A Critical Assessment of the Financial Performance of Banks in...

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A Critical Assessment of the Financial Performance of Banks in United Kingdom using

CAMELS Ratings and Altman Score Model

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Executive Summary

It is alleged that United Kingdom’s banking industry has been under a recovery process

following the financial meltdown in the period 2009-2010; the same has been supported by

the reports by Bba.org.uk. Similarly, the UK government is on record for bailing out two

public banks which equally attracted a number of changes in the regulations. The banking

system in UK is said to consist of numerous product markets such as personal loans, branches

operations, mortgage lending, credit card and SMEs funding incentives. In light of Herfindahl

Index score for various products 919 has been accorded to Mortgage lending while 1014 been

to credit card and 1153 going to branches; on the same, 1225 has gone to SME business

accounts portfolio. The purpose of the dissertation is to perform a comparative-explorative

analysis of the financial performance of banks in the United Kingdom for the period 2011-

2016 basing on CAMEL Ratings; then rely on Altman Score to predict corporate failure on

government-led and private-led banks. Sharp drops were evident in Barclays Bank in terms of

asset quality, management efficiency and liquidity. Therefore, the conclusion is that for the

bank the management has been struggling in effectively utilising its assets, optimising its

retained earnings and capacity to offset current liabilities using available current assets. sharp

drops were evident in Barclays Bank in terms of asset quality, management efficiency and

liquidity. Therefore, the conclusion is that for the bank the management has been struggling

in effectively utilising its assets, optimising its retained earnings and capacity to offset current

liabilities using available current assets. From the CAMELS Ratings analysis, the researcher

observed that Barclays Bank and Standard Chartered Bank have had financial challenges that

need to be looked into to safeguard the interests of shareholders. The assessment carried out

on the Bank of England and Royal Bank of Scotland indicated that ROE for the latter two

have positively been influenced by capital adequacy, liquidity, management efficiency, and

asset quality.

Keywords: CAMELS, Altman Score, Regression, United Kingdom, ROE

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Table of Contents

Executive Summary ................................................................................................................... 2

Declaration ................................................................................................................................. 4

Acknowledgement ..................................................................................................................... 5

List of Tables ........................................................................... Error! Bookmark not defined.

List of Figures ............................................................................................................................ 6

List of Exhibits ........................................................................................................................... 6

1.0 CHAPTER ONE: INTRODUCTION .................................................................................. 8

1.1 Background of the study .................................................................................................. 8

1.1.1 Overview of UK Banking Industry ........................................................................... 8

1.1.2 The banking system in UK ........................................................................................ 8

1.1.3 The impact of digital technology ............................................................................... 9

1.1.4 Policy Development .................................................................................................. 9

1.1.5 Compliance to New Regulatory Framework ........................................................... 10

1.1.6 Market size and growth ........................................................................................... 10

1.2 Purpose Statement .......................................................................................................... 11

1.3 Research Questions ........................................................................................................ 11

1.4 Research Objectives ....................................................................................................... 11

1.5 Value of the Research .................................................................................................... 12

1.6 Definition of Terms ........................................................................................................ 12

1.7 Dissertation Architecture................................................................................................ 12

2.0 CHAPTER TWO: LITERATURE REVIEW .................................................................... 14

2.1 Corporate Failure Model ................................................................................................ 14

2.1.1 Predicting corporate failure using Altman Score Model ......................................... 14

2.2 Review on financial performance of banks ................................................................ 14

2.3 A review of empirical studies on financial performance of banks ................................. 17

2.4 Summary of Chapter .......................................................................................................... 20

3.0 CHAPTER THREE: RESEARCH METHODOLOGY .................................................... 21

3.1 Research Design ............................................................................................................. 21

3.2 Research Philosophy ...................................................................................................... 22

3.3 Methodological Choice .................................................................................................. 24

3.4 Research approach.......................................................................................................... 24

3.4 Sampling, Models, and Instrumentation ........................................................................ 25

3.5 Data Analysis ................................................................................................................. 26

3.6 Ethical Consideration ..................................................................................................... 26

4.0 CHAPTER FOUR: DATA ANALYSIS ............................................................................ 27

4.1 Overview of Data ........................................................................................................... 27

4.3 Further analysis on CAMELS Model Application to Banks.......................................... 41

4.3.1 Applications based on correlation analysis ............................................................. 41

4.3.2 Applications based on regression analysis .............................................................. 44

4.3.3 Predicting Corporate Failure using Altman Score ................................................... 47

5.0 CHAPTER FIVE: CONCLUSION, IMPLICATIONS, RECOMMENDATIONS ........... 49

5.1 Recommendations .......................................................................................................... 51

5.2 Limitations ..................................................................................................................... 52

References ................................................................................................................................ 53

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Declaration

This is my original work and everything contained therein reflects original ideas of the

author. However, all borrowed ideas have been duly acknowledged.

