestic banks themselves creates greater pressure" (2009:96). This point is also made by Alam who emphasizes that, "The banking sector is constantly and rapidly evolving; the last two decades, in particular, represent a substantial metamorphosis for banking sectors in countries around the world" (2001:121).

The banking sector in Malaysia has certainly not been immune to these forces as well. Consequently, commercial banks are increasingly being required to remain profitable while simultaneously becoming more efficient in the delivery of banking products and services in an increasingly globalized environment that is characterized by competition from domestic and international sources (Tahir et al. 2009). While all organizations seek to become more efficient in order to improve their performance and therefore their profitability, the importance of an efficient banking system also relates to the need to minimize the spreads between lending and deposit rates that can stimulate increased demands for industrial development loans as well as improved mobilization of financial savings through the banking sector (Ikhide 2000).

1.2

Purpose of the Study

The purpose of this study is two-fold as follows:

1. To identify the optimum approach and metrics for measuring the efficiency of Malaysian banks;

2. To analyze archival financial performance data using the optimum approach for measuring the efficiency of Malaysian banks to determine historic efficiency levels in an effort to identify opportunities for improvement in the future.

1.3

Importance of the Study

The importance of the study directly relates to the need to identify effective ways to measure the efficiency of Malaysian banks. The evaluation of bank efficiency, though, introduces a number of constraints that are related to the nature and function of financial intermediaries, particularly in view of the fact that banks provide products and services that are dissimilar to those found elsewhere. As a result, one of the most important issues involving the investigation the efficiency of the banking sector concerning the specification of discrete bank inputs and outputs, but there remains an ongoing controversy concerning precisely what banks produce (Tahir et al., 2009). In this regard, Kaparakis, Miller and Noulas report that, "Little agreement exists as to what a bank produces or how to measure output" (1994:875). Generally speaking, there have been two conventional approaches used to analyze the banking industry: the production and intermediation approaches. According to Kaparakis and his associates, "The production approach measures outputs by the number of accounts and considers only operating costs. The intermediation approach asserts that banks collect deposits and purchased funds, with the assistance, of course, of labor and capital, and intermediate these funds into loans and other assets" (1994:876). On balance, these authorities suggest that the intermediation approach represents a superior alternative: "It measures outputs by the dollar value of accounts and considers both operating and interest costs. Conceptually, the latter approach seems more appropriate when the sample contains large banks, which fund a larger share of their assets from nondeposit sources" (1994:876). In their study of the efficiency of Islamic banks, Mohamad, Hassan and Bader also weigh in on the production approach. In this regard, Mohamad and his colleagues advise, "In the production approach, banking activities are described as the production of services to depositors and borrowers. Traditional production factors, land, labour and capital, are used as inputs to produce desired outputs. The production approach views banks as producers of loan and deposit services using capital and labour. However, majority of the recent empirical research of banking efficiency are based on the intermediation approach" (2006:107).

Whichever approach is used to identify a bank's products, there remains a need to determine how efficiently it is producing them. Therefore, the importance of the study also relates to the need for an informed approach to banking regulation to maintain the economic recovery that is taking place in Malaysia. In this regard, Karim emphasizes that, "How the increased competitive pressures will affect banks depends in part on their ability to adapt and operate efficiently in the new environment. Banks that fail to do so will be driven off the market by the more efficient ones. That is, the most efficient banks will have a competitive advantage" (2001:289).

1.4

Rationale of the Study

Today, Malaysia stands at an important juncture in its economic development. For example, a study by Desa (2003) points out that, "The message is clear, which is even louder after the recent financial crisis of the banking sector in 1997. Commercial banks in Malaysia will have to review the way they have been doing business in the past and . . . understand the internal and external factors which influence their profitability performance" (p. iv). On the one hand, the World Bank's most recent analysis of the Malaysian economy found that it has been experiencing a solid recovery with economic growth projected to reach a respectable 5.7 per cent in 2010 as a result of increased domestic private consumption and investment (Schellekens, 2010). On the other hand, though, the ability of the country to continue this pattern of growth during a period of global economic downturn represents one of the primary near-term risks (Schellekens, 2010).

Other issues are also at work that make the study of banking efficiency an important issue today. For instance, Katib and Matthews emphasize that, "In this changing environment, the measurement of efficiency in the banking sector becomes pivotal and more complex. For the banking institutions themselves, efficiency analysis helps to appraise their performance" (2003:89). Likewise, Schellekens emphasizes that for Malaysian banks, another issue "is whether private sources of growth can lead the recovery once fiscal and monetary policy support unwinds. The medium-term growth outlook is favorable, with growth at 5.3 per cent in 2011 and 5.6 per cent in 2012. These forecasts price in gradual structural reform implementation as well as fierce external competition for trade, talent, and foreign direct investment" (2010:3). Taken together, the foregoing issues create an environment in which the investigation and analysis of the efficiency of Malaysian banks represents a timely and valuable enterprise and the organization of the study that will achieve these goals is discussed further below.

1.5

Overview of the Study

The study used a five-chapter format to achieve the above-stated research purpose. Chapter one was used to introduce the topic under consideration, including a statement of the problem, the purpose and importance of the study, as well as its supporting rationale. Chapter two was used to provide a critical review of the relevant and peer-reviewed literature concerning banking efficiency in general and the efficiency of Malaysian banks in particular, and chapter three presents the study's methodology, a description of the study approach, the data-gathering method and the database of study consulted. Chapter four consists of an analysis of the data developed during the research process and chapter five was used to present the study's conclusions, as well as a summary of the research.

2.0 Literature Review

2.1.

Introduction

This chapter delivers a review of the related literature to provide an overview of the Malaysian banking industry, and a discussion concerning the stochastic frontier approach that has been used to evaluate the efficiency of banks in Malaysia and other countries. The foregoing is followed by a similar analysis concerning the distribution-free approach and data envelopment approach for banks in Malaysia and other countries. A discussion concerning the non-bank financial institution research that has been conducted in Malaysia in recent years is followed by a summary of other research that has been conducted in this area. Finally, a summary of the literature review is provided in the chapter conclusion.

2.2

Overview of the modern Malaysian banking industry

Unlike the so-called "Asian Tigers" that suffered greatly during the Asian monetary crisis during the 1990s, the commercial banking industry in Malaysia managed to avoid many of the problems its neighbors in the region experienced and has enjoyed significant growth in recent years. In this regard, Stewart reports that, "Malaysia was markedly less afflicted by the regional economic crisis than Thailand and Indonesia. However, the paper wealth of the country had been halved, some companies, mainly in the service industries, were shedding staff, civil servants faced restrictions on overseas travel and bonus payments to workers were on hold" (2003:44). After the completion of the consolidation program by Bank Negara Malaysia following the Asian monetary crisis and the elimination of merchant banks from the Malaysian banking sector, the commercial banking industry in Malaysia currently consists of 22 financial institutions; nine of these institutions (or about 41 per cent) are domestically-owned and 13 (or about 59 per cent) are foreign-owned as shown in Table 1 below.

