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Bangladesh Journal of Multidisciplinary Scientific Research; Vol. 2, No. 2; 2020 
ISSN 2687-850X   E-ISSN 2687-8518  

Published by CRIBFB, USA  
 

    40 
 

Benchmarking and Rating of Private Commercial Banks of Bangladesh Through 
CAMELS Components 

 
 
 

A H M Ziaul Haq PhD  
Professor 

Department of Finance 
University of Rajshahi, Bangladesh 
E-mail: zia_haq2001@yahoo.com 

 
 

Hosnay Nasrin 
PhD Fellow 

Department of Finance 
University of Rajshahi, Bangladesh 

E-mail: hn_nahin@yahoo.com 

 
 
Received: August 30, 2020    Accepted: September 13, 2020 Online Published: September 27, 2020 
 
doi: 10.46281/bjmsr.v2i2.783  URL: https://doi.org/10.46281/bjmsr.v2i2.783  
 
 
Abstract 
The banking sector of Bangladesh is becoming more complicated than before. Ensuring the financial stability of the economy, 
monitoring, supervision, and continuous performance evaluation of the banking sector are compulsory. The present study, 
therefore, is an attempt to evaluate and compare the performance of our banks. One of the most effective supervisory techniques, 
CAMELS rating system has been used to benchmark and rate the banks based on their performance. In this study, 21 private 
commercial banks (PCBs) have been chosen as samples to meet the purpose of the study. Data for analysis has been collected 
from the banks‟ annual reports for the period of 2008 to 2018. The result shows that none of the banks could achieve a 'strong' 
position, and only SEBL was able to secure a „satisfactory‟ mark. Unfortunately, AB bank was rated "marginal" in the composite 
rating, which is the lowest rating among the sample banks. Hence, AB bank needs to develop reform and follow-up programs as 
soon as possible to avoid financial failure.  
 
Keywords: Private Commercial Banks, Performance Evaluation, CAMELS Components, Benchmarking, Composite Rating.  
 
1. Introduction 
Since the banking industry has become globalized and liberalized, so clients everywhere in the world would quickly look forward 
to the identical world-class support from any bank offering a similar service, as customers always expect better service; therefore, 
benchmarking is a competitive strategy to win over the market shares, and a survival approach for threatened businesses and 
industries. Initially, banks should conduct benchmarking with their competitors or banks having excellent performance in the 
banking industry operating anywhere in the world. Secondly, banks can benchmark with their affiliates, sister companies, and 
subsidiaries which may be performing specific practices a lot better than the bank does. Finally, banks can also benchmark their 
performance with companies outside the industry whose approaches can be tailored to the banks themselves. After 
benchmarking, banks can realize their rating of performance in specific key areas. CAMELS is used as a benchmarking tool to 
evaluate the performance of commercial banks. 

Benchmarking is a process of comparing the performance of one business with its rivals.  (Tzu, 2002) 
mentioned in his study that benchmarking is the system of finding out the comparative significance of something by relating it 
to a recognized criterion. And (Anderson & McAdam, 2006) stated in their study that benchmarking is used as a method of 
evaluating practices and choosing new strategies to sustain a company. The role of benchmarking in British banking is narrated 
in research by (Knights & McCabe, 2006) in detail as well. Through benchmarking, British banks have gradually adopted quality 
initiatives and gained significant success in quality management, the results showed.   

mailto:zia_haq2001@yahoo.com
mailto:hn_nahin@yahoo.com
https://doi.org/10.46281/bjmsr.v2i2.783
https://doi.org/10.46281/bjmsr.v2i2.783


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The banking sector of Bangladesh is divided into four classifications of scheduled banks; State-Owned Commercial 
Banks (SCBs), Government Owned Development Financial Institutions (DFIs), Private Commercial Banks (PCBs), and Foreign 
Commercial Banks (FCBs). The number of banks in Bangladesh was increased to 59 in 2018, and the number of bank branches 
increased to 10286 in 2018. Table 1 shows the banking structure in Bangladesh. (December 2018). In Table 1, it is observed 
that PCBs' deposits in 2018 amounted to BDT. 7127.2 billion Or 66 percent in the total deposit and its share in the total assets 
also increased to 67 percent during the same period. Since PCBs are dominating the whole banking industry in terms of assets 
and deposits, it is, therefore, essential to evaluate the performance of PCBs whether they are running on the right track. 
 