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Acknowledgement

The dissertation has seen the light of day because of the support that came from my

supervisor. The guidance throughout the project was helpful and critical to have enabled me

to complete this dissertation in high quality. I also thank my parents and friends who

supported me in my studies in general.

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List of Figures

Figure 3.1: Research Onion Model

Figure 4.1: Graphical trend for Barclays Bank Capital Adequacy

Figure 4.2: Graphical trend for Barclays Bank Asset Quality

Figure 4.3: Graphical trend for Barclays Bank Management Efficiency

Figure 4.4: Graphical trend for Barclays Bank Liquidity

Figure 4.5: Graphical trend for SC’s Capital Adequacy

Figure 4.6: Graphical trend for SC’s Asset Quality

Figure 4.7: Graphical trend for SC’s Management Efficiency

Figure 4.8: Graphical trend for SC’s Liquidity

Figure 4.9: Graphical trend for BoE Capital Adequacy

Figure 4.10: Graphical trend for BoE Asset Quality

Figure 4.11: Graphical trend for BoE Management Efficiency

Figure 4.12: Graphical trend for BoE Liquidity

Figure 4.13: Graphical trend for RBS for Capital Adequacy

Figure 4.14: Graphical trend for RBS for Asset Quality

Figure 4.15: Graphical trend for RBS for Management Efficiency

Figure 4.16: Graphical trend for RBS for Liquidity

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List of Exhibits

Exhibit 4.1: Raw Data for Barclays Bank

Exhibit 4.2: Raw Data for Standard Chartered Bank

Exhibit 4.3: Correlation analysis for CAMELS’ Ratings for SC and Barclays Bank

Exhibit 4.4: Raw Data for Bank of England

Exhibit 4.5: Raw data for Royal Bank of Scotland

Exhibit 4.6: Correlation analysis between performance for RBS and BoE

Exhibit 4.7: Descriptive Statistics for Barclays Bank

Exhibit 4.8: Descriptive Statistics for Standard Chartered Bank

Exhibit 4.9: Descriptive Statistics for Bank of England

Exhibit 4.10: Descriptive Statistics for Royal Bank of Scotland

Exhibit 4.11: Correlation analysis for Barclays Bank

Exhibit 4.12: Correlation analysis for Standard Chartered Bank

Exhibit 4.13: Correlation analysis for Bank of England (BoE)

Exhibit 4.14: Correlation analysis for Royal Bank of Scotland

Exhibit 4.15: Regression Analysis 1


Exhibit 4.17: Altman Score Analysis and Implementation

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1.0 CHAPTER ONE: INTRODUCTION

The title of the dissertation reads as follows: “A Critical Assessment of the Financial

Performance of Banks in United Kingdom using CAMELS Ratings and Altman Score

Model”.

Further, is that the dissertation aimed to be a comparative analysis between government-

owned banks and private-managed banks i.e. selected ones been Royal Bank of Scotland

(RBS) and Bank of England (BoE) and Barclays Bank and Standard Chartered Bank.

1.1 Background of the study

1.1.1 Overview of UK Banking Industry

It is alleged that United Kingdom’s banking industry has been under a

recovery process following the financial meltdown in the period 2009-

2010; the same has been supported by the reports by Bba.org.uk

(2014). Similarly, the UK government is on record for bailing out two

public banks which equally attracted a number of changes in the

regulations. There are five major commercial banks that dominate the

banking industry in the UK namely Standard Chartered, HSBC, Lloyds

Banking Group and Royal Bank of Scotland. The fact of having the

above as dominant banks has created oligopolistic opportunities.

Moving on is that following the financial crisis the concentration in

terms of H-H index grew from 1401 to 1736 in the period 2007-2010.

The banking system in UK is regarded as one with high concentration

hence allowing for less competition (Bba.org.uk, 2014).

1.1.2 The banking system in UK

It is held that the banking system in UK is said to consist of numerous

product markets such as personal loans, branches operations, mortgage

lending, credit card and SMEs funding incentives. In light of

Herfindahl Index score for various products 919 has been accorded to

Mortgage lending while 1014 been to credit card and 1153 going to

branches; on the same, 1225 has gone to SME business accounts

portfolio (Bba.org.uk, 2014). From the findings above it means market

portfolios such as credit cards, personal loans and mortgages have been

relatively competitive (Theguardian.com, 2015). In addition, it is

indicated that due to the infrastructural capabilities brought by

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digitalisation it has become easier for the emerging entrepreneur

bankers to penetrate the market; the same stability has been attributed

to PRA’s swift new licensing regime. The speedy changing technology

has been said to enable new players to enter the banking industry

whilst making it more competitive.