Table 1

List of commercial banks currently competing in Malaysia

Bank Name

Ownership

Affin Bank Berhad

Domestic

Alliance Bank Malaysia Berhad

Domestic

AmBank (M) Berhad

Domestic

Bangkok Bank Berhad

Foreign

Bank of America Malaysia Berhad

Foreign

Bank of China (Malaysia) Berhad

Foreign

Bank of Tokyo-Mitsubishi UFJ (Malaysia) Berhad

Foreign

CIMB Bank Berhad

Domestic

Citibank Berhad

Foreign

Deutsche Bank (Malaysia) Berhad

Foreign

EON Bank Berhad

Domestic

Hong Leong Bank Berhad

Domestic

HSBC Bank Malaysia Berhad

Foreign

J.P. Morgan Chase Bank Berhad

Foreign

Malayan Banking Berhad

Domestic

OCBC Bank (Malaysia) Berhad

Foreign

Public Bank Berhad

Domestic

RHB Bank Berhad

Domestic

Standard Chartered Bank Malaysia Berhad

Foreign

The Bank of Nova Scotia Berhad

Foreign

The Royal Bank of Scotland Berhad

Foreign

United Overseas Bank (Malaysia) Berhad

Foreign

Source: Monthly Statistical Bulletin, Bank Negara Malaysia, July 2009

According to Elyor (2009), the fact that a majority of the commercial banks that are competing in Malaysia today has some important positive as well as negative consequences for the industry in general. In this regard, Elyor notes that, "The presence of foreign banks in a domestic financial landscape has positive as well as negative implications, particularly for a developing economy. [F]oreign banks' presence contributes positively in the development of a strong and stable domestic banking industry" (2009:15). In addition, the foreign banks that are operating in the Malaysian banking sector today provide the impetus for domestic banks to improve their efficiency in order to remain competitive. As Elyor concludes, "The comparatively more efficient foreign banks which adopt cutting-edge technology in their banking services create competitive pressure on the domestic banks, resulting in positive spill-over effects on the banking industry in general" (Elyor 2009:16). Consequently, the banking industry in Malaysia was in a relatively solid position when the Asian monetary crisis struck the region, but it is also worthwhile emphasizing at the outset as well that Malaysia's experience differs in several ways from those of other East Asian economies that were most severely affected by the Asian monetary crisis during the closing decade of the 20th century (Lee 2003).

According to Lee, although administrative constraints adversely affected the financial liberalization process in Malaysia over the past two decades, the economic problems that were confronting Malaysia during the Asian monetary crisis were not considered to be as severe as in other parts of the region (Lee 2003). Likewise, notwithstanding the fact that the Malaysian banking system was responsible for facilitating the level of price inflation at the time through the issuance of property loans and share purchases, Malaysian banks and enterprises did not enjoy the same level of access to foreign capital as their counterparts in other countries in the region that were more adversely affected by the crisis (Lee 2003). Moreover, foreign bank loans did not play as significant a role in the Malaysian crisis as elsewhere in the region; rather, capital market flows, particularly those into and out of the stock market, were more discernible (Lee 2003). The penultimate reason the Asian monetary crisis was not felt as severely in Malaysia as elsewhere in the region was a result of its minimal exposure to private foreign bank capital and Malaysia was not required to petition the International Monetary Fund (IMF) or other international financial services organizations to obtain emergency international credit facilities (Lee 2003). Finally, during the period from late 1997 and once again from mid-1998, authorities in Malaysia intentionally opted for what Lee describes as "unconventional measures in response to the deteriorating situation, with rather mixed results" (2003, p. 106).

As shown in Table 2 below, Malaysian banks tend to be conservative, primarily extending loans on the basis of collateral rather than the viability of a given project (Hing 1987).

Table 2

Distribution of Malaysian bank credit for select purposes, 1966-96 (per centage)

Years

Manufacturing

Property*

Shares

Agriculture

1966-1970

2.6

8.8

-9.2

1971-1975

8.5

17.0

8.6

1976-1980

18.8

22.5

1.8

7.1

1986-1990

21.1

32.0

1.8

6.5

1991-1996

22.6

30.5

3.8

2.9

*Note: Property includes loans for building, construction, real estate and housing.

Figure 1. Distribution of Malaysian bank credit for manufacturing, 1966-96 (per centage)

Figure 2. Distribution of Malaysian bank credit for property, 1966-96 (per centage)

Figure 3. Distribution of Malaysian bank credit for shares, 1966-96 (per centage)

Figure 4. Distribution of Malaysian bank credit for manufacturing, 1966-96 (per centage)

Source: BNM Quarterly Economic Bulletin and Annual Report, various issues cited in Lee 2003: 111

As shown in the series of figures above, the emphasis on the security of loans has meant that Malaysian banks have preferred to extend loans to the real property sector as well as for share purchases and consumption instead of production during periods in which the property and stock markets have been upward moving. In fact, only about 25 per cent of Malaysian commercial bank loans were extended to agriculture, manufacturing and other industries that produced outputs (Griffith-Jones, Gottschalk & Cailloux 2003). According to these authors, "This modest share for productive investments is likely to be even smaller for foreign borrowings, most of which have been collateralized with assets such as real property and stocks" (Griffith-Jones et al. 2003:113).

The dearth of motivational factors to compel the Malaysian banking industry to prefer long-term lending for productive investments represents an important factor that has contributed to the relatively limited development of the Malaysian manufacturing sector, particular in non-resource-based export-oriented industries that are primarily controlled by foreign investors (Griffith-Jones et al. 2003). Citing the results of a study by Chin and Jomo (2003) that determined that export-oriented manufacturing represents a miniscule proportion of the overall total outstanding loans that have been made by commercial banks in Malaysia, Griffith-Jones and her associates emphasize that, "With the exception of export credit and some relatively minor financial institutions, there is little evidence that the government has used financial policy as an instrument for promoting industry" (2003:113).

According to Lee, an analysis of private investment trends in Malaysia by Bank Negara Malaysia determined that the unavailability of bank credit for the Malaysian manufacturing sector resulted in this sector increasingly depending on funds that were generated internally. The Bank Negara Malaysia study determined that, "On average, surveyed firms financed 52 to 66 per cent of their capital expenditure from internally generated funds during 1986-90, while bank financing accounted for only about 10-14 per cent. Although banks still provided a larger share of external finance than the capital market (ranging from 1 to 8 per cent), this probably reflected the less-developed state of the capital market relative to the banking system at that time" (Lee 2003:112).