Table 1. Banking Structure in Bangladesh (2018–in Billion Tk.) 

 
 
 
 
 
 
 
 
 
 

Source: Annual Report of Bangladesh Bank, 2018-19 
 

So, the banks of Bangladesh need to conduct benchmarking, which is a modern process of comparing the 
performance of one business with its rivals. Hence, this study aims to conduct benchmarking of the selected PCBs to 
apprehend the performance of the selected banks using the CAMELS components.  
 
1.1 Statement of the Problem 
Bangladesh‟s financial system is dominated by banks where the banking system accounts for around 96 percent of the total assets 
of the financial sector. As the banking sector is the leading component of the overall financial system in Bangladesh, so  i t  is  
ess entia l to ensure the soundness of its banking system for the socio-economic development of the country. It is crucial to 
assess and evaluate the overall performance of banks in Bangladesh through the implementation of a regulatory banking 
supervision framework. 

Various constraints hinder the development of the banking sector including PCBs of Bangladesh which includes, 
among others, numerous forms of banking scams such as money laundering, non-performing loans (NPLs), etc. Some banks 
still have been facing capital shortfalls and fail to maintain the BASEL requirement. Because of the high focus of loans and 
advances, the vulnerability of assets to credit risk increases. Because of high NPLs banks experience enormous stress to earn a 
profit, and the financial stability of the banks becomes day by day. It has been observed that there is a negative and reverse 
relationship that exists between NPLs and the profitability of banks. Again, due to the growing size of NPLs, banks are 
now facing difficulties at maintaining healthy liquidity. According to a recent study (Raju, 2017), the cost efficiency 
level of 35 commercial banks of Bangladesh is 91.4 percent. On the other hand, the earnings ability of these banks has also been 
decreasing alarmingly. So, this scenario reflects negatively in the overall banking industry performance of Bangladesh. 

At this stage, it is essential to examine the fundamental factors which affect the performances of banks in Bangladesh. 
The additional focus of the study is to examine the rating of the PCBs of Bangladesh through benchmarking based on 
CAMELS components. Among different prevalent approaches, the CAMELS rating system is the most preferred 
approach used by regulators and scholars. Bangladesh Bank introduced CAMELS in 1993 as an integral part of the 
off-site supervision system. 

 
1.2 Research Questions 
Hence, keeping the statement of the problem in mind, the ultimate goal of the study has been set to address the following 
questions; 

 How to benchmark the performance of the PCBs of Bangladesh with respect to composite rating? 

 What has been the level of the soundness of the PCBs of Bangladesh? 
 
 
 

Bank Type 
 

Number of 
Banks 

Number of 
Branches 

Total 
Assets 

% of Industry 
Assets 

Deposits 
 

% of 
Deposits 

SCBs 6 3746 3732.2 25.6 2868.4 26.6 

DFIs 3 1412 324.0 2.2 286.0 2.6 

PCBs 41 5060 9769.7 67.0 7127.2 66.0 

FCBs 9 68 747.1 5.2 517.2 4.8 

Total 59 10286 14572.9 100 10798.7 100 



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1.3 Objectives of the Study 
The p r i m e  objective of the study is to conduct benchmarking to evaluate the performance of the PCBs of Bangladesh from 
the year 2008 to 2018. The following are the specific objectives: 

 To benchmark the performance of the PCBs of Bangladesh, and 

 To analyze the performance of the PCBs of Bangladesh using the CAMELS components. 
 
2. Literature Review 
The study reviewed various studies in the area of performance evaluation of banks, CAMELS rating, and benchmarking, which 
were conducted in Bangladesh and abroad. Some of the literature reviews are as follows: 

The CAMELS approach measures the financial performance of banking institutions. Under this 
system, each banking institution is examined based on six vital magnitudes concerning the bank's operations 
and performance mentioned by (Sahajwala & Van den Bergh, 2000).  

(Barr, Killgo, Siems, and Zimmel (2002) states that CAMELS rating has become a concise and indispensable tool for 
examiners and regulators.  

The rating ensures a bank's healthy conditions by reviewing different aspects of a bank based on a variety of 
information sources such as financial statements, funding sources, macroeconomic data, budget and cash flow (Suba, 2015) gave 
a comprehensive framework on the CAMELS model. The author gave detailed definitions of the ratios and the interpretations of 
them to form a structural model on them. 