1.1.3 The impact of digital technology

It is reported that regardless of the evolution of digital technology,

there has been considerable portion of banks that rely on traditional

process; these include incidences for use of cheques, paper work and

printed statements, cash payments and electronic transfers. But now

the emergence of the internet and adaptation of digital app has brought

revolution such as online debits, speedy remittances, account

management, virtual standing orders and easier and most convenient

access to bank accounts. A case of Barclays Bank has been reported as

that which supported £134 billion value transfers and remittances

through digital banking by the period 2013. This is not to mention the

fast paced emergence of mobile phone payments (Theguardian.com,

2015).

1.1.4 Policy Development

In the UK the aftermath of the financial crisis has led banks to operate

within tighter policies and requirements for compliance. For instance,

there is great attention to risk mitigation and monitoring of the same

for the banks, much requirements for security protocols and data

transfer oversight; thus banks in the UK are currently subject to such

regulations. In the same respect, the supervision focuses on ensuring a

balance in efforts for financial stability and anti-trust regulations in the

industry. The Financial Conduct Authority (FCA) has been entrusted

with the responsibility to monitor the banking industry. It is reported

that banks have a challenge to ensure they uphold appropriate culture

including implementing a workable operating model pegged to a

capacity to achieve feasible returns in the long-term.

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1.1.5 Compliance to New Regulatory Framework

As a result of the financial crisis, UK did announce measures that

would see the separation of the provided financial services with risk-

tolerant aspects inherent in financial markets; this is besides the

reinforcement of banking regulations (Bba.org.uk, 2014). On the other

hand, the European Banking Authority (EBA) is mandated to

undertaking periodic tests in checking stress degrees of national banks

so as to measure how effective they can mitigate financial shocks. It

was in the year 2013 when the UK’s new regulation framework took

shape; suffice to mention about The Financial Conduct Authority

(FCA) and Prudential Regulation Authority (PRA) are the institutions

entrusted with implementation and oversight of new regulations. For

instance, the PRA is mandated to create and ensure stability throughout

the entire financial system which supports 1,700 financial institutions.

Moreover, the FCA is charged with the responsibility to ensure

effectiveness in terms of financial market operations via upholding

acceptable conduct as well as enforcing laid out legislative banking

standards (See Bba.org.uk, 2014). It is worth mentioning about the

Financial Policy Committee (FPC) which was established to help the

Bank of England in its oversight and banking supervision including

supporting PRA in its functions. In point of fact, FPC has been

entrusted with measuring and eliminating systematic risk (Bba.org.uk,

2014).

1.1.6 Market size and growth

It is indicated that the contribution of the banking sector towards the

UK’s economy has been relatively high in comparison to other

countries. Looking at UK’s banking size it is reported that there exists

about 145 branches that obtain deposit including 100 foreign owned

banks. Also, in approximation half of banking assets in the UK

constitute of the residence portfolio managed by foreign investors. In

the same respect, top 10 subsidiaries hold a fund base of £2.8 trillion in

terms of assets in the period 2014 (Kpmg.com, 2014). Further research

indicates that the banking sector in UK has strongly contributed to the

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wider economy across the years. As a case example, is the tax

contribution that was generated prior to the occurrence of the financial

crisis which had approximated at 20%; however, due to the financial

meltdown the same dropped to 4% in the phase 2011/12. It is held that

the trend designates a decline to £1.3 billion from £7 billion through

the same has been reported to have improved slightly to a level of

£2.3billion by the period 2012/3 (Theguardian.com, 2015).

1.2 Purpose Statement

The purpose of the dissertation is to perform a comparative-explorative

analysis of the financial performance of banks in the United Kingdom for the

period 2011-2016 basing on CAMEL Ratings; then rely on Altman Score to

predict corporate failure on identified banks. Further in the scope, it was

sought to demonstrate the extent to which private banks perform better than

government owned banks in the United Kingdom.

1.3 Research Questions

The research questions addressed were as follows:

1) What has been the financial performance of privately-owned banks when

compared to government-owned banks in the United Kingdom basing on

the CAMEL Ratings?

2) What is the possibility of corporate failure of privately-owned banks when

compared to government-owned banks in the United Kingdom basing on

Altman Score?

3) What are the strategic policy implications of privately-owned banks when

compared to government-owned banks in the United Kingdom towards

future financial sustainability?

1.4 Research Objectives

In light of the research questions, the objectives addressed included the

following:

i. To analyse the financial performance of privately-owned banks

when compared to government-owned banks in the United

Kingdom basing on the CAMEL Ratings

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ii. To examine the possibility of corporate failure of privately-owned

banks when compared to government-owned banks in the United

Kingdom basing on Altman Score

iii. To recommend strategic paths for both privately-owned banks and

government-owned banks in the United Kingdom towards future

financial sustainability

1.5 Value of the Research

Banking industry is among the widely reviewed platforms of doing

business and there are numerous studies that have been achieved in

checking for financial performance. However, the unique contribution

of the current dissertation is that there was comparison of financial

performance of UK banks with a niche to comparing private-banks vis

a vis government owned banks using models such as CAMEL Ratings;

the research also uses Altman model to predict corporate failure. Thus,

making it a valuable resource for future policy makers and potential

investors in the banking sector after having comprehensive judgment

on the financial sustainability of the industry.