In addition, the analysis by Lee also determined that the size of the company was also found to be an important factor concerning whether a company was able to obtain credit from Malaysian banks, and on average, larger enterprises were able to secure loans at lower credit costs. In this regard, "This could be due to the fact that financial institutions imposed less stringent requirements for loans to larger companies since they had better track records and reputations than did smaller companies (Zainal et al. 1994: 313 cited in Lee at 112). Although these findings have not extended to more recent studies, the recessionary period under investigation by Zainal et al. (1985-1986) showed that this tendency was more pronounced and the "average cost of credit for large companies was almost 11 per cent lower compared to that charged for small and medium-sized companies, if they were able to secure credit at all (Lee 2003).

These findings as well as other studies into the efficiency of commercial banks clearly indicate that there are a wide range of factors that must be taken into account in determining the efficiency of the banking sector and what impact varying levels of efficiency has on the larger society in which they compete. According to Katib and Matthews, "Research in [the efficiency of the banking sector] has developed in two separate directions, namely the parametric approach using econometric techniques and the nonparametric approach which utilizes the linear programming method" (2003:89). These methods are described further below as they apply to other countries in general and Malaysia in particular.

2.2.

Distribution-free approach in Malaysia

Despite an exhaustive search of the literature and available studies, there were no relevant investigations of the efficiency of Malaysia banks using the distribution-free approach. However, According to Tahir et al., "In the distribution-free approach (DFA), a functional form for the frontier is also specified but inefficiencies are separated from random error in a different way. Unlike the SFA, the DFA makes no strong assumptions regarding the specific distributions of the inefficiencies or the random errors" (2009:97). The distribution-free approach has been used to analyze the efficiency of the banking sector in other countries, and these studies are discussed further below.

2.5.

Distribution-free approach in other countries

According to Balling and his associates, "The distribution-free approach requires a constant level of efficiency over time that, in the case of transition economies, is difficult to assume" (2004:231). Despite these constraints, the distribution-free approach (DFA) to analyzing the efficiency of banks was used by Berger (1993) in an assessment of the banking industry in the United States. In the Berger study, it was determined that frequency distribution of inefficiencies was likely closer to the shape of symmetric normal distribution than an asymmetric half-normal distribution. A subsequent study by Berger and Mester (1997) also used the distribution-free approach in combination with the stochastic frontier approach for both the translog and the Fourier specification of the cost and profit function of the banks being analyzed and determined that the empirical findings in terms of either average industry efficiency or ranking of individual banks are similar across methods. Similarly, Taci (2000) examined the cost efficiency of the Czech financial sector relative to the ownership structure, size, and performance status of banks using the distribution-free approach in a cross-sectional estimation and fixed effects approach in panel data estimation.

2.6.

Data envelopment analysis in Malaysia

As with the other analytical approaches to determining the efficiency of the banking industry, the use of the data envelopment method has received far less attention than the importance of the subject matter would indicate. In this regard, Leong, Dollery, and Coelli note that, "Over the past two decades, the measurement of financial institution efficiency using nonparametric frontier models has received considerable attention. However, while the literature on the application of data envelopment analysis (DEA) to the area of bank efficiency measurement is burgeoning, research on the salient properties of efficiency scores as a tool of policy is comparatively rare" (2003:195). This absence can be attributed, in some part, to the recent introduction of the methodology itself. For instance, according to Katib and Matthews, "The early development of the use of linear programming to examine efficiency measures was that of Charnes, Cooper and Rhodes (1978-1981). Their approach, properly known as data envelopment analysis (DEA) was developed initially to evaluate efficiencies in public sector agencies and nonprofit organizations" (2003:92). This point is also made by Tahir et al. who note, "DEA is based on the concept of efficiency that has been widely used in engineering and the natural sciences to measure the amount of work performed by a machine in relation to the amount of energy consumed in the process. The concept of DEA is similar to that of technical efficiency in the microeconomic theory of production" (2009:11).

The primary difference relates to the fact that the DEA production frontier is not developed through the use of a specific equation; rather, the DEA production frontier is developed using the actual data that can be located for the banks being studied. Consequently, Tahir et al. point out that, "The DEA efficiency score for a specific firm is defined not by an absolute standard but is relative to the other firms under consideration. This feature differentiates DEA from parametric approaches which require a specific functional form. DEA also assumes that all firms face the same unspecified technology, which defines their production possibility set" (2009:11).

While the variables used in this approach differ from study to study, the primary goal of a DEA analysis is to identify which banks are functioning on their efficient frontier and those that are failing to do so (Tahir et al. 2009). According to these authorities, "If the firm's input-output combination lies on the DEA frontier, the firm is considered efficient; and the firm is considered inefficient if the firm's input-output combination lies inside the frontier" (Tahir et al. 2009:12).

According to Jayadev and Sensarma, "The two important issues examined by several academic studies relating to bank mergers are: first, the impact of mergers on operating performance and efficiency of banks and second, analysis of the impact of mergers on market value of equity of both bidder and target banks" (2007:21). To this end, a study by Sufian (2004) used the non-parametric frontier approach, data envelopment analysis, to analyze the efficiency of domestic banks operating in Malaysia during the merger year as well as during pre- and post-merger periods. This researcher determined that for the period under investigation, 1998-2003, Malaysian banks demonstrated an impressive overall efficiency level of 95.9 per cent, reflecting a minimal waste of inputs of just 4.1 per cent. According to Sufian, these findings "suggest that the merger programme was successful, particularly for the small and medium sized banks, which have benefited the most from the merger and expansion via economies of scale" (2004:53). However, Sufian also points out that these findings "suggest that the larger banks should shrink to benefit from scale advantages. Decision-makers hence ought to be more cautious in promoting mergers as a means to enjoying efficiency gains" (2004:53).

2.7.

Data envelopment analysis in other countries

A cross-country study of Islamic banks operating in 35 different countries using the data envelopment approach that was conducted by Brown and Skully (2003) found that on average, the most cost-efficient banks were competing in the Middle East region. Another study by Lin used the data envelopment analysis of the non-parametric approach to examine the efficiency of banks in Taiwan because this analytical approach "is not subject to fixed function patterns and huge sample limitations and capable of measuring the diversified input and output items, hence it is very convenient for empirical studies. Banks have diversified inputs and outputs, hence the DEA was used to measure the operating efficiency of banks" (2002:334).

The data envelopment analysis approach was used by Berg, Forsund, Hjalmarssonc and Suominen to study the efficiency of the banking sector in Norway, Sweden, and Finland. According to Berg and his colleagues, "The analysis produces a detailed account of how well banks from different countries and different sizes may be prepared to meet the more intense competition of a common European banking market" (1993:371). These researchers used three outputs (i.e., total loans, total deposits, and number of branches) and two inputs (i.e., labor, measured in man-hours per year, and capital, measured by book values of machinery and equipment). Berg et al. also used Malmquist indices to describe the regional productivity differences. The results of the Berg et al. analysis found that the most efficient Swedish banks were the largest ones, and they concluded that these larger institutions were in a better position to expand in the future (Berg et al. 1993).