CAMEL parameters were used by (Sangmi & Nazir, 2010) to evaluate the financial performance of the 
two major northern Indian banks.  

Concerning their capital adequacy, asset quality, management capability, and liquidity, the financial 
performance of these two banks was found as sound and satisfactory by the study. (Roman & Sargu, 2013) used 
the CAMELS framework to comparatively analyzes the financial soundness of the commercial banks of Romania.   

The results from the study highlighted the strengths and the vulnerabilities of the analyzed banks and suggested 
guidelines to improve and increase their soundness. (Venkatesh & Chithra, 2014) used the CAMELS model to analyze the 
financial efficiency of selected commercial banks in the kingdom of Bahrain which is considered as the financial hub of the 
Middle East and plays a significant role in the economic activities in the Mena Region. 
   (Barker & Holdsworth, 1993) mentioned in their study that in the prediction of banks‟ failure CAMEL rating is 
useful.  
   (Cole & Gunther, 1998) conducted a study to assess the accuracy of CAMELS ratings in predicting the failure of 
banks. They used CAMELS as a benchmark and an off-site monitoring system based on publicly available accounting data.   
   (Nurazi & Evans, 2005) also investigated whether CAMEL ratios could be used to predict bank failure. It has proven 
to be a useful internal supervisory tool for evaluating the soundness of a financial firm, based on identifying those institutions 
requiring special attention or concern.   

(Yuksel, Dincer & Hacioglu, 2015) exhibited the relationship between CAMELS ratios and credit ratings of twenty 
depository banks in Turkey. They used secondary data for the period (2004-2014) and analyzed 21 different ratios of 
CAMELS components. 

(Moudud-Ul-Huq, 2017) attempted to measure the financial performance of PCBs in Bangladesh. In the study, 
primarily he selected 10 PCBs and collected data for the periods 2013–2014. For measuring the financial performance and 
rating these banks according to the composite rating system, CAMELS was employed by the study.   

(Rahman & Islam, 2018) in their study took an attempt to evaluate and compare the performance of the banking 
sector in Bangladesh. Accordingly, the CAMELS rating system had been employed by the study to grade the banks based on 
their performances. 

 
2.1 Research Gap 
A review of previous pieces of the literature reveals that some studies have been done in the context of the performance of banks, 
benchmarking, and CAMELS components in different countries. From the perspective of Bangladesh, several research works 
have been conducted so far to make a comparative analysis of PCBs to examine the differential impact of various CAMEL 
components upon banks' profitability. Few articles and research papers explore the CAMEL rating of the commercial banks and 
few kinds of research explore the comparative analysis of the conventional and Islamic banks which are performing in 
Bangladesh. On the other hand, this study has conducted benchmarking to find the composite ratings of the selected banks to 
examine the performance of the banks based on CAMELS components. So, this study is different from the earlier studies in the 
sense that it highlights the composite rating approach using the CAMELS components. All the six components including “S”, to 



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assess the position of the banks in the market and create a space for the respective policymakers of the PCBs of Bangladesh to 
undertake initiatives to improve their bank's performance to attain a better rating. 
 
3. Methodology of the Study 
The present study has been carried out to assess the performance of the PCBs of Bangladesh. The population of the study is, 
therefore, all the PCBs that are enlisted in the Dhaka Stock Exchange (DSE) and Chittagong Stock Exchange (CSE). However, 
Sharia-based Islamic banks have been excluded from the study as their operating systems are not similar to conventional banks. 
Again, banks which have not adequate data available for the period of the study also have been excluded from the study. Finally, 
21 PCBs have been selected for the study to evaluate their performance based on CAMELS components. Data has been 
collected from the financial statements and annual reports of respective banks for the period of 2008 to 2018. Besides, the 
researcher visited the websites of DSE, CSE, Bangladesh Bank, and Bangladesh Securities and Exchange Commission to gather 
required data when necessary. The data has been analyzed and interpreted using tables and graphs. Analyses have been performed 
to assess the performance of the selected PCBs and identify the composite ratings of the selected PCBs based on CAMELS 
components. Six components of the CAMELS model (capital adequacy, asset quality, management efficiency, earnings ability, 
liquidity, and sensitivity to market risk) are used as variables. 
 