1.6 Definition of Terms

The main terms shall be:

Private Banks or Private-Owned or Private-Managed: This

shall refer to banks not necessarily private but rather those that are

governed by a board of directors appointed through voting by the

shareholders. Therefore, a bank shall be termed as private even if listed

in the London Stock Exchange for the reason its board of directors is

appointed by shareholders. The other connotation for a private bank

shall be those institutions that are not answerable to the government in

terms of management and core operations.

Government Banks or Government-Owned or Government-

Led: This shall refer to banks that are directly answerable to the

government and whose core operations are in the best interest of the

state e.g. directing monetary policy among others.

1.7 Dissertation Architecture

The structure of the dissertation consisted of six chapters:

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1st Chapter: The introduction of the dissertation was developed

in this part where the research questions, research objectives, problem

statement and value of the study were addressed.

2nd Chapter: The main literature review of the dissertation was

presented in this part. For instance, the debate on CAMEL model and

Prediction of Corporate Failure basing on Altman Score was presented.

3rd Chapter: The methodology of the research was featured in

this part. It consisted of the design of the research, data collection and

analysis and sampling criteria.

4th Chapter: In this chapter the main data analysis was

commenced especially implementation of both CAMEL Ratings

Model and the Altman Score.

5th Chapter: The main conclusion and implications of the

study’s findings were presented in this chapter.

6th Chapter: The key recommendations of the study have been

presented in this chapter. The recommendations focus on the direction

for future research; other recommendations point to the management of

banks and strategies for financial stability.

That done the next chapter of the dissertation focused on

developing literature review to shed more light on financial

performance of banks. Also, a deeper understanding of the proposed

models was evident.

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2.0 CHAPTER TWO: LITERATURE REVIEW

In this chapter the main models and theories to be applied in the research were developed

especially CAMELS Ratings and Altman score. The two were operationised so as to

serve different purposes namely assessment of financial performance processes in the

banking sector and then prediction of corporate failure in the banking sector. It was

equally important to present studies that in the past have relied on such models to report

bank failure or financial performance basing on different regions and economies.

2.1 Corporate Failure Model

2.1.1 Predicting corporate failure using Altman Score Model

Altman’s proposed multiple discriminant process has been central where it

incorporates weighted five financial ratios so as to enhance the predictive strength of the

model (Altman, 2000). In this model it generates a holistic discriminate score known as the Z

score or zeta model (Altman, 2000). The initial Z score model would be as follows:

Z = 0.012X1 + 0.014X2 + 0.033X3 + 0.006X4 +0.999X5

But later reported as shown below:

Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5

Where:

X1 = working capital/total assets

X2 = retained earnings/total assets

X3 = earnings before interest and tax/total assets

X4 = market value of equity/book value total liabilities

X5 = sales/total assets

Therefore:

A score lower than 1.81 indicated potential for bankruptcy

Greater than 3 being a state of financial soundness

2.2 Review on financial performance of banks

In most cases, financial performance in the banking industry has been monitored

and evaluated using ratio analysis. However, different methods of analysis have

been adopted and this is evident in the works by Tarawneh (2006) where the

financial evaluation of commercial banks in the region of Oman was administered

differently. For instance, the use of simple regression was considered whereby the

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effects of asset management, operational efficiency and bank size was checked

against the financial performance of five commercial banks in Oman. The

outcomes of the regression were that the banking institutions that recorded higher

aggregate capital, deposits, greater total assets and credits did not showcase an

improved performance in terms of profitability.

Similarly, in the works by Al-Tamini (2009) the focus was to address the

significant factors that influenced the financial trend of commercial banks, taking

the case scenario of the United Arab Emirates. The same sample consisted of both

Conventional and Islamic banks for the period dating 1996-2008. From the study,

it is seen that there was use of regression analysis which aimed to measure

variables such as return on asset (ROE), return on equity (ROE) being the

dependent variables. The findings indicated that liquidity influenced the

performance of the conventional banks and for the Islamic banks the key

influencing factors to were reported as cost and the number of branches.

In the case of Malaysian commercial banks, a study was commenced by Sufian

(2009) who sought to analyse the impacting factors on profitability for the period

2000-2004. In the results, it was depicted that increased credit risk and loan

concentration were causing a downward pressure on the Malaysian commercial

banks. However, on the opposite it was established that in the same region banks

that had greater capitalisation base, income growth generating from non-interest

streams, and increased operational expenses experience higher profitability

growth.