A study by Pastor, Perez, and Quesada (1997) used the data envelopment method to analyze the productivity, efficiency, and differences in technology of various European and U.S. banking systems. To accomplish their DEA analysis, Pastor and his associates employed loans, deposits, and short-term as well as equity investments as their outputs and non-interest expenses, besides personnel expenses, as their inputs. The results of the Pastor et al. analysis found that France, Spain, and Belgium enjoyed the most efficient banking systems, while the United Kingdom, Austria, and Germany experienced the least efficient banking systems (Pastor et al. 1997). From a productivity perspective, the Malmquist indices showed that banks in Austria, Italy, Germany, and Belgium were more productive compared with those in the United States, the United Kingdom, France, and Spain (Pastor et al. 1997).

A study by Casu and Molyneux (2003) used the data envelopment approach to analysis the productivity efficiency of European banking systems in an effort to determine whether the sector had improved and converged towards a common European frontier during the period 1993 through 1997. The countries used in this analysis were France, Germany, Italy, Spain and the United Kingdom. All data were reported in ECU as the reference currency (Casu & Molyneux 2003). The results of this DEA analysis found relatively low average efficiency levels, but the researchers suggested that it was possible to discern a slight improvement in the average efficiency scores over the period of analysis for almost all banking systems in the sample, with the single exception of Italy (Casu & Molyneux 2003).

A study by Fernandez, Gascon and Gonzalez analyzed the economic efficiency of 142 financial intermediaries from eighteen countries over the period 1989-1998 and the relationship between efficiency, productivity change and shareholders' wealth maximization (2002). These researchers used the data envelopment approach to estimate the relative efficiency of commercial banks of different geographical areas (i.e., North America, Japan and Europe); the European banks studied by Fernandez and his associates were located in Austria, Belgium, Denmark, Finland, Germany, Ireland, Italy, Luxemburg, Norway, Portugal, Spain, Sweden, Switzerland and the United Kingdom (Fernandez et al. 2002). In their use of the DEA model, Fernandez et al. used three preferred outputs (i.e., total investments, total loans, and non-interest income plus other operating income); the four input variables used in this study were property, salaries, other operating expenses and total deposits (Fernandez et al. 2002). The values for all of these variables were expressed in terms of billions of U.S. dollars. The results of the Fernandez et al. analysis found that commercial bank productivity in the countries studied had significantly increase (19.6 per cent) during the period from 1989 to 1998. The researcher attributed this increased productivity primarily to relative efficiency improvement, with technological innovations having just a moderate impact (Fernandez et al. 2002).

A summary of the key findings from numerous studies of banking efficiency in different European countries using the different analytical methods reviewed above is provided by Weill (2002) which are recapitulated in Table 3 below.

Table 3

Summary of banking efficiency studies for five European countries

Methodology/No. Of Banks/Time Period

Findings

France

DFA, cost efficiency, 375 banks, 1988-92

Mean cost efficiency 40.6 per cent-70.7 per cent

DEA, technical efficiency, 93 banks, 1994

Mean technical efficiency 78-91 per cent. No clear relation with size. Cooperative and savings banks more efficient than commercial banks.

DFA, cost efficiency, 223 banks, 1988-92

Mean cost efficiency 88 per cent.

DEA, technical efficiency, 38 banks, 1994-97

Mean technical efficiency: 89-95 per cent

SFA and DFA, cost efficiency, 32 banks, 1988-92.

Mean cost efficiency 73.4 per cent (small banks)

and 84.3 per cent (large banks)

DEA, technical efficiency, 67 banks, 1992

Mean technical efficiency 95 per cent

SFA and DFA, cost and profit efficiency, 190 banks, 1993-97.

Mean cost efficiency 82.36 per cent, mean profit efficiency 88.38 per cent

Germany

SFA, cost efficiency, 1425 banks, 1989-92

Mean cost efficiency 90 per cent. Lower efficiency for commercial banks

SFA and DFA, cost and profit efficiency, 7539 bank observations, 1989-96

Mean cost efficiency: 81.3-86.6 per cent

Mean profit efficiency: 78.1-82.1 per cent

Higher cost efficiency for cooperative and savings banks than for commercial banks

SFA and DFA, cost efficiency, 38 banks, 1988-92

Mean cost efficiency 87.6 per cent (small banks)

and 87.7 per cent (large banks)

DEA, technical efficiency, 22 banks, 1992

Mean technical efficiency 65 per cent

SFA and DFA, cost and profit efficiency, 1052 banks, 1993-97

Mean cost efficiency 84.2 per cent, mean profit

efficiency 95.91 per cent

Italy

SFA and DEA, cost efficiency, 270 banks, 1988-92.

SFA: mean cost efficiency 69.6 per cent, negative relation with size. DEA: mean cost efficiency 68.2 per cent, relation with size: positive if variable returns-to-scale, no significant if constant returns-to-scale.

SFA and DFA, cost efficiency, 85 banks, 1988-92.

Mean cost efficiency 84.9 per cent (small banks) and 79.9 per cent (large banks).

SFA and DFA, cost efficiency, 85 banks, 1988-92.

Mean cost efficiency 84.9 per cent (small banks) and 79.9 per cent (large banks).

DEA, technical efficiency, 31 banks, 1992

Mean technical efficiency 77.3 per cent.

SFA and DFA, cost and profit efficiency, 178 banks, 1993-97

Mean cost efficiency 88.73 per cent, mean profit

efficiency 64.73 per cent

Spain

TFA, profit efficiency, 54 savings banks, 1986-91

Mean profit efficiency 72 per cent.

DEA, Malmquist productivity index, 77 savings banks, 1986-91

Mean technical efficiency 75-80 per cent

DFA, cost efficiency, 101 banks, 1988-92

Mean cost efficiency 88 per cent

SFA and DFA, cost efficiency, 52 banks, 1988-92

Mean cost efficiency 79.8 per cent (small banks) and 85.5 per cent (large banks)

DEA, technical efficiency, 59 banks, 1992.

Mean technical efficiency 82.2 per cent

Switzerland

SFA and DEA, cost efficiency, 477 banks, 1987-91.

SFA: mean cost efficiency 3.9 per cent, negative relation with size. DEA: mean cost efficiency 56 per cent, positive relation with size.

SFA and DFA, cost efficiency, 53 banks, 1988-92.

Mean cost efficiency 83.4 per cent (small banks) and 87 per cent (large banks)

Source: Weill 2002:4

As can be seen in Table 3 above, the results of these studies of European banking efficiency differed in their analytical approach but arrived at comparable results, particularly as they related to the effect of size on a given bank's profit and technical efficiency.

2.8.

Non-bank financial institutions research.