4. Overview of Benchmarking and Composite Rating of PCBs in Bangladesh 
To benchmark each component of CAMELS, they are to be evaluated on the scale of "1" to "5" rating in ascending order.  
Each component has a well thought out scale of rating based on the prevailing financial and economic conditions. Table 2 shows 
the details of the conversion of the CAMELS financial ratios to the progressive scale, which starts from "1" as strong to "5" as 
weak and for each equation used after relying on many previous studies to develop these ratios. Bangladesh Bank also follows the 
same formula and criteria whenever to examine the CAMELS rating for the banks. 
 
Table 2. Benchmarking under the CAMELS Rating System 

 

Code CAMELS Component Ratio‟s Ranking 

1 2 3 4 5 

C Capital Adequacy (CRAR) > 11% 8 - 11% 4 - <8% 1 - 4% < 1% 

A Asset Quality (NPL to 
Total Loan Ratio) 

< 1.5% 1.5 - 3.5% 3.5 - 7% 7 - 9.5% > 9.5% 

M Management Efficiency 
(Operating Expense to 

Operating Income Ratio) 

< 25% 26 - 30% 31 - 38% 39 - 45% > 46% 

E Earnings Ability (ROA) > 1.5% 1.25 - 1.5% 1.01 - 1.25% 0.75 - 1.00% < 0.75% 

L Liquidity (ADR) <60% 60 - 65% 65 - 70% 70 - 80% >80% 

S Sensitivity (P/E) <10% 10-15% 15%-20% 20%-25% >25% 

Source: (Majithiya & Pattani, 2010; Babar & Zeb, 2011; Sarwar & Asif, 2011; Masngut & Rahman, 2012)  
 

Composite rating assigns on a numerical scale "1" to "5", where "1" indicates the highest rating of the bank, which 
specifies: the most robust performance of the bank and best management practices relevant to the bank's size, complexity 
including risk profile and the level of minimum supervisory apprehension. Whereas, rating "5" shows the lowest rating of the 
bank and indicates the most decisively deficient level of performance of the bank and insufficient management practices relevant 
to the bank's size, complexity including risk profile, and the maximum level of supervisory concern. The following Table 3 is 
showing the composite rating, which is used to evaluate the performance and identify the position of the banks in the market. 

 
Table 3. Composite Rating and its Interpretation 
 

Composite Rating  Range Description Rating Analysis Interpretation 

1 1- 1.4 Strong Strong and sound in every aspect, no intensive supervisory responses are required.  

2 1.5-2.4 Satisfactory Fundamentally sound with modest correctable weakness, limited supervisory response.  

3 2.5-3.4 Fair A combination of weaknesses, if not redirected the weaknesses will become severe. Watch 
category. Pre-requisites are more than regular supervision. 



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4 3.5-4.4 Marginal Excessive weaknesses, unless adequately addressed, could impair the future viability of the 
bank. Requires close supervision. 

5 4.5-5 Unsatisfactory High risk of failure in the immediate period. The bank should be under constant 
supervision/cease and desist order. 

Source: Credit Rating Agency of Bangladesh Ltd. (2020)  
 

The classification grades are usually divided into the six components of the mentioned standard according to the 
following weights for each system component or according to the monetary authority, as shown in Table 4. 
 
Table 4. CAMELS Components‟ Weights 
 

Item C A M E L S 

Weight 20% 20% 25% 15% 10% 10% 

           Source:  (Dirheb, 2010; Shakara, 2012; Masood, Ghauri, & Aktan, 2016) 
 
5. Data Analysis and Discussion 
5.1 Composite Range for CAMELS Rating 
In this composite study range of the selected PCBs using the CAMELS components has been calculated for the year 2008 to 
2018.  Table5 below provides the outcomes of CAMELS components of the selected PCBs along with their ratings. The value 
of each CAMELS component has been shown afterward in the figures separately. From Table 5 and the following Figures 
(Figure 1-6) rating of each selected bank based on CAMELS components can be comprehended easily. 
 