In a study based in Nigeria the financial performance of selected banks was

checked applying factor analysis method; the quest was to evaluate main factors

impacting on the financial performance of the banking system based on the results

from the sampled banks. The results depicted that independence of the executive

board members, political unrest, low capitalisation base and fraudulent

engagements served as determinant factors in influencing banking financial

performance in Nigeria (Okpara, 2009).

In the study by Spathis and Doumpos (2007) in their quest to assess financial

performance of banks, they sought to capture the relationship between risk and

return. The indications were that the higher the risk the more the investors would

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expect returns. The critical point is that in this study the two authors assessed

financial performance looking at the two variables i.e. risk and return.

In the Greek region, financial performance of banks was cross-examined basing

on the asset size relying on multi criteria methodology. The methodology

classified Greek commercial banks in respect to efficiency and profitability as

well as in lieu of their operational factors and return trends. In the outcome results,

it was depicted that in light of the commercial banks in Greeks they exhibited

positive correlation of interest margin, return on assets and capital adequacy

(Elizabeth et al, 2009).

In a different study there was established positive relationship between size and

capital adequacy; it was depicted that size positively impacted on performance of

commercial banks (Kosmidou, 2008). In the case of Pakistan commercial banks,

the effect of capital adequacy on GDP, operating efficiency and asset management

was established especially their role towards profitability. Other factors assessed

against financial performance of Pakistan commercial banks included bank-

specific factors and macroeconomic factors and their influence to profitability of

banks (Ali et al, 2011).

Similar to the study above, Abbas et al (2012) performed a comparative

evaluation on Pakistan commercial banks looking at key variables such as Return

on Assets (ROA), Return on Equity (ROE), and Return on Capital (ROC) making

application to top five commercial banks in the region; in the same study the

authors were seen to introduce new depend variable referred to as the “Return on

Operating Fixed Assets (ROFA)” and use correlation analysis to establish the

relationships across the selected financial factors.

The financial performance of Bangladesh banking sector was analysed in the

study by Nimalathasan (2008) where the scholar adopted CAMELs rating system.

Further, there was collection of secondary data picking from annual reports of the

involved banking firms for the period 1999-2006. Therefore, the financial

performance analysis basing on CAMELs ratings was applied to 6562 Branches

representing 48 mother banks situated in Bangladesh. The results from the

CAMELs ratings depicted that three of the banks did show a score of 01 meaning

strong while 31 banks scored 02 which was a satisfactory score while 7 banks

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scored 03 which interprets as a fair score. On the same findings, 4 banks gave a

score of 04 and other 2 banks scoring 05 such being an unsatisfactory outcome.

2.3 A review of empirical studies on financial performance of banks

As had been noted earlier is that financial performance of commercial banks and

even the same applying to non-financial institutions has been estimated and

analysed relying on ratio analysis. However, other procedures have been used to

perform such analysis like in the case of benchmarking and performance

measurement using budget (Avkiran, 2007). Hempel et al (2008) depicted that

financial performance of banks is developed by looking at the returns and their

risk reduction. Another study by Chien and Danw (2009) depicted that banking

financial performance was addressed basing on operational efficiency including

operational effectiveness where the two measures influence sustainability of

banks. Also, basing on the innovative two-stage model it was opined that sound

efficiency of banking firms was not an indicator of effectiveness.

Moving on other studies indicated to measure financial performance of banks

relying on parameters such as capital adequacy, interest margin and ROA that

equally depicted to positively correlate to satisfactory and superior customer

service (Elizabeth and Ellot, 2006). In checking financial performance of

commercial banks in the Arab gulf region, it was established that they had

recorded sound performance; this included them being sufficiently capitalised and

increased competition across the banks.

The financial performance evaluation carried out basing on privately owned

commercial banks in the region of Pakistan was by Shah and Jan (2014). The two

authors sampled from top ten commercial banks in the private sector and used

correlation and regression technique. From their findings they discovered that the

size of the banks and operational efficiency had negative relationship to Return on

Asset (ROA); on the other hand, the same study established a positive relationship

between Asset Management Ratio and ROA. In the same empirical study, it was

depicted that there existed positive relationship in the case of Interest Income and

Asset Management although a negative one emerged when compared to Interest

Income Operational Efficiency.

It was opined that realisation of higher capital deposits in total, total assets, credits

or deposits such did not guarantee sound performance in lieu of profitability of

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banks (Tarawneh, 2006). In the same respect, is that asset management together

with operational efficiency and bank size, did show to have positive relationship

to the financial performance of the selected banks. From the empirical analysis it

was established that operational efficiency and asset management for the selected

banks did have positive relationship to bank size.

Ahmad (2011) developed a study which focused on financial performance basing

on the case of Jordanian commercial banks where they paid attention to ROA as a

variable estimation for performance of selected banks. In the same study, there

was consideration of operational efficiency, bank size and assets management

where the latter three operationised as independent variables and how they

impacted on ROA. The results of the research depicted that there existed a strong

and negative linear relationship between ROA and bank size and the same case

applied to operational efficiency. In other words, bank size and operational

efficiency did not show strong linearity to ROA of the Jordanian commercial

banks. On the contrary, Ahmad did establish a positive linear relationship between

ROA and asset management ratio.