According to Tahir and his colleagues, there are some important reasons for analyzing non-bank financial institutions as follows:

1. Banks offer assets (deposits) that claim to be capital certain. If this promise is to be honored, then there must be limits to the range and nature of assets that a bank can reasonably take on to its balance sheets. Notwithstanding the existence of universal banking in many parts of the world (i.e., banks also engaged in securities market activities), this consideration implies that bank-based financial system will tend to have a smaller range of equity-type assets than those with a more broadly-based structure including a wide range of NBFIs. More generally, NBFIs play range of roles that are not suitable for banks and through their provision of liquidity, divisibility, informational efficiencies, and risk pooling services, they broaden the spectrum of risks available to investors. In this way, they encourage and improve the efficiency of investment and savings. Through the provision of a broader range of financial instruments, they are able to foster a risk management culture by attracting customers who are least able to bear risks and fill the gaps in financial services that otherwise occur in bank-based financial systems.

2. From the view of financial stability, in a financial sector in which NBFIs are comparatively undeveloped, banks will inevitably be required to assume risks that otherwise might be borne by the stock market, collective investment schemes or insurance companies. However, there is basic incompatibility between the kinds of financial contracts offered by the banks and those offered by the financial institutions. Thus, banks are more likely to fail as a result (2009:10).

Because the Malaysian banking sector has been characterized by an amplification of the types of services it offers in recent years, NBFIs represent a potential safety valve that can help minimize the consolidation of risky accounting practices that can result in skewed perceptions of the viability of banks. In this regard, Tahir and his associates conclude that, "One way of minimizing financial fragility in the developing economies may be to encourage a diversity of financial markets and institutions, where investors are able to assume a variety of risks outside the banking system itself. Without this diversity, there is a tendency for all risks to be bundled within the balance sheet of the banking system, which may lead to severe financial crises more likely" (2009:10).

2.9.

Other research

Although the foregoing analytical approaches to determining the efficiency of banks are the most common for the reasons specified, there are other approaches available as well. For instance, Balling, Lierman and Mullinax report that, "A growing number of international comparative studies use banking system efficiency scores for various countries, including transition economies, to derive policy recommendations and analyze different aspects of financial structure architecture or performance" (2004:232). These authors also note that whatever analytical approach is used, there remains a lack of consensus concerning what types of input and output variables are most effective for determining efficiency in the banking sector (Balling et al. 2004). According to Balling and his associates, "Inputs and outputs in banking can be specified using either the assets (or intermediation) approach, the user-cost approach or the value-added (or production) approach" (2004:233). There has been a growing tendency among many researches to employ the intermediation approach that treats deposits as inputs and defines loans and investments as outputs; researchers using this approach regard interest on deposits as being part of total costs (Balling et al. 2004).

According to Finneran, yet another approach to measuring the efficiency of the banking sector is to use the efficiency ratio. In this regard, Finneran notes that, "The efficiency ratio is the traditional measure for bank productivity. At its simplest, it is the cost required to generate each dollar of revenue. Its simplicity is an advantage, but the ratio always needs a business context, and consideration of the complicating factors" (2006:2). There are two approaches available for calculating a bank's efficiency ratio. The first and most commonly used is the cost to revenue ratio. As Finneran puts it, "This measures non-interest expenses as a proportion of operating revenue. Costs include salaries, technology, buildings, supplies, and administrative expenses. Revenue includes net interest income (interest revenue less interest expenses) plus fee income" (2006:3). The second approach is to use the cash efficiency ratio that is calculated by deducting the amortization of intangible assets from noninterest expenses before calculating the efficiency ratio described above (Finneran 2006). Following this step, the efficiency ratio must be interpreted. According to Finneran, "A bank's non-interest expense level reflects its efficiency in converting inputs into revenue. A cost to revenue ratio of 50 per cent, or below, is admired. A less efficient bank will have a higher efficiency ratio, say, 70 per cent and above. So, all other things being equal, a low efficiency ratio is good" (2006:4). Similarly, Allen and Gale report that, "The large literature on the efficiency of the banking industry is mostly concerned with the cost- and profit-efficiency of retail banking. For example, [researchers] summarize the evidence as suggesting that the average bank operates at a cost level that is 10 per cent or 20 per cent above the best-practices level. This is just one (probably small) part of the total costs of deviations from perfect competition. Unfortunately, the total costs of a deviation from perfect competition have not been documented as carefully as the costs of financial instability" (2004:454).

In his book, Financial Intermediation in the 21st Century, Mikdashi also notes that a significant number of studies have sought to measure standard returns to scale or scope in banking in recent years; by and large, these studies "have concluded that they are exhausted at a relatively small scale and are not the source of a very large cost advantage. Specifically, most studies have failed to find evidence of scale economies for banks above $25 billion in asset size and they have generally found differences in unit costs attributable to sizes smaller than 10 per cent" (Mikdashi 2001:213).

A study by Mahesh and Rajeez determined that the effect of deregulation on various sectors of the banking industry as it relates to their efficiency has been found to be highly varied in different countries. According to these authors, "While in countries like Australia, Spain, Turkey and Norway, financial liberalisation has positively affected the efficiency and productivity of commercial banks; for Italy, the United States and others, banking efficiency was relatively unchanged after deregulation. Surprisingly, in Korea, productivity of the banking sector has declined after deregulation" (2008:7). In addition, an analysis of 130 studies conducted by Berger and Humphrey (2000) of financial institutions in 21 countries found that the overall effect of deregulation on the efficiency of banks has been mixed. This issue was also examined by Gupta and Lensink in their text, Financial Liberalization and Investment, wherein the authors report that, "Another important issue with respect to the effects of financial deregulation relates to the effects of changes in banking efficiency on private investment. It has been argued that a high spread between deposit and lending rates reflects high cost of financial intermediation and, therefore, lower banking efficiency" (1996:6).

A study of banking efficiency by Evanoff and Ors used as its primary measure of bank performance the cost X-efficiency which is obtained through an analysis of empirical estimates of a minimum-cost frontier for the population of banks under investigation. According to these researchers, "X-efficiency analysis, a standard benchmarking tool in empirical industrial economics, has been used in a large number of studies that examine the banking industry. The X-efficiency benchmark is our preferred method because it encompasses both technological and allocative efficiencies at the firm level. A technologically efficient bank would produce with minimum amounts of inputs given the level of outputs, or, equivalently, would produce the maximum amount of outputs for the given level of inputs" (2008:897). Banks with allocative efficiency would use an appropriate mix of inputs and outputs based on the prices it encounters in its respective market. Consequently, Evanoff and Ors conclude that, "The empirical cost X-efficiency measure accounts for differences in the prices of inputs that the banks (which are price takers operating in competitive markets) face in their local markets, differences in the levels of outputs that they choose to produce, and differences in the fixed-netputs (such as different forms of capital) that banks can only change in the long-term" (2008:898). An alternative approach to the foregoing is to simply employ accounting ratios for the efficiency analysis; accounting ratios, though, Evanoff and Ors caution, "presume that all else (i.e., input prices, output, and fixed-netput levels) is equal across banks when, in fact, they are not. This could result in significant benchmarking errors" (2008:898).

