ownership structure and financial performance of commercial...

GALAXY International Interdisciplinary Research Journal_______________________ ISSN 2347-6915 GIIRJ, Vol.1 (2), DECEMBER (2013)

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OWNERSHIP STRUCTURE AND FINANCIAL PERFORMANCE OF

COMMERCIAL BANKS:

A COMPARATIVE STUDY OF TWOMAJOR BANKS IN TANZANIA

DR.SRINIVAS MADISHETTI

PROFESSOR, SCHOOL OF BUSINESS

MZUMBE UNIVERSITY, MZUMBE, TANZANIA

ABSTRACT

The study is a comparison based on performance of TwoMajor Banksof Tanzania- NMB bank

with major ownership of Europeans and CRDB Bank with major ownership of Tanzanians

applying t-test to investigate any significant difference between selectCAMEL ratios.The study

reveals that there is a significance difference between the performances of both the banks in all

the CAMEL ratios applied except Return On Assets (ROA). The NMB bank‟s performance in

Capital Adequacy Ratio(CAR), Non Performance Assets ratio(NPA) and Net Interest Margin

ratio(NIM) comparatively appears to be better whereas the CRDB Bank performance was

comparatively higher in Operating Expenses Ratio(OER), Loan Deposit Ratio(LDR) and Return

On Assets with lower variability. It signals that CRDB management is concentrating on efficient

functioning of the bank as its OER is comparative lower and its LDR is higher indicating

effective use of deposits to increase its ROA instead of concentrating on comparative lower

performance in Capital adequacy, Asset quality (NPA) and volume of business (NIM). As against

this, NMB Bank is concentrating maintaining higher capital adequacy, asset quality and higher

NIM instead of efficiency in use of its resources both human and financial. This may be due to

differences in ownership structures and also managerial variability. Both need to improve their

performance learning each other‟s experience.

KEY WORDS: CAMEL, Financial Performance, Ownership Structure, Commercial Banks.

1. INTRODUCTION

Financial sector is the backbone of economy of any country as it plays the role of facilitator for

achieving sustained economic growth through providing efficient monetary intermediation. A

strong financial system with competitive environment promotes investment by financing

productive business opportunities, mobilizing savings, efficiently allocating resources and makes

easy the trade of goods and services. Banking system as a major component of financial system

plays a very important role in the economic life of the nation. The health of the economy is

closely related to the soundness of its banking system which is the consequence of efficient

management complying policies of the government and sound financial management principles.

In a developing country the banking system as a whole play a vital role in the progress of

economic development like heart in the economic structure and the Capital provided by it for

industry, agriculture and allied activities is like blood in it. Modern trade and commerce would

almost be impossible without the availability of suitable competitive banking services. This is so

because they promote savings from all manner of people, promotes investment in industry,

agriculture trade; enables to carry foreign trade in the form of exports and imports which is very

important in the present day situation. It is well-known fact that the banking sector plays a more

important role than it was believed earlier holding large share of economic activity of the

country.A profitable and sound banking sector is at a better point to endure adverse upsets and

adds performance in the financial system (Athanasoglou et al., 2008).A competitive banking

system promotes the efficiency and therefore important for growth, but market power is

necessary for stability in the banking system (Northcott, 2004).

Performance evaluation is the important approach for enterprises to give incentive and restraint to

their operators and it is an important channel for enterprise stakeholders to get the performance


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information (Sun, 2011). The performance evaluation of a commercial bank is usually related to

how well the bank can use its assets, shareholders‟ equities and liabilities, revenues and expenses.

The performance evaluation of banks is important for all parties including depositors, investors,

bank managers and regulators. The evaluation of a firm‟s performance usually employs the

financial ratio method, because it provides a simple description about the firm‟s financial

performance in comparison with previous periods and helps to improve its performance of

management (Lin et al., 2005). Moreover, the ratio analysis assists in determining the financial

position of the bank compared to other banks. Financial ratios based on CAMEL Framework are

related to capital, assets, management, earnings and liquidity considerations. Being its scope

covers performance evaluation of all the areas of the bank, it is considered one of the popular

measures for financial performance.

2. OVERVIEW OF BANKING SECTOR IN TANZANIA:

The function of the commercial banks has been enhanced in Tanzania to sustain theincreasing

need of the agriculture, industrial and service sector and the economy in general after the

financial reforms contemplated in the country. Starting in the mid‐1960s, Tanzania implemented

a series of economic policies grounded in socialist principles. According to these principles, the

government implemented central controls by directly investing in all sectors of the economy.

However, by the mid‐1980s, it was clear that earlier reforms had created a host of inefficient

companies verging on financial crisis. In the early 1990s, the Tanzanian government

implemented reforms designed to decrease its influence in the financial sector. In 1991, the

government passed the Banking and Financial Institutions Act, which allowed for the formation

of privately held banks. In addition, the Bank of Tanzania was given certain oversight controls to

ensure the development of prudent banking activities. In 1996, Tanzania‟s Cooperative and Rural

Development Bank (CRDB) became the first state‐owned bank to be privatized. Currently, a

number of banks have been established in Tanzania and now hold a significant amount of total

market share.