In the case of Pakistan banking financial performance, works by Khizer et al,

(2011) showed to pay close attention to profitability variables for the period 2006-

2009. In their findings the establishments were that there existed direct and

positive relationship in the case of profitability and operational efficiency; the

same positive nexus was established between operational efficiency and bank size

and assets management. The results as reported involved the selection of ROA as

the profitability indicator. In the works by Khizer et al (2011) it was affirmed that

ROE being a profitability indicator did show positive relationship to asset

management although a negative relationship emerging when compared to size

and operational efficiency.

Moving on still in a case of Pakistan there were attempts to measure the

performance of banks where Sidqui and Shoaib (2011) related their analysis to

capital structure. In the outcomes, the two noted that bank size had played a major

role towards the influence of profitability; return on equity was used as a measure

for profitability. Similarly, the same authors adopted Tobin’s Q model where they

used it to make estimations of the profitability of selected banks and their

performance. The results depicted positive relationship in the case of bank size,

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leverage ratio and assets. In the same region the study by Rivizi (2001) indicated

that profitability of banks had declined following the regression in technological

infrastructure of products and services delivery. As a solution it was proposed that

the banking firms were needed to have in place value-added services and quality

customer support base.

Further evaluations on bank performance look into the works by Olweny and

Shipho (2011); here, there was consideration of Market Power and Efficiency

Structure models. For instance, the model for Market Power asserted that a vibrant

external market enhances profitability; from this it is hypothesized that only

banking firms with large market share and highly differentiated portfolios in

relation to products are likely to enjoy monopolistic profits (See also

Athanasoglou et al, 2007).

On the other hand, ES theory holds that effective managerial including scale

efficiency is what leads to high concentration thereafter increasing profits. In light

of balanced portfolio theory, the bank performance framework has been attributed

to its portfolio, profitability, and shareholder wealth; due to this it has been opined

that banking performance draws from factors from internal and external

environment. The internal factors, for instance, refer to management efficiency,

bank size, risk management, and capital base. Then, the external factors point to

dynamics of interest rate, inflation, economic growth and ownership among others

(Athanasoglou et al, 2007).

Other studies did persist in addressing issues related to financial (See Al-Tamini,

2010 and Aburime, 2006). In these works, the authors aimed to assess the key

determinants underlying the performance of banks. To recap is that internal

factors point factors are those which are affected by the decisions undertaken by

the management including deliberations of the board; then external factors being

the unfolding of the business environment which supersede management control.

All these have an effect to the banks’ profits (Flamini et al., 2009).

In past studies attention went mostly to asset and liability management in the

banking firms where it was depicted that efficient management of both assets and

liabilities would boost or sustain profitability of banks including control and

mitigation of emerging risks (Flamini et al, 2009). Further, relying on multiple

regression analysis and correlations, Medhat Tarawaneh (2006) sought to test

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financial performance on sampled commercial banks in Oman region. The key

parameters sought included return on asset (ROA) as well interest income where

both as performance proxies served as dependent variables. On the other hand,

parameters such as operational efficiency, bank size and asset management were

operationised as the independent variables. The results depicted that there existed

a positive correlation in the dependent performance variables with operational

efficiency; however, a moderate correlation existed in the case of return on assets

(ROA) and bank size.

In the same study by Tarawaneh (2006) the author used ANOVA analysis where it

was used to capture the relationship between operational efficiency, bank size and

asset management and financial performance; in the results the F statistics gave a

significant score with 95% confidence margin. In light of the assertions by Al-

Obaidan (2008) was that large banks in Gulf region reported greater efficiency in

comparison to small banks. Further was that banks with higher capital base,

deposits, credits and total assets did not show to always generate stable

profitability performance. In the Jordanian case analysis, financial performance of

banks was analysed where ROA was operationised as the metric for dependent

variable while asset management and operational efficiency serving as the

independent variables. The results depicted that there existed strong and negative

linearity between ROA and the bank size (Almazari, 2011).

2.4 Summary of Chapter

The literature review developed captured the different ways past scholars used

CAMELS Ratings to evaluate and determine the financial performance of banks

in different regions. The researcher was keen on the manner of choice for the

variables where ROA, Management Efficiency and ROE appear to be widely

sought as the key indicators of financial performance. On the other hand, asset

management and operational efficiency being the main indicators used as

independent variables.

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3.0 CHAPTER THREE: RESEARCH METHODOLOGY

In this part of the analysis the research methodology was developed so as to pave

way for in-depth research based on the sample of the study and the proposed objectives.