In his study of banking efficiency in Europe, Vennet (2002) notes that a significant amount of research has been devoted to the measurement of X-efficiency of financial institutions in recent years. For example, Vennet cites the Berger and Humphrey (1997) survey of 130 studies concerning efficiency that employed data from 21 different countries across a number of time periods, from different types of financial institutions including banks, savings institutions, and insurance companies, and that employed various efficiency concepts and measurement methods. The results of this comprehensive survey of financial institutions found that by and large, the average inefficiency in banking is placed between 20-25 per cent of total costs. Citing research by Berger, Hancock, and Humphrey (1993), Vennet also notes that larger banks tend to be more efficient; because there is a wide range of disparities between banks of similar size, though, these researchers also caution that the manner in which individual banks are operated is much more salient to an efficiency analysis than their respective types of organization or size, as such. It should also be pointed out that these data were derived primarily from banks in the United States and did not making any explicit distinction between universal and nonuniversal banks (Vennet 2002). In sum, Vennet concludes that, "The data on economies of scale and scope and X-efficiency indicate some advantage for universal banks over specialized banks. However, considering that specialized banks are able to survive in direct competition with universal banks, the author concedes that the efficiency advantages of neither form of banking appear to be overwhelming. Clearly, a more direct assessment of efficiency in universal vs. nonuniversal banks is needed" (2002:255).

Finally, Rutherford states that the efficiency of a bank is "a measure of a bank's effectiveness in using the money available to it. This can be assessed by the 'mark-up' between interest rates, i.e. either the ninety-day bank time deposit day rate minus the prime rate of interest or the bank demand deposit rate minus the bank prime rate. Mark-ups are similar within one country but differ between countries" (1995:30).

2.10.

Conclusion

The research showed that the efficiency of banks can be measured in a number of different ways but the results of these analyses depend in large part on the accuracy of the data inputs that are used for these measurements. In some cases, accurate and timely data are either unavailable or remain proprietary, making the efficiency analysis problematic. Furthermore, identifying appropriate inputs and outputs remains an area of controversy among researchers interested in determining the efficiency of banks. Moreover, all of the analytical methods reviewed in this chapter were marred by different types of constraints or weaknesses compared to others, while each had its own respective strengths. The selection of an appropriate analytical approach, then, depends in large part on what timely and accurate information is available and these issues are discussed further in chapter three below.

3.0

Methodology

3.1.

Introduction

This chapter describes more fully the study approach to be used in this study, the data-gathering method that will be used, the research method and database of study to be consulted, and the research variables that will be used. The study's guiding research hypothesis is also presented, following by a chapter conclusion.

3.2.

Description of the Study Approach

As noted in chapter two above, there are numerous ways to evaluate the efficiency of the banking sector in a country, but no one approach appears to be the absolute best for all purposes and settings. In fact, all of the methodologies reviewed had their own respective strengths and weaknesses, and researchers have arrived at starkly different results even using the same analytical approaches for the same banking sectors. This diversity of findings suggests that measuring bank efficiency must proceed with caution and the results interpreted based on the best available information. According to Sathye, "It is usual to measure the performance of banks using financial ratios. The major demerit of this approach is its reliance on benchmark ratios. These benchmarks could be arbitrary and may mislead an analyst. Further, financial ratios do not capture the long-term performance, and aggregate many aspects of performance such as operations, marketing and financing" (2000:6). As noted in the preceding chapter, there has been a growing trend towards studying bank performance and efficiency through the use of one of the frontier analysis methods. In this regard, Sathye notes that, "In frontier analysis, the institutions that perform better relative to a particular standard are separated from those that perform poorly. Such separation is done either by applying a non-parametric or parametric frontier analysis to firms within the financial services industry. The parametric approach includes stochastic frontier analysis, the free disposal hull, thick frontier and the Distribution Free Approaches (DFA), while the non-parametric approach is Data Envelopment Analysis (DEA)" (2000:6). In this regard, Sengupta reports that, "In a relatively short period of time Data Envelopment Analysis (DEA) has grown into a powerful quantitative, analytical tool for measuring and evaluating performance. It has been successfully applied to a host of different entities engaged in a wide variety of activities in many contexts worldwide" (2005:xi). Likewise, Data Envelopment Analysis (DEA) is an increasingly popular management tool. DEA is commonly used to evaluate the efficiency of a number of producers. A typical statistical approach is characterized as a central tendency approach and it evaluates producers relative to an average producer. The efficiency is simply the ratio of the inputs to the outputs" (Data Envelopment Analysis 2003: 147).

Based on its perceived advantages, the study approach that was used in this study employed the data envelopment analytical approach. The use of the data envelopment analytical approach has several advantages over other approaches for determining the efficiency of banks. For example, in his book, Modern Methods for Business Research, Marcoulides reports that, "Data Envelopment Analysis (DEA), can be successfully applied to assess performance of units utilizing multiple inputs to produce multiple outputs. DEA can also be applied when the input-output transformation is not known, or when accounting and financial ratios are of little value, and it enjoys a number of advantages over the traditional ratio analysis approach and other parametric approaches to assessing performance" (1998:122).

Furthermore, Marcoulides emphasizes that this methodology has become increasingly popular in recent years. According to Marcoulides, "A plethora of methodological enhancements to DEA have been made over the last few years by researchers in North America, Europe, and elsewhere. As a result, DEA applications were soon widely spread in different industries such as banking" (1998:122). Likewise, Banker and Morey note that, "Data Envelopment Analysis has now been extensively applied in a range of empirical settings to identify relative inefficiencies, and provide targets for improvements. It accomplishes this by developing peer groups for each unit being operated. The use of categorical variables is an important extension which can improve the peer group construction process and incorporate 'on-off' characteristics, e.g., presence of drive-in window or not in a banking network" (1986:1613). The data envelopment approach also significantly strengthens the credibility of the findings derived from such analyses (Banker & Morey 1986).

3.3.

Data-gathering Method

The data-gathering method that was used in this study proceeded in a step-wise fashion, beginning with an expansion on the preliminary review of the literature where required as well as collecting the requisite data for the data envelopment analytical approach as described further below. This data-gathering method is highly congruent with the guidance provided by a number of researchers who emphasize the need to review what is known about a given subject in order to formulate an informed opinion and develop relevant findings. For example, Fraenkel and Wallen report that, "Researchers usually dig into the literature to find out what has already been written about the topic they are interested in investigating. Both the opinions of experts in the field and other research studies are of interest. Such reading is referred to as a review of the literature" (2001:48). Likewise, Gratton and Jones suggest that a review of the relevant literature represents the foundation of all contemporary research. "No matter how original you think the research question may be," they point out, "it is almost certain that your work will be building on the work of others. It is here that the review of such existing work is important. A literature review is the background to the research, where it is important to demonstrate a clear understanding of the relevant theories and concepts, the results of past research into the area, the types of methodologies and research designs employed in such research, and areas where the literature is deficient" (2003:51).