Table 5. Outcomes of CAMELS Components of the PCBs (FY 2008-2018) 
 

Code Banks C R A R M R E R L R S R 

A AB Bank 10.98 2 6.25 3 45.65 4 1.23 3 87.01 5 109.90 5 

B Bank Asia 12.16 1 3.94 3 39.04 4 1.31 2 83.33 5 9.58 1 

C BRAC 12.55 1 5.28 3 50.28 5 1.39 2 83.07 5 14.73 2 

D City 12.63 1 5.81 3 49.14 5 1.34 2 80.52 5 13.37 2 

E DBBL 12.57 1 3.63 3 56.29 5 1.36 2 76.52 4 17.67 3 

F Dhaka 11.82 1 4.78 3 38.76 3 1.17 3 85.17 5 9.43 1 

G EBL 12.53 1 2.87 2 39.87 4 1.74 1 88.13 5 12.07 2 

H IFIC 11.06 1 5.27 3 52.81 5 1.17 3 83.66 5 16.31 3 

I Jamuna 11.75 1 4.65 3 44.37 4 1.38 2 77.73 4 8.50 1 

J Mercantile 11.42 1 3.81 3 45.60 4 1.21 2 83.15 5 8.59 1 

K MTB 11.43 1 3.51 3 53.93 5 1.00 4 81.15 5 12.35 2 

L NCC 12.06 1 4.99 3 51.73 5 1.49 2 85.42 5 8.32 1 

M ONE 11.56 1 4.89 3 43.88 4 1.65 1 84.26 5 8.21 1 

N Premier 11.43 1 5.09 3 57.34 5 1.35 2 84.37 5 8.66 1 

O Prime 13.03 1 4.32 3 43.98 4 1.25 2 82.57 5 12.57 2 

P Pubali 11.90 1 5.34 3 26.70 2 1.15 3 83.48 5 14.04 2 

Q SEBL 11.51 1 4.42 3 29.44 2 1.25 2 68.91 3 2.80 1 

R Standard 11.93 1 3.71 3 49.79 5 1.40 2 85.69 5 9.12 1 

S Trust 12.39 1 3.45 3 49.04 5 0.98 4 82.02 5 7.64 1 

T UCBL 10.70 2 4.51 3 45.51 4 1.24 
 

3 80.42 5 10.98 2 

U Uttara 12.28 1 6.22 3 51.60 5 1.24 
 

3 67.11 3 9.99 1 

Source: Researcher‟s Calculation 



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Whereas, C= Capital Adequacy (CRAR), A = Asset Quality (NPL to Total Loan Ratio), M = Management 
Efficiency (Operating Expense to Operating Income Ratio), E= Earnings Ability (ROA), L= Liquidity Ratio (Advance to 
Deposit Ratio), S = Price/Earnings Ratio, R = Rating. 
 
5.1.1 Capital Adequacy 

 
Figure 1 shows the composite ratings of the selected 
PCBs concerning CRAR. It is understandable from 
the figure and Table 5 that among the 21 banks most 
of the banks have the CRAR above 11%, and 
according to the CAMELS composite rating, most of 
the banks have reached the highest level. Only AB 
and UCBL have earned rating 2 with average CRAR 
below 11%. 
 
 

Figure 1. Composite Rating of the Selected PCBs concerning CRAR 
 

5.1.2  Asset Quality 
The most significant indication to show the asset 
quality in the loan assortment is the ratio of gross non-
performing loans (NPLs) to total loans. Figure 2 
displays the composite ratings of the selected PCBs 
concerning asset quality for the year 2008 to 2018. 
From Table 5, it is observed that among the 21 PCBs, 
only EBL obtains 'satisfactory' rating. The rest 20 
banks have been facing challenges with their classified 
loan. Because of the weak management of the loan 
portfolio and lack of diversification in their asset 
portfolio, most of the PCBs fail to generate sufficient 
financial returns. Moreover, these banks require 
maintaining higher provision as their NPL grows day 
by day. It creates pressure on banks' profitability too. 

Figure 2. Composite Rating of the Selected PCBs concerning NPLs 
 
5.1.3 Management Efficiency 

Management efficiency is an essential pre-requisite 
for the strength and growth of any bank. Figure 3 
shows the efficiency ratio of PCBs from the year 
2008-2018. It is evident from Table5 that most of 
the banks perform poorly to show their management 
efficiency. Among the 21 sampled banks, 10 banks 
get 5 (unsatisfactory) grading points, and 8 of them 
got 4 grading points. Unfortunately, no bank falls 
under the 'strong' position, and only Pubali and 
SEBL get „satisfactory‟ ratings. 
 