Thus, the design of research and implementation has been fully explored. In recall the

main research objectives proposed included:

1) To analyse the financial performance of privately-owned banks



2) To examine the possibility of corporate failure of privately-owned



3) To determine the strategic policy implications of privately-owned


Kingdom towards future financial sustainability

Thus, a design needs to be developed which will act as a reliable pathway

to ensure the realisation of each objective.

3.1 Research Design

The focus of this dissertation was to depend on a study design that would

facilitate the researcher to seek solid data for use to achieve the research questions

and objectives of the study. The deliberation on the research design settled on both

(i) explanatory research and (ii) descriptive research. Notable, the audience is able

to see the existence of adequate exploration and assessment of studies in relation

to banks’ financial performance and the elements that can help enhance their

services. In addition, the analysis has examined the models and pertaining to

market share; these aspects constitutes the explorative component of the research.

With this groundwork in place, the researcher sensed and considered the

importance of more information that would enrich the study therefore the

necessity for a descriptive research. As suggested by Collins and Hussey (2013),

descriptive research seeks to explore and expound a topic while providing

additional information.

A descriptive research process defines a subject in more detail hence

filling gaps and enriching the understanding. In addition, the process entails the

collection of more data that helps to avoid use of models or guesses to forecast the

22

future (Creswell, 2013). The resort to explanatory research is justified because the

researcher was able to examine and assess new concepts in banks’ performance.

Further, descriptive research helps to enlighten more about the existing knowledge

on models such as Altman Score and CAMEL Ratings. According to Easterby-

Smith (2000), explanatory research refers to attempt made to connect ideas to

understand the cause and effect-basically, showing what is happening. Through

use of explanatory research, the investigator or researcher is able to note the way

things interact or coalesce (Morgan, 2014).

Accordingly, the current study relied on explanatory and descriptive

research designs. However, an important thing to note is that each design played

its purpose. A good example on this aspect is that descriptive research sought to

evaluate “what is happening” whereas explanatory research sought to assess “why

things happen the way they did”. In reference to this dissertation, the data

collected from secondary sources including books and journals needed to express

or indicate what was happening when relevant models are applied and use them to

establish respective bank’s financial performance. Upon establishment of data as

indicated, explanatory research was applied to interrogate why there was some

variances in some of the elements that were surveyed. In addition, the

explanations on the “why” would lead into causal determinations where one event

could be seen to cause or lead to another (Easterby-Smith, 2000). The current

dissertation required this approach because it was imperative to find the causal

relationship pertaining to how to use variables such as ROE and ROA in

determining the financial performance of banks and autonomous variables which

include asset efficiency and operational efficiency among others.

3.2 Research Philosophy

The concept of research philosophy entails the approach to be used to

source knowledge in the present dissertation and this comprise the knowledge

in terms of its nature and its development. The figure below represents a

“research onion” model by Saunders et al (2007).

23

Figure 3.1: Research Onion Model

Source: Saunders et al, 74)

The research onion model shows that the outer layer has four

philosophies viz.: pragmatism, positivism, interpretivism and realism. In

reference to the current dissertation, pragmatism philosophy shall inform the

approach used by the researcher. The philosophy states that selecting one

position such as axiology, ontology or epistemology is in practice idealistic or

impractical; for pragmatism approach the questions for the specific research

should be central in terms of informing the philosophical position to be

adopted or applied (Creswell & Clark, 2009). In this approach (pragmatism

philosophy), both quantitative and qualitative research methods are anticipated

in the pursuit to address a real-life problem. Essentially, pragmatism

philosophy applauds the use of interpretive and positivism to resolve a

problem (Oates, 2012).

In regard to ontology, pragmatism philosophy advocates that a

researcher takes the position of an external entity whereby any view expressed

is aimed at answering the research questions in the most appropriate way. In

terms of Epistemology, pragmatism philosophy posits that a researcher has the

option to use objective or subjective meanings to provide facts that answers a

research question; in addition, it equally focuses on the practical use to issues

via linkage of views to aid in data interpretation (Creswell, 2012). As regards

24

axiology, the concept of pragmatism proposes that values play a critical role in

interpreting outcomes using both objective and subjective reasoning. In

regards to approach, the chosen research philosophy applies mixed methods or

both quantitative and qualitative methods (Pare, 2009). In reference to this

dissertation, a pragmatic design was performed where the researcher was not

limited or restricted to particular methods but instead depend on several

methods to enrich exploration on the problem. A good example of this is

where data collected from secondary resources was further used in quantitative

methods particularly within numerical evaluations of Altman Score and

CAMEL Ratings models.