A number of important outcomes can be achieved during this phase of the research process. For example, Silverman notes that a well-conducted literature review can serve to answer the following questions:

A. What do we know about the topic?

B. What do we have to say critically about what is already known?

C. Has anyone else ever done anything exactly the same?

D. Has anyone else done anything that is related?

E. Where does your work fit in with what has gone before?

F. Why is your research worth doing in the light of what has already been done? (2005:300).

Similarly, Wood and Ellis identified the following as worthwhile goals of a well-conducted review of the literature:

A. It helps describe a topic of interest and refine either research questions or directions in which to look;

B. It presents a clear description and evaluation of the theories and concepts that have informed research into the topic of interest;

C. It clarifies the relationship to previous research and highlights where new research may contribute by identifying research possibilities which have been overlooked so far in the literature;

D. It provides insights into the topic of interest that are both methodological and substantive;

E. It demonstrates powers of critical analysis by, for instance, exposing taken for granted assumptions underpinning previous research and identifying the possibilities of replacing them with alternative assumptions;

F. It justifies any new research through a coherent critique of what has gone before and demonstrates why new research is both timely and important.

The next step in the data-gathering method will involve collecting the data needed to complete the data envelopment analytical approach needed to confirm or refute the study's guiding hypothesis described above, and this step is discussed further below.

3.4.

Research Method and Database of Study

The study consulted the available data stream in the sponsoring university library to collect the pertinent information from balance sheets and relevant financial statements for selected Malaysian banks for the period from 2005 to 2009.

3.5.

Research Variables

The research variables to be used in the data envelopment analysis will consist of unit costs defined as the operational costs incurred by Malaysian banks in doing business and outputs defined as the revenues generated.

3.6.

Research Hypothesis

It was the guiding hypothesis of this study that it is possible to discern the relative efficiency of financial institutions operating in Malaysia today using the data envelopment analytical approach.

3.7.

Conclusion

This chapter presented a description of study approach to be used in the proposed study, as well as its data-gathering method, the research method and database of study to be consulted, and the research variables that will be used. Chapter four will be used for an analysis of the data collected during the research process and chapter five will be used to provide a summary of the research, relevant findings and recommendations.

4.0 Data Analysis

5.0 Summary and Conclusion

5.1.

Summary

The research showed that an efficient banking industry is an essential ingredient for the economic development and viability of all countries, but especially developing and emerging nations that seek to become fully integrated into the international community. The research also showed that there remains a debate concerning which metrics provide the best indication of the efficiency of banks, as well as which analytical approach provides the most robust and trustworthy results. In this regard, two separate schools of thought have emerged over the years concerning the optimal approach for this purpose, with one school advocating the use of the parametric approach and econometric techniques while the other school maintains the nonparametric approach provides better results. The research also showed, though, that analysts have arrived at vastly different results even when they used the same methods for the same banks for the same periods of time based on their selection of which metrics they believed most accurately reflected banking efficiency. Therefore, it is also not surprising that the use of the nonparametric data envelopment analytical approach for determining the efficiency of banks has also produced some mixed results as well, but this approach does provide some useful tools for determining, at least in a general fashion, how well banks are performing compared to the larger industry in which they compete, and a recapitulation of the results of the analysis of selected Malaysian financial institutions using this method are reported below.

The comparison of revenues generated by selected Malaysian banks for the period 2003 through 2009 with the industry average (as calculated for these financial institutions only) showed that RHB Capital Berhad generated 41.09 per cent compared to the industry average in 2003, 45.20 per cent for 2004, 43.38 per cent for 2005, 51.37 per cent for 2006, 65.43 per cent for 2007, 87.99 per cent for 2008, finally managing to exceed the industry average in 2009 with 108.93 per cent. The operational costs for RHB Capital Berhad for the period 2003 through 2009 compared to the industry average showed that this institution was near the average for the entire period, with 104.74 per cent for 2003, 110.98 per cent for 2004, 110.41 per cent for 2005, 100.94 per cent for 2006, 97.26 per cent for 2007, 100.11 per cent for 2008 but declining in 2009 to 78.07 per cent. The ratio between revenues generated and operational costs compared to the industry average for RHB Capital Berhad for the period 2003 through 2009 showed steady increases, with 39.23 per cent for 2003, 40.73 per cent for 2004, 39.29 per cent for 2005, 51.25 per cent for 2006, 67.27 per cent for 2007, 87.90 per cent for 2008 and 139.54 per cent for 2009.

By sharp contrast, the revenues generated by Malayan Banking BHD were 327.34 per cent compared to the industry average for 2003, 359.55 per cent for 2004, 343.81 per cent for 2005, 330.87 per cent for 2006, but the financial institution experienced significant declines thereafter, with 291.68 per cent reported for 2007, 245.68 per cent for 2008 and just 62.74 per cent for 2009. The operational costs for Malayan Banking BHD were significantly higher compared to the industry average for the period 2003 through 2009, though, with 232.64 per cent for 2003, 235.05 per cent for 2004, 228.20 per cent for 2005, 215.95 per cent for 2006, 208.99 per cent for 2007, 219.88 per cent for 2008 and 233.41 per cent for 2009. The ratio between revenues generated and operational costs for Malayan Banking BHD were relatively consistent for the period 2003 through 2009 until 2009, with 140.71 per cent for 2003, 152.97 per cent for 2004, 150.66 per cent for 2005, 153.22 per cent for 2006, 139.57 per cent for 2007, 111.73 per cent for 2008 but plummeting to 26.88 per cent for 2009.

The results for Hong Leong Bank BHD showed that revenues generated for 2003 were 95.23 per cent of the industry average, declining to 56.64 per cent in 2004, but rebounding to 71.40 per cent in 2005, but then declining again in 2006 to 65.90 per cent, 56.97 per cent in 2007, 62.24 per cent in 2008 but regaining some strength in 2009 at 82.09 per cent. The comparison of the operational costs for Hong Leong Bank BHD for the period 2003 through 2009 showed that this institution consistently incurred significantly lower rates, with 51.21 per cent for 2003, 48.18 per cent for 2004, 49.05 per cent for 2005, 40.36 per cent for 2006, 43.21 per cent for 2007, 47.68 per cent for 2008 and 39.82 per cent for 2009. The Hong Leong Bank BHD experienced a number of swings in its ratio of revenues generated compared to operational costs for the period 2003 through 2009 compared to the industry average, with 185.96 per cent in 2003, 117.57 per cent in 2004, 145.58 per cent in 2005, 160.82 per cent in 2006, 131.84 per cent in 2007, 130.54 per cent in 2008 and jumping to 206.14 per cent in 2009.