As of December, 2011, there are48 commercial banksconsisting of 31 fully-fledged commercial

banks and 17 financial institutions.. The top 10 banks in term of market share are National

Microfinance Bank (NMB) with 23%, National Bank of Commerce (NBC) with 13.3%, CRDB

Bank 12.8%, Barclays Bank Tanzania 6%, Exim Bank 4.3%, Stanbic Bank Tanzania 3.6%,

Tanzania Postal Bank 3.5%, Akiba Commercial Bank 3.2%, Standard Chartered Bank 3%,

FBME Bank 2.7%.Three of the top six, NMB, NBC and CRDB are the private sector banks have

significant domestic share holdings either via the government, aid agencies or the Tanzanian

private sector. The other four, are foreign owned.

The performance of the Banking sector during the period from 2006 to 2011 can be understood

from its increase in Total Assets from TSHS 5,294 Billion to TSHS.14,537 Billions, Loans from

TSHS 2,214 Billion to TSHS.7,157 Billion, Deposits from TSHS 4,240 Billion to TSHS.11,964

Billions, Shareholder Capital from TSHS. 525 Billions to TSHS.1,746 Billions, and Net Income

from TSHS 131 Billion to TSHS.343 Billions, signifying a CAGR 18.2%, 17.8%, 23.2%, 7.95%

respectively. During the same period the net interest income went up from TSHS.332 Billion to

TSHS.1048 Billion and interest spread went from 8.7% to 15%.. With The total number 48

banks, the branch network has gone up from 285 to 503 and employees from 6167 to 11,897 by

the end of 2011. Out of the total assets, foreign and local banks account for 50% each as at the

end of 2011.

Tanzania‟s banking sector has very limited exposure to the world financial markets. As a result,

the negative ramifications of the global credit crisis have not affected Tanzania relative to other,

more developed African states. Nevertheless, the strength of the banking system will be tested by

the economic slowdown that has followed the initial crisis. In spite of significant role played by

the banking sector it fails to cater the needs of industry, agriculture, service sector. High interest

rates, high interest spreads, low return on capital employed, growth in NPAs are some of the

challenges faced by the banking sector.


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3. PROBLEM SETTING: The banking sector of Tanzania comprises banks with different ownership like government,

public, private. According to the Tanzania Banking Sector Performance Review of 2011 in

Tanzania there are 31 full-fledged commercial banksout of which 29 are privately owned

banks.16 banks from the private sector banks are Non-government owned while the rest 13 are

partly owned by the Government. Among the Government partly owned private sector banks

three types of owner ship structure can be observed viz; banks having major ownership of

Tanzanians, banks with major ownership byAfricans other than Tanzanians and banks with major

ownership by Non- Africans.

Among these banks the market share of three major banks constitutes 49% of total banking in

Tanzania. The NBC Bank (Tanzania) Ltd acquired by Absa Group of companies, South Africa

with 55% share (NBC Bank Tanzania Ltd report 2010) government of Tanzania 30% and others

15%.In 1997, the National Microfinance Bank Limited Incorporation Act established the NMB.In

2005, The Government of the United Republic of Tanzania started the privatization process and

sold part of its shareholding (49%) to a consortium led by the CoöperatieveCentraleRaiffeisen-

Boerenleenbank B.A. ('Rabobank Group, Netherland‟). In 2008, the Government reduced its

share to 30% through the sale of shares to the general public in an IPO (16%) and to the NMB

staff (5%). NMB became listed on the Dar es Salaam Stock Exchange on 6th November,

2008.CRDB Bank Plc is a leading, wholly-owned private commercial bank in Tanzania. The

Bank was established in 1996 and has grown and prospered over the years to become the most

innovative, and trusted bank in the country. The Bank reached an important milestone recently

and was listed on the Dar es Salaam Stock Exchange on 17th of June, 2009.The 49% of

ownership is spread over Shareholders Owning Shares Below 1% and remaining over 12

categories of investors with highest share of 10% fromDANIDA Investment Fund.

Given the policy frame work and regulatory environment the performance of banks may also

relate with ownership and management structure as they pursue different managerial paths in

managing the banks. This may be due to planning, policy decisions of banks and also differences

in thrust areas. The studies on evaluating the comparative performances of such banks enable to

enlighten the causes for variations and enable to take appropriate measures. The review of

literature revealed peripheral studies of such kind in Tanzania.Hence in this paper an attempt is

made to study the performance of twomajor private sector banks in Tanzania one having

ownership structure with majority of Tanzanians, second one with ownership structure with

majority from Europeans applying CAMEL frame work which enlightens performance in many

area of bank. For the purpose,CRDB bank and NMB Banks were selected.

4. OBJECTIVES OF THE STUDY:

The prime objective of the study is to assess the financial performance of selected two major

banks in the private sector of Tanzania applying CAMEL frame work. In addition it also

concentrates on finding the ownership concentration impact on the performance difference in

CAMEL parameters.