 

Figure 3. Composite Rating of the Selected PCBs concerning Expense-Income Ratio 
 

 
Therefore, it is clear that the PCBs of Bangladesh are very inefficient in the management field. This weakness is 

represented by the management's inability to adjust the banking policy on sound bases. This also indicates that management has 
no plans to develop future banking policies as it has been observed during the last 11 years. 
 
 

Efficiency Ratio

0

10

20

30

40

50

60

70

A B C D E F G H I J K L M N O P Q R S T U

Banks

%

A B C D E F G H I J K L M N O P Q

R S T U

CRAR

0

2

4

6

8

10

12

14

A B C D E F G H I J K L M N O P Q R S T U

BANKS

%

A B C D E F G H I J K L M N O P

Q R S T U

Classified Loan

0

1

2

3

4

5

6

7

A B C D E F G H I J K L M N O P Q R S T U

Banks

%

A B C D E F G H I J K L M N O P

Q R S T U



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5.1.4 Earnings Ability 
                                                                                                                                                                                                                              

Figure 4 is showing the ROA of the selected 
banks from 2008-2018. Here it is observed from 
Table 5 that among 21 banks, the ROA of EBL 
is higher (1.74%). ONE bank has also reached 
the highest level (1.65%) of „earnings‟ ratings. 
According to Table5, the performance of the 
other 18 banks is either „satisfactory‟ or „fair‟. 
However, MTB and Trust bank show 
„unsatisfactory‟ performance during the period of 
study. „Earnings‟ achieved by these banks is not 
within the required level. This means that the 
banks incur high expenses and have doubtful 
debts,    which also affected the decline in profits. 
And the banks need strong strategies to reduce 
costs. 

Figure 4. Composite Rating of the Selected PCBs concerning ROA 
 
5.1.5 Liquidity 

Figure 5 is showing the advance to deposit ratio of 
the 21 banks for the year 2008-2018. It is observed 
from Table5 that except SEBL and Uttara bank, most 
of the banks‟ ADR are alarmingly more than 80%. It 
is meant that in terms of liquidity, the banks‟ 
performance is not „satisfactory‟ or even „fair‟. Instead, 
their performance is „unsatisfactory‟ and „marginal‟. 
The probable cause of most banks' sufferings from a 
lack of liquidity is due to their low realized profits, 
non-performing loans, and an increase in 
expenditures. 
 
 

Figure 5. Composite Rating of the Selected PCBs concerning ADR 
 
5.1.6 Sensitivity 

It is seen from Table 5 that the PE ratio of SEBL shows 
very 'strong'. Performances of most other selected banks 
are between 7% and 17% except AB. Unfortunately, the 
PE of AB bank is very 'unsatisfactory'. Figure 6 shown 
beside expresses the PE ratios of the selected banks. If 
the PE ratio of any bank is too high, then investors 
assume the stocks as overvalued and that doesn't express 
a strong rating of the bank. So from the analyst, the PE 
ratio between 05-15% is better, which may express 
'strong', 'satisfactory', or 'fair' performance of the banks. 
In this study, concerning PE ratio of most of the banks 
has a fair/satisfactory/strong rating except AB bank. 
The Higher PE ratio of the banks expresses the 
overvaluation of their stocks. 

Figure 6. Composite Rating of the Selected PCBs concerning PE  
 
5.1.7 Combined Rating 
After depicting the CAMELS components in the previous figures, the study has reached at the final stage now. Table 6shows the 
final score for each selected bank. 

ROA

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

A B C D E F G H I J K L M N O P Q R S T U

Banks

%

A B C D E F G H I J K L M N O P Q

R S T U

ADR

0

20

40

60

80

100

A B C D E F G H I J K L M N O P Q R S T U

BANKS

%

A B C D E F G H I J K L M N O P

Q R S T U

P/E Ratio

0

10

20

30

40

50

60

70

80

A B C D E F G H I J K L M N O P Q R S T U

Banks

%

A B C D E F G H I J K L M N O

P Q R S T U



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Table 6. Combined Rating of CAMELS Components of PCBs with Weights (FY 2008-2018) 
 

Banks 
 

C (20%) A (20%) M 
(25%) 