Revenue generation by CIMB Group Holdings was consistently above the industry average for the period 2003 through 2009, with 128.26 per cent reported for 2003, 111.55 per cent for 2004, 113.59 per cent for 2005, 177.55 per cent for 2006, jumping to 256.34 per cent in 2007, but declining to 163.78 per cent in 2008 before nearly regaining its 2007 level in 2009 at 254.51 per cent. A comparison of the operational costs for CIMB Group Holdings for the period 2003 through 2009 with the industry average showed this institution experienced steady increases, with 163.54 per cent being reported for 2003, 172.31 per cent for 2004, 185.47 per cent for 2005, 243.96 per cent for 2006, 256.71 per cent for 2007, 222.49 per cent for 2008 and 262.61 per cent for 2009. The ratio for CIMB Group Holdings for revenues generated compared to operational costs for the period 2003 through 2009 compared to the industry average showed 78.43 per cent for 2003, 64.74 per cent for 2004, 61.24 per cent for 2005, 72.78 per cent for 2006, nearly reaching the industry average in 2007 with 99.86 per cent, but declining to 73.61 per cent in 2008 before increasing again to 96.91 per cent in 2009.

By contrast, Alliance Financial struggled throughout the period 2003 through 2009, with revenue generation at just 26.67 per cent compared to the industry average for 2003, 29.98 per cent for 2004, 29.55 per cent for 2005, followed by a disastrous year in 2006 at -23.82 per cent, but climbing to 9.84 per cent in 2007, 31.88 per cent in 2008 and 20.78 per cent in 2009. Alliance Financial also experienced operational costs lower compared to the industry average for the period 2003 through 2009, though, with 40.10 per cent for 2003, 33.77 per cent for 2004, 34.01 per cent for 2005, 34.86 per cent for 2006, 36.50 per cent for 2007, 31.14 per cent for 2008, and 30.92 per cent for 2009. There were also some interesting swings in the ratio of revenues generated compared to operational costs calculated for Alliance Financial compared to the industry average for the period 2003 through 2009, with 66.51 per cent for 2003, 88.78 per cent for 2004, 86.88 per cent for 2005, declining to -68.31 per cent in 2006, but regaining slightly in 2007 to 26.97 before topping the industry average in 2008 with 102.36 per cent but declining again in 2009 to 67.19 per cent.

The situation was rosier for Public Bank BHD for the period 2003 through 2009, though, with this bank consistently generating higher revenues compared to the industry average for 2003, with 164.47 per cent reported for 2003, 187.89 per cent for 2004, 199.25 per cent for 2005, 203.78 per cent for 2006, 194.91 per cent for 2007, 216.57 per cent for 2008 and 228.26 per cent for 2009. Public Bank BHD also experienced operational costs near the industry average for the period 2003 through 2009, with 127.05 per cent for 2003, 127.01 per cent for 2004, 118.38 per cent for 2005, 113.01 per cent for 2006, 114.12 per cent for 2007, 119.94 per cent for 2008 and 116.01 per cent for 2009. By and large, Public Bank BHD also experienced steady increases in its ratio of revenues generated with operational costs for the period 2003 through 2009 compared to the industry average, with 129.46 per cent for 2003, 147.93 per cent for 2004, 168.32 per cent for 2005, 180.31 per cent for 2006, 170.80 per cent for 2007, 180.57 per cent for 2008 and 196.76 per cent for 2009.

With regards to EON Capital BHD, this institution also struggled during the period 2003 through 2009, experiencing a steady decline in revenues generated compared to the industry average, with 53.84 per cent for 2003, 41.87 per cent for 2004, 39.90 per cent for 2005, 25.08 per cent for 2006, 20.43 per cent for 2007, and just 11.22 per cent for 2008 before regaining some strength in 2009 at 30.93 per cent. Perhaps not surprisingly, EON Capital BHD also experienced operational costs lower than the industry average, with 48.83 per cent for 2003, 46.80 per cent for 2004, 49.15 per cent for 2005, 37.15 per cent for 2006, 37.86 per cent for 2007, 47.46 per cent for 2008 and 43.74 per cent for 2009. There were also some interesting trends in the ratio of revenues generated with operational costs for AMMB Holdings Berhad compared to the industry average, with 56.47 per cent in 2003, 43.65 per cent in 2004, 36.00 per cent in 2005, 58.86 per cent in 2006, but declining to -27.28 per cent in 2007 before regaining significantly to 71.41 per cent in 2008 and then topping the industry average in 2009 at 116.52 per cent.

The situation was much the same for AMMB Holdings Berhad for the period 2003 through 2009, with this institution generating revenues of 42.21 per cent compared to the industry average for 2003, 33.18 per cent for 2004, 27.74 per cent for 2005, 43.14 per cent for 2006, -18.70 per cent for 2007, but regaining some strength in 2008 at 56.09 per cent and 2009 at 78.06 per cent. Operational costs for AMMB Holdings Berhad compared to the industry average for the period 2003 through 2009 showed 74.75 per cent for 2003, 76.01 per cent for 2004, 77.06 per cent for 2005, 73.29 per cent for 2006, 68.55 per cent for 2007, 78.55 per cent for 2008 and 66.99 per cent for 2009.

Finally, the results for Affinity Holdings BHD showed that this institution generated revenues compared to the industry average for 2003 through 2009 of 20.87 per cent for 2003, 34.14 per cent for 2004, 32.37 per cent for 2005, 26.78 per cent for 2006, 23.11 per cent for 2007, 24.56 per cent for 2008 and 33.72 per cent for 2009. The comparison of operational costs for Affinity Holdings BHD to the industry average for 2003 through 2009 showed 57.13 per cent for 2003, 49.89 per cent for 2004, 42.28 per cent for 2005, 40.48 per cent for 2006, 36.81 per cent for 2007, 32.78 per cent for 2008 and 28.43 per cent for 2009. The ratio between revenues generated and operational costs for Affinity Holdings BHD for the period 2003 through 2009 compared to the industry average was 36.53 per cent for 2003, remaining relatively steady thereafter with 68.43 per cent for 2004, 67.06 per cent for 2005, 66.15 per cent for 2006, but increasing to 74.98 per cent in 2008 and topping the industry average in 2009 at 118.58 per cent.

5.2.

Conclusion

Taken together, the results of the application of the data envelopment analytical approach to the selected Malaysia financial institutions in Chapter 4 above showed that some were less efficient as measured by the ratio between revenues generated and operational costs during the period 2006 and 2007, but most maintained steady performance throughout the period from 2003 through 2009. Indeed, financial institutions such as RHB Capital Berhad enjoyed steady increases in revenues earned while experiencing a concomitant decrease in operational costs, suggesting a high degree of efficiency, but others such as CIMB Group Holdings experienced modest increases in revenue generation together with increases in operational costs, suggesting a lower degree of efficiency. It is reasonable to conclude, though, that these ratios would be markedly different if other financial institutions were included in this analysis, or if different metrics were used to calculate their efficiency. Therefore, economists and banking authorities should seek to incorporate as many relevant variables into their analysis of banking efficiency as possible, and use a number of different analytical approaches, including both parametric and nonparametric methods, to formulate informed views about the efficiency of the financial institutions under study. In this fashion, a more robust view of the comparative efficiency of the banking industry can be gained, and benchmarks can be established for use in future analyses that employ these same methods.