5 REVIEW OF LITERATURE:

This study has relied on both conceptual and empirical review of literature

5.1.Conceptual review:

Concept and measures of financial performance:

Measuring the results of a firm's policies and operations in monetary terms is known as financial

performance.(Business dictionary). It is a subjective measure of how well a firm can use assets

from its primary mode of business and generate revenues. This term is also used as a general

measure of a firm's overall financial health over a given period of time, and can be used to

compare similar firms across the same industry or to compare industries or sectors in aggregation.

(Investopedia) The financial performance of a commercial bank is usually related to how well

the bank can use its assets,shareholders‟ equities and liabilities, revenues and expenses.

Performance evaluation is the important approach for enterprises to give incentive and restraint to


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their operators and it is an important channel for enterprise stakeholders to get the performance

information (Sun, 2011).

The financial performance of commercial banks and other financial institutions has been

measured using a combination of financial ratios analysis, benchmarking, measuring performance

against budget or a mix of these methodologies [Avkiran, (1995)]. Gopinathan (2009) has

presented that the financial ratios analysis can spot better investment options for, investors as the

ratio analysis measures various aspects of the performance and analyzes fundamentals of a

company or an institution. The tools for analysis may include DEA Model, CEAL approach,

Camels approach, finding relation between return and selected parameters of CAMEL rating by

applying multiple regressionsetc. Application of CAMEL frame work for measuring financial

performance of banks is widely accepted as it concentrates measuring performance in many

respects which include capital adequacy, asset quality, management efficiency, earnings ability,

and liquidity.

Ownership structure/concentration of Banks: Many studies have shown that ownership structure and concentration are important factors that

affect a firm‟s health. So studying the relation between ownership and performance is useful to

predict the probability of default (Claessens et al. 2002). There are broadly two approaches to

classify the ownership structure or concentration in banks. The first approach concentrates

making classification based on origin of ownership whereas the second approach concentrates on

share of largest owner and ownership mix. As per the first approach, ownership concentration is

divided into three mutually exclusive and collectively exhaustive categories, namely, majority

foreign, majority domestic and majority state or government ownership. The foreign and

domestic groups combined are called the private banking group in a given country. The definition

of “majority” is defined when the bank has at least 50% of ownership of a given category. Since

in many cases, there was no clear cut majority of ownership another group with the highest

ownership can be included within the foreign, domestic, and government banks in order to create

mutually exclusive distinct groups. As per the second approach the concept of ownership

structure can be defined along two concepts: ownership concentration, which refers to the share

of the largest owner, and ownership mix related to the major owner identity (Xu and Wang 1997;

Imam and Mlik 2007; Zeitun 2009).

Ownership structure and performance:

The relationship between ownership concentration and firm performance is complex and

empirical studies reported mixed results (Demsetz, 1983, Demsetz and Lehn 1985; Shleifer

and Vishny 1986). Three hypotheses are emerged out of these studies.

Among the three hypotheses,Convergence of interest hypothesis states that the more the

percentage of capital is concentrated the narrower is the gap to the objective of maximizing firm

value (Jensen and Meckling 1976) it proves performance by decreasing monitoring costs and

providing better control of management, predicts a positive relationship between ownership

concentration and firm performance. (Shleifer and Vishny 1986).

The second hypotheses Entrenchment hypothesis argues instead that presence of large controlling

shareholders can lead to expropriation behavior. In fact, the ultimate owner can abuse their power

of control to extract private benefits and expropriate minority stakeholders. Indeed, Shleifer and

Vishny (1997) point out that “large investors may respect their own interests, which need not

coincide with theinterests of other investors in the firm, or with the interests of employees and

managers”.Moreover, this expropriation behavior, in the case of high ownership concentration,

may limitthe ability of firms to raise funds through borrowing or new share offerings.

Consequently,the share participation for insider controllers may decrease firm performance.

Empirically, Leech and Leahy (1991) find, in the United Kingdom, a negative relationship

between the ownership concentration and the firm‟s value and profitability. Lin and Zhang (2009)

using a panel of 60 Chinese banks over the 1997–2004 report that the „„Big Four “commercial


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banks, which are the more concentrated, are less profitable, are less efficient, and have worse

asset quality than other types of banks.

Neutrality hypothesisargues that concentrated ownership is not associated with better operating

performance or higher firm valuation. According to neutrality hypothesis, ownership structure is

an endogenous variable, which determines the maximization of the value of a firm

(concentrated/diffused structure), rather than the characteristics of its environment, its market

and its own characteristics and operating conditions. So there is separation between ownership

and decision and there is no reason to think that concentrated firm is more efficient than firm

having diffuse capital (Demsetz 1983; Demsetz and Lehn, 1985; Holderness and Sheehan 1988;

Himmelberg et al. 1999; Demestz and Villalonga, 2001).

5.2 Empirical Review on performance of banks applying CAMEl:

The empirical studies on financial performance applying CAMEL frame work and ownership

concentration and performance are presented in brief.