E (15%) L (10%) S (10%) CR Position 

AB Bank 2 3 4 3 1 5 3.5 Marginal 

Bank Asia 1 3 4 2 1 1 2.7 Fair 

BRAC 1 3 5 2 1 2 3.1 Fair 

City  1 3 5 2 1 2 3.1 Fair 

DBBL 1 3 5 2 2 3 3.1 Fair 

Dhaka 1 3 3 3 1 1 2.6 Fair 

EBL  1 2 4 1 1 2 2.5 Fair 

IFIC 1 3 5 3 1 3 3.3 Fair 

Jamuna 1 3 4 2 2 1 2.6 Fair 

Mercantile 1 3 4 2 1 1 2.7 Fair 

MTB 1 3 5 4 1 2 3.4 Fair 

NCC 1 3 5 2 1 1 3.0 Fair 

ONE 1 3 4 1 1 1 2.6 Fair 

Premier 1 3 5 2 1 1 3.0 Fair 

Prime 1 3 4 2 1 2 2.8 Fair 

Pubali 1 3 2 3 1 2 2.5 Fair 

SEBL 1 3 2 2 3 1 2.0 Satisfactory 

Standard 1 3 5 2 1 1 3.0 Fair 

Trust 1 3 5 4 1 1 3.3 Fair 

UCBL 2 3 4 3 1 2 3.2 Fair 

Uttara 1 3 5 3 3 1 2.9 Fair 

Source: Researcher‟s Calculation 
 

Where, C= Capital Adequacy (CRAR), A = Asset Quality (NPL to Total Loan Ratio), M = Management Efficiency 
(Operating Expense to Operating Income Ratio), E= Earnings Ability (ROA), L= Liquidity Ratio (Advance to Deposit Ratio), 
S = Price/Earnings Ratio, CR = Composite Rating. 

From Table- 6, it is found that out of 21 banks, none of the sample banks can achieve the 'strong' position and only 
one bank (SEBL) can secure a 'satisfactory' mark. Most of the sampled banks (19 in numbers) have achieved a 'fair' position that 
is 90% of the whole sample. Therefore, these banks need to be controlled and followed-up and develop considerable cost 
reduction programs. Unfortunately, AB bank narrowly slips from „fair‟ position and becomes rated “marginal” in their composite 
rating that is the lowest rating among the sample banks. Therefore, AB is at risk and may lead to failure. The bank needs to 
develop reform and follow-up programs as soon as possible to avoid financial failure. Also, it needs to review the types of 
provided loans. 

 
6. Conclusion 
The banking sector is playing a major role to materialize most of the transactions happening throughout the world. Performance 
appraisal and overall evaluation help both banks and their stakeholders to assess the outcomes of the bank‟s policies and 
operations in monetary terms. Since PCBs have dominated the whole financial sector of Bangladesh, therefore, it was 
essential to assess banks' ratings in the market and evaluate the performance for both banks and its stakeholders to 
assess the outcomes of every bank's policies and operations. In this study, the CAMELS rating system was employed through the 
benchmarking approach on 21 sampled PCBs of Bangladesh. Through the value of a composite rating for each selected bank, the 
position of these banks has been realized. It is seen that most of the PCBs have sufficient capital adequacy. The earning 



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performance of these banks is more or less worthy. Their PE ratio is also sensible. But the banks have been facing challenges 
with their classified loan. The management efficiency of these banks is very modest. And in terms of liquidity, the banks‟ 
performance is not satisfactory as well.  

Therefore, the policymakers of the related lowest ranking banks have to carry out the required steps to overcome their 
weaknesses and get better their performance. And it is expected that the outcomes of this research work would be useful for 
administrators of the selected PCBs in Bangladesh to recover their monetary crises and develop strategies that would improve 
their operational performance and banking activities as well. 
 
6.1 Limitations of the Study and Scope for Further Research 
The study is not liberal from limitations. It is mainly based on secondary data, so a lack of adequate and necessary data might 
affect the research. Even because of different constraints with social patterns in Bangladesh, it was felt unable to collect 
information about the PCBs of Bangladesh, mostly when annual data of each bank were not available digitally. Therefore, all the 
PCBs were not included in the study. Again, the banks which are not listed in the capital markets of Bangladesh, i.e., DSE or 
CSE, were excluded from this study. The study has used only one ratio for evaluating the CAMELS. P E  ratio was used to 
measure the sensitivity to market risk. In the future, therefore, a study with a much larger sample of commercial banks in 
Bangladesh with the inclusion of all CAMELS components may give a better representation. For more research, the study can 
add some samples by adding a time series or total bank samples. More ratios could be incorporated to signify each component of 
CAMELS. 
 
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