A study was conducted in Uganda in 2008 employing A CAEL approach (Capital adequacy as

measured by core capital/risk weighted asset; Asset quality as measured by NPA (Non-

Performing Assets)/Total advances and specific provisions; Earnings as measured by ROA

(Return on Assets) and ROCE (Return on Capital Employed) and Liquidity which is measured by

liquidity assets/Total deposit). A series of secondary data for the period from 2000 – 2003 annual

reports of four banks selected using judge mental sample on the base of number of deposits was

obtained. It was found that banks performed fairly above regulatory requirements in terms of

capital adequacy and asset quality, performed at almost below zero in earnings and indicated

weakness in liquidity management by holding too much liquidity of more than 110%.

Neceur (2003) using a sample of ten Tunisian banks from 1980 to 2000 and a panel linear

regression model, reported a strong positive impact of capitalization to ROA.

There are number of studies, which examine the bank performance using CAMEL framework,

which is the latest model of financial analysis. Elyor (2009) and Uzhegova (2010) have used

CAMEL model to examine factors affecting bank profitability with success. The CAMEL

Framework is the most widely used model (Baral, 2005).Further empirical evidence on the use of

ratios for banks‟ performance appraisal included, Beaver (1966),Altman (1968), Maishanu

(2004),Mous (2005),Winkar and Tanko (2008). Beaver was the first person to use financial ratios

for predicting bankruptcy-his study was limited to looking at only one ratio at a time.

Wirnkar and Tanko (2008) identified and ranked the best ratios in each of the CAMELS

quantitative components apart from the „S‟ component (Sensitivity to market risk) which cannot

be easily quantified1. They brought forth a new acronym for CAMEL known as CLEAM in order

to reflect the magnitude and ability of each component to capture the performance of a bank in

descending order.

In a study titled Commercial bank efficiency in Tanzania, technical and ex-efficiency were

measured using non parametric data Envelop Analysis(DEA) Model based on a functional

relationship between inputs (cost) and output (revenue) using a series of secondary data from

financial reports for 10 years from 1990 was obtained from a sample of 5 banks and found that

commercial banks of Tanzania to be generally efficient but holding too much liquid assets

unnecessarily.it is an aggregate study concentrated on productivity.This research is built on the

identified best CAMEL components in a bit to derive a holistic function or model that could be

used by banks‟ regulators and management to check, monitor ,identify and correct emerging

problems on daily, weekly, monthly and short notices before they become unbearable.

5.3Empirical Review on ownership concentration and performance: Nada Kobeissi in his study on „Ownership Structure and Bank Performance: Evidence from the

Middle East and North Africa(MENA)‟ Using ownership details of 249 banks in 20 MENA

countries, with a total of 567 observations during the 2000-2002 sample years, Applied multiple


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regression OLS using ROI,ROE and ownership selected control variables such as loan to assets,

investment to assets, deposits to assets, equity to assets non interest expenditure to assets, loan

loss provision to assets and sheds some light on the association and impact of ownership structure

affecting bank performance. Overall, the results show that private banks, especially foreign ones

are significantly better performer than all sample groups. Government banks are lagging behind

other banks substantially and performed the worst among the sample banks. Banks involved in

the stock exchanges and foreign banks with majority ownership within the MENA region seem to

have significant effect on performance in most estimation. Importantly, the extent of foreign bank

presence in the country is associated with better performance by the sample banks. These findings

are strong and consistent even after adjusting for time and country differences among the sample

banks.

Bikram De in his paper on (2003) „Ownership Effects on Bank Performance: A Panel Study of

Indian Banks‟ used Panel Regression techniques to analyze the effects of ownership on bank

performance in the context of an emerging economy, India. The literature points to mixed results

in this context. They find that with the entire sample of public sector banks, old private sector

banks and new private sector banks, ownership does not seem to have any effect on the Return

On Assets but, public sector banks do seem to have higher Net Interest Margin and Operating

Cost Ratio. However, when the State Bank of India and its seven associates are dropped from the

sample, new private sector banks start showing a higher Return On Assets.

Alejandro Micco, Ugo Panizza and Mónica Yañez Inter-American Development Bank(November

2004) in their paper on „Bank ownership and performance‟ builds a new dataset on bank

ownership and bank performance covering approximately 50,000 observations for 119 countries

over the 1995-2002 period. The paper then uses the dataset to reassess the relationship between

bank ownership and bank performance, providing separated estimations for developing

and industrial countries. It was observed that, while ownership is strongly correlated with

performance in developing countries, that ownership is not correlated with performance in

industrial countries.

Morteza Soltani, Mehdi Esmaili, Majid Hassan poor, Hossein Karami in their study on

„Evaluating the Performance of Public and Private Banks and Providing Suggestions for

Improving the Performance of Them (Case study: Melli, Agriculture, Pasargad and Parsian Bank

of Qom)‟ employed CAMEL Model to evaluate and compare the financial performance of public

and private banks and tested the significance by applying independent „t‟ test. Statistical sample

includes Melli and Agriculture bank which are public and Pasargad and Parsian bank whichare

private. The results show that there is a significant difference between private and public banks in

terms of liquidityand earning performance and management quality. In terms of liquidity and

earning performance the private banks havebetter performance but the public banks have better

performance in terms of management performance. Also the resultof testing the main hypothesis

show there is no significant difference in the performance of public and private banks.Although

the overall mean suggests the better performance of private banks, but this difference is not

significant. So theprivate banks should try to improve their performance.

The foregoing review reveals that the comparative performance of commercial banks are studied

mostly by applying multiple regression taking either ROI or ROEas dependent and ownership

concentration, some control variables as independent variables at country aggregate level. But

specific studies are not observed in Tanzania to compare the performance by applying CAMEL

frame work that too for ownership concentration and performance choosing specific banks.This

study is a modest attempt in this direction to fill the gap.

6. RESEARCH METHODOLOGY:

For the purpose of this study, two major banks of Tanzania viz; CRDB Bank and NMB banks are

chosen as stated earlier and the following process followed in developing this paper:

Information relating to select camel framework variables from 2006 to 2011 are collected from

financial statements of respective banks


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On the basis of collected data, selected CAMEL ratios Viz; Capital Adequacy Ratio, Non

Performance Loan Ratio, Operating Expenses ratio, Net Interest margin ratio, and Loan deposit

ratio are calculated for all the years for both the banks.

Whether the data of both the banks are suitable for t- test or not is tested by applying t- test

diagnosis i.e equal means, equal variances by applying appropriate tests

Applied t- test to identify the significance and results are interpreted.

The study applied the CAMEL ratios and t-test for analyzing the performance of banks as

followed by Morteza Soltani1, Mehdi Esmaili2, Majid Hassan poor3, Hossein Karami in thier

study Evaluating the Performance of Public and Private Banks and ProvidingSuggestions for

Improving the Performance of Them(Case study: Melli, Agriculture, Pasargad and Parsian Bank

of Qom)

6.1 Relationship of parameters chosen with financial performance:

In this study the independent variables are CAMEL ratios and the dependent variable is financial

performance. Based on the theoretical and empirical findings the expectations of how the

independent variables impact the dependent variable were predicted are presented

hereunder.ROA in this context is a reflection of the net profit of a bank. ↑↓

The expected impact of independent variables on ROA (Return on assets) Camel Component Ratio Symbol Formula Predicted impact on

financial performance

Capital Adequacy Capital Adequacy Ratio

CAR↑ CAR = Tier I + Tier II/Risk

weighted Assets

+ve

Asset Quality Non-performing loans

Ratio

NPL↑ NPL= Nonperforming assets/

Total loans and advances

-ve

Management Quality Operating Expenses

Ratio

OER↑ OER= Total operating expense/

Total operating revenue

-ve

Earnings

Performance

Net Interest Margin NIM↑ NIM= (Interest received- Interest

paid)/ Average earning assets

+ve

Return on Assets ROA Net profit/total assets +ve

Liquidity

Management

Loan to Deposit Ratio LDR↑ LDR= Total loan and advances/

Total deposit

-ve or +ve

Source: Authors own composition

The expected impact of the independent variables can further be explained as follows;

The ultimate strength of a bank lies in its capital funds given its significance as a tool for meeting

liabilities in times of financial crisis and as a cushion of insulating a bank in times of varying market

adversities and is a tool for operating profitably.CAR serves this purpose. The review reveals that

maintaining required CAR improves the financial performance.

NPL which represents non-performing loans is expected to move in the opposite direction with net

profit. The higher the non-performing loans the less profitable the bank is supposed to be, because

there is a loss in collection of interest income derived from the non-performing loans which is the

most depended on source of revenue to the bank.

Operating expenses ratio reflects on the ability of the management to control costs. The operating

costs in the income statement appear under expenses and are deducted from the gross profit to arrive

at the net profit. The higher the expenses the less the net profit is. That is why the net profit moves in

a negative direction with the OER. The higher the expense of a bank keeping other things constant,

the lesser the bank‟s profitability will be.

It is expected that as net interest income which is revenue increases the net profit will also increase,

given the layout of the income statement.

The effect of liquidity was a bit tricky to predict. If optimum liquidity is maintained without idle cash

balances it helps to increase the financial performance. As Against this if excessive liquidity is

maintained keeping funds idle, though it may improve the credit worthiness but affects the financial

performance.

Increase in ROA is an ultimate indication of distribution of increased returns to funds suppliers.

Decrease indicates vice versa.


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7. ANALYSIS OF DATA AND FINDINGS

In order to analyze the comparative financial performance of CRDB and NMB banks, as stated

earlier, six CAMEL ratios are calculated for selected parameters of capital adequacy, asset

quality, management quality, earnings ability, liquidity position and return on assets as overall

financial performance. The means and standard deviations are analyzed first and subsequently „t‟

test is applied between two banks for every parameter to find whether any significant variation is

present in the results. To test the validity of data test of normality and test of homogeneity of

equal variances is applied. Finally based on t test results inferences are arrived. The details are

presented below.

7.1 Descriptive statistics of the parameters of both the banks:

Comparative performance of CRDB and NMB banks are examined on the basis of their average

performance in terms of CAMEL ratios and their standard deviations. The average performance

of chosen six ratios along with their standard deviations is given in table1.

Table 1: Descriptive statistics of CAMEL ratios Parameter/ratio Bank N Mean Standard deviation Standard error of Mean

CAR CRDB 7 17.1429 2.4103 0.91101

NMB 7 27.7286 8.82170 3.33429

Asset quality/NPA CRDB 7 6.9386 3.05746 1.15561

NMB 7 3.9100 1.58122 0.59765

Management

quality/OER

CRDB 7 46.1514 1.45702 0.5507

NMB 7 53.6643 4.52674 1.71095

Earnings/NIM CRDB 7 9.6786 0.5436 0.2061

NMB 7 11.9671 1.40539 0.5311

Earnings/ROA CRDB 7 2.9857 1.17887 0.44557

NMB 7 2.4271 1.45424 0.54965

Liquidity/LDR CRDB 7 60.7329 5.45801 2.06293

NMB 7 45.7900 14.62506 5.52775

Source: compiled on the basis of calculated values of the parameters.

The following observations can be made from the analysis of the above table:

The mean of capital adequacy ratio of NMB Bank (27.73) was higher than the mean of CRDB

Bank (17.14).However NMB Bank CAR standard deviation was higher as a share of its mean

(8.82/27.73) when compared to CRDB Bank(2.41/17.41). It shows that though both the banks

maintained CAR of stipulated level NMB Bank maintained higher than CRDB Bank with higher

variability.

The mean of NPA ratio of NMB Bank (3.91) was lower than the mean of CRDB Bank

(6.93).However the NMB Bank NPA standard deviation wasmarginally higher as a share of its

mean (1.58/3.91) when compared to CRDB bank (3.06/6.93). It shows that though both the banks

NPA ratio were more than stipulated level NMB maintained comparatively lower level than

CRDB Bank with marginally higher variability.

The mean of OER of NMB Bank (53.66) was higher than the mean of CRDB Bank

(46.15).However the NMB Bank OER standard deviation was higher as a share of its mean

(4.53/53.661) when compared to CRDB Bank (1.46/46.15). It shows that OER ratio of NMB

Bank was higher with higher variability when compared to CRDB Bank.

The mean of NIM ratio of NMB Bank (11.97) was higher than the mean of CRDB Bank

(9.68).However the NMB Bank NIM standard deviation was marginally higher as a share of its

mean (1.41/11.97) when compared to CRDB bank (0.54/9.68). It shows that NIM ratio of NMB

Bank was higher with marginally higher variability when compared to CRDB Bank.

The mean ROA ratio of NMB Bank (2.43) was lower than the mean of CRDB Bank (2.99).

Further, the NMB Bank ROA standard deviation was marginally higher as a share of its mean

(1.45//2.43) when compared to CRDB bank (1.185/2.99). It shows that The ROA of CRDB Bank

was higher with lower variability when compared to NMB Bank.


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The mean of LDR of NMB Bank (45.79) was lower than the mean of CRDB Bank (60.73).

Further, the NMB Bank LDR standard deviation is higher as a share of its mean (14.63/45.79)

when compared to CRDB bank (5.45/60.73). It shows that the CRDB bank LDR was higher than

NMB Bank with lower variability.

From the above it can be inferred that the NMB bank performance in CAR,NPA and NIM

comparatively appears to be better with higher variability. The CRDB Bank performance was

comparatively higher in OER, LDR and ROA with lower variability. This may be due to

managerial ability in effective use of human and financial resources.

7.2. Test of Normality:

For testing the normality of the data of all the parameters,Kilmogorov-smirnov and Shapiro-wilk

tests are applied using SPSS.Null Hypothesis is that there is no significant departure from

normality as such; retaining the null hypothesis indicates that the assumption of normality has

been met for the given sample.The Alternative Hypothesis is that there is a significant departure

from normality, as such; rejecting the null hypothesis in favor of the alternative indicates that the

assumption of normality has not been met for the given sample. From this test, the Sig. (p) value

is compared to the a priori alpha level (level of significance for the statistic) – and a

determination is made as to reject (p < α) or retain (p >α ) the null hypothesis.

Table 2: Test of Normality parameter

bank

Kilmogorov-smirnovᶦ Shapiro-wilk

statistics df Sig statistics Df sig

CAR CRDB 0.111 7 0.200ͫ 0.984 7 0.976

NMB 0.269 7 0.136 0.762 7 0.017

Asset

quality(NPA)

CRDB 0.206 7 0.200 0.898 7 0.317

NMB 0.159 7 0.200 0.962 7 0.839

Management

quality

CRDB 0.210 7 0.200 0.924 7 0.504

NMB 0.170 7 0.200 0.976 7 0.940

Earnings CRDB 0.294 7 0.069 0.849 7 0.120

NMB 0.200 7 0.200 0.948 7 0.714

Liquidity CRDB 0.140 7 0.200 0.954 7 0.767

NMB 0.253 7 0.195 0.927 7 0.525

ROA CRDB 0.219 7 0.200 0.957 7 0.794

NMB 0.288 7 0.082 0.839 7 0.097

ᵐ. This is a lower bound of the true significance.

ⁱ. Lilliefors Significance Correction

In Kilmogorov – Smirnov test of normality Since p(values of all the parameters stated in above

table for both the banks) >α i.e 0.2;0.136;0.2;0.2;0.2;0.2;0.069;0.2;0.2;0.195;0.2 and 0.082 are

more than 0.05, the null hypotheses of no significant departure from normality is not rejected.

Hence the normality assumption in these variables can be construed as satisfied.

Similarly in Shapiro-wilk test of normality Since p(values of all the parameters stated in above

table for both the banks) >αi.e 0.976;0.317;0.839;0.504;0.940;0.120; 0.714; 0.767;

0.524;0.794;0.097 are more than 0.05, the null hypotheses of no significant departure from

normality is not rejected. However, the p value of CAR of NMB is 0.017 which is less than

αvalue 0.05 Hence the normality assumption as per Shapiro-wilk test is also satisfied in all the

variables of two banks except CAR of NMB.

7.3 Test of Homogeneity of variances:

For testing the Homogeneity of variances Leven‟s statistic is calculated using SPSS. Null

Hypothesis is that there is no significant departure from Homogeneity of variances as such;

retaining the null hypothesis indicates that the assumption of normality has been met for the given

sample. The Alternative Hypothesis is that there is a significant departure from Homogeneity of

variances as such; rejecting the null hypothesis in favor of the alternative indicates that the


10

assumption of normality has not been met for the given sample. From this test, the Sig. (p) value

is compared to the a priori alpha level (level of significance for the statistic) – and a

determination is made as to reject (p < α ) or retain (p >) α the null hypothesis.

Table 2: Test of Homogeneity of Variances parameter Based on Levene statistic Df1 Df2 sig

CAR Mean 1.322 2 18 0.291

Median 0.412 2 18 0.668

Asset quality(NPA) Mean 0.620 2 18 0.549

Median 0.524 2 18 0.601

Management quality Mean 13.187 2 18 0.000

Median 6.487 2 18 0.008

Earnings ability Mean 2.072 2 18 0.155

Median 0.924 2 18 0.415

Liquidity Mean 4.511 2 18 0.026

Median 1.918 2 18 0.176

ROA Mean 0.994 2 18 0.339

Median 2 18

The second important test of assumption‟ homogeneity of variances‟ isalso construed as satisfied as

null hypotheses is not rejected for the both banks as their p values 0.291; 0.668;0.549;

0.601;0.155;0.415;0.026;0.176 and 0.339 are >0.05 with exception of management quality ratio where

the p value was 0.000 (mean) and 0.008 ( median) which are lower than 0.05. Wherever normality and

homogeneity of variances tests are not met, for interpreting the final results the values of unequal

variances are also used.

7.4 Independentt-test for CAMEL parameters of CRDB and NMB banks:

As explained in methodology Independent Samples t-test is applied using SPSS for finding

significance in differences of CAMEL parameters of CRDB and NMB banks. Null Hypothesis is

that there is no significant departure from, as such; retaining the null hypothesis indicates that the

assumption of normality has been met for the given sample.

Table 3: Independent t- test for CAMEL parameters of CRDB and NMB Banks:

parameter Levens t Test for

equality of variances t test for equality of Means

F Sig. T DF Sig(2

Tailed)

Mean

Diff.

SE

Diff.

95% Confidence

level(lower)

Interval of the

mean (upper)

CAR -

Equal

variances

assumed 3.105 .103 -3.063 12 .010 -10.5857 3.4565 - 18.11679 -3.05464

Not

assumed

- - -3.063 6.891 .019 -10.5857 3.4565 -18.78536 -2.38606

Asset quality

Equal

Variances

assumed 2.387 .148 2.328 12 .038 3.02857 1.30101 0.19392 5.86322

Not

assumed

- - 2.328 8.995 .045 3.02857 1.30101 0.08525 5.97189

Mgt.quality-

Equal variances

assumed 6.384 .027 -4.180 12 .001 -7.51286 1.79739 -11.42904 -3.59668

Not

assumed

- - 4.180 7.230 .004 -7.51286 1.79739 -11.73476 -3.28996

Earnings-

Equal variances

assumed 4.375 .058 -4.017 12 .002 -2.28857 0.56978 -3.53001 -1.04713

Not

assumed

- - 4.017 7.767 .004 -2.28857 0.56978 -13.60938 -0.96776

Liquidity-

Equal variances

assumed 3.094 0.104 2.533 12 .026 14.9428

6

5.90015 2.08753 27.79818

Not

assumed

- - 2.533 7.639 .036 14.9428

6

5.90015 1.22452 28.66120

ROA-

Equal Variances

assumed 0.994 0.339 0.789 12 .445 0.55857 0.70757 -0.98308 2.10023-

Not

assumed

- - 0.789 11.507 .446 0.55857 0.70757 -0.99043 2.10758

Source: compiled from the t-test results of individual parameters.

The following observations can be made from the analysis of the above table:

The p values of „equal variances assumed‟ and „equal variances not assumed‟for CAR were 0.010

and 0.019showing less than valueof 0.05. Hence the null hypotheses mean variations of both

groups are same is rejected.


11

The p value of Asset quality for „equal variations assumed‟ and „equal variations not assumed‟

were 0.038 and 0.045. This value is lower Whenit is compared witha priori alpha level (level of

significance for the statistic) 0.05. Hence the null hypotheses „mean variations of both groups are

same „is rejected.

The p value ofmanagerial quality for „equal variations assumed‟ and „equal variations not

assumed‟ were 0.001 and 0.004 respectively showingless thana priori alpha level (level of

significance for the statistic) of 0.05. Hence the null hypotheses „mean variations of both groups

are same is rejected.

The p value of earnings ability for‟equal variances assumed‟ and „equal variances not assumed‟

were 0.002 and 0.004 respectively showing less thana priori alpha level (level of significance for

the statistic) value of 0.05. Hence the null hypotheses „mean variations of both groups are same „

is rejected.

The p value of liquidity for „equal variances assumed‟ and „equal variances not assumed‟ were

0.026 and 0.036 respectively showing less thana priori alpha level (level of significance for the

statistic) value of 0.05. Hence the null hypotheses „mean variations of both groups are same „ is

rejected.

The p value of ROA for equal variances assumed‟ and „equal variances not assumed were 0.445

and 0.446 showing more thana priori alpha level (level of significance for the statistic) value of

0.05. Hence the null hypotheses „mean variations of both groups are same is not rejected.

The summary of findings are presented in the following table:

Table 4: Summary of Findings s/n Hypothesis p-value Empirical conclusion

1 H1: There is no significant Mean variation between CRDB and NMB Banks in capital adequacy

ratio

0.010

/0.018

Rejected null

2 H2: There is no significant Mean variation between CRDB and NMB Banks in asset quality ratio 0.038

/0.045

Rejected null

3 H3: There is no significant Mean variation between CRDB and NMB Banks in Management

quality ratio

0.001

/0.004

Rejected null

4 H4: There is no significant Mean variation between CRDB and NMB Banks in Earning ability

ratios

0.002/

0.004

Reject null

5 H5: There is no significant Mean variation between CRDB and NMB Banks in liquidity ratios 0.026/

0.036

Reject null

6 H6: There is no significant Mean variation between CRDB and NMB Banks in ROA . 0.445/

0.446

Not to reject null.

8. CONCLUSIONS AND SUGGESTIONS:

Economic development and attainmentof the endowed mission and vision of commercial banks in any countryis

closely related with and affected by growth of banking industry and the motives and strategies of the ownership

structure of the banks.. Thisstudy was conducted whit the aim of evaluating the comparative performance of two

major private banks of Tanzania viz; CRDB and NMB Banks based on CAMEL model. The share capital

CRDB bank iswidely spread over the shareholders of Tanzania while the major share capital of NMB Bank is

contributed by Netherland apart from substantial participation from the public and government. The

comprehensive literature review and study of research background showed mixed results about the comparative

performance of different ownership structures.

The results of this study showedthat thereis significant differences in the performance of CRDB and NMB

banks. In all the CAMEL ratios except ROA the t-test results show that there is difference in the performances

of both the banks. In the case of ROA there is no significant variation in the performance. As per descriptive

statistics it can be understood that the NMB bank‟s performance in CAR, NPA and NIM comparatively appears

to be better with higher variability. The CRDB Bank performance was comparatively higher in OER, LDR and

ROA with lower variability. With these study findings it can be concluded that CRDB management is

concentrating on efficient functioning of the bank as its OER is comparative lower and its LDR is higher

indicating effective use of deposits to increase its ROA instead of concentrating on comparative lower

performance in Capital adequacy, Asset quality (NPA) and volume of business(NIM). As against this, NMB

Bank is concentrating maintaining higher capital adequacy, asset quality and higher NIM instead of efficiency in

use of its resources both human and financial. This may be due to differences in ownership structures and also

managerial variability.


12

Since CRDB is concentrating on efficiency in use of resources and NMB is concentrating on size higher

margins and quality of assets, both can share the experiences of each other. CRDB has to concentrate on its

composition of assets by reducing its NPAs and increasing sectors of lending to increase its asset quality and

increase in capital adequacy whereas the NMB Bank need to concentrate on effective use of its deposits without

keeping idle resources and also efficient use of human resources.

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