3.3 Methodological Choice

A number of research methods exists and one of them is the mixed

methods. The mixed methods entail the combination of both quantitative and

qualitative methods in a particular study; As underscored by Johnson et al

(2010), mixed methods facilitates more in-depth analysis and indulgence of a

particular phenomenon. There is a general consensus among scholars that

mixed method design research afford better indulgence and understanding on

the matter under consideration than if only one method is used (Creswell &

Clark, 2008). Tashakkori & Teddie (2011) emphasized that multiple method is

the core premise behind pragmatic philosophy. As noted by Creswell (2012),

qualitative research plays the role of investigation that entails the study of a

human problem or occurrence as exhibited with words, that records

comprehensive perspectives of informers and carry out in a normal setting.

In contrast, a quantitative research approach entails the study of a

human or social issue but in relation to testing theory that constitutes

variables, which is projected in numbers and assessed using numerical

procedures in order to establish if prognostic generalisations in the hypotheses

is true (Pare, 2009).

3.4 Research approach

The research approach concept comprises two main methods namely

inductive and deductive approaches. In exploratory study or (deductive

approach), the researcher depends on secondary study that may include a

review of available data or literature, or via the use of qualitative approaches

25

which may entail informal deliberations with employees, competitors,

consumers, or the management of an organisation; and may also involve a

more formal approaches via projective methods, case studies, in-depth

interviews, pilot studies and focus groups (Bowen, 2009). In essence, an

explanatory research refers to an inductive approach whose purpose is to find

patterns in a particular data set. In an Inductive analysis, the categories of

analysis, patterns, and themes are derived from the data; Bowen (2009) argues

that the patterns, and themes emerge or are drawn from the data instead of

being forced on them before the collection and analysis of data.

In the present study, the research approach comprises a mix of both

inductive and deductive questions, where the plan entails a combination of

both approaches, therefore using the theories of Altman and CAMELS for

financial performance for purposes of predicting organisation failure.

Essentially, stability and growth is representing some form of continuity and

prosperity over the long run. The current study has used descriptive approach

to define how the organisations achieve financial stability and growth and at

the same time exploratory approach was applied to show how the firms do it.

Basically, an explanatory research approach was meant to enlighten how

stability was attained and maintain.

3.4 Sampling, Models, and Instrumentation

The sample consisted of 4 commercial banks operating in the United

Kingdom both private and government owned banks. The main private banks

included Standard Chartered Bank and Barclays Bank Limited. The

government owned banks considered included Bank of England and The

Royal Bank of Scotland. The data was developed from their audited annual

statements for the period 2012-2016. The financial data was then used to

develop parameters of each of the models. The financial statements were

downloaded from the company’s websites which the researcher perused both

income statements and statement of financial position so as to pick key

variables that were converted to respective variables for both CAMELS

Ratings and Altman Score Models where the latter was used to predict

corporate failure.

26

3.5 Data Analysis

In the data analysis, the researcher used protocols that would help to

describe and correlate findings from one dimension to the other in light of

CAMELS Ratings Model. Therefore, for the qualitative analysis the researcher

was keener to rely on summative content analysis. On the bit of quantitative

research, the focus went to the use of numerical analysis such as descriptive

statistics where central tendency and dispersion rates were estimated relying

on mean, median, mode, and standard deviation. Moreover, Pearson product

Moment Correlation, Anova and Multiple Regression Analysis were the two

inferential statistics parameters that were used. Furthermore, Excel software

program was used to analyse data. Also, it was used to make graphs and pie-

charts with the aim to present data visually for clarity purposes.

3.6 Ethical Consideration

The central ethical concern in the current study was to ensure that the

narrations and arguments devoid of plagiarism. Thus, the study which is

mainly a desk research sought to provide reference to borrowed ideas and

material used in the dissertation. Essentially, the data used for the firms was

efficiently disclosed without manipulation in order to depict the true picture of

designated banking firms. Therefore, the data used reflects what is contained

in their financial statements as availed on respective websites.

27

4.0 CHAPTER FOUR: DATA ANALYSIS

The purpose of the dissertation was to undertake a comparative-explorative analysis

of the financial performance of banks in the United Kingdom for the period 2011-

2016 basing on CAMEL Ratings; then relying on Altman Score to predict corporate

failure on identified banks. Further, the analysis sought to demonstrate the extent to

which private banks perform better than government owned banks in the United

Kingdom. The main objectives of the research have been as follows:







iii. To determine the strategic policy implications of privately-owned


Kingdom towards future financial sustainability

4.1 Overview of Data

The data was acquired from the selected banks’ audited annual reports for the period

2012-2016. Therefore, the concern of the analysis was to check for the financial

performance in the period of five months down the years in order to have sound

judgment on the status of the banks. The data in the annual reports was downloaded

from the respective banks’ official websites and through reduction process coded in

the Excel spreadsheet. Exhibits 4.1-4.4 illustrate the analysed data for the selected

banks in terms of CAMELS Ratings. In other words, they are executed analysis for

CAMELS rating after analysing the financial data traceable in appendix 1-4.

Exhibit 4.1: Raw Data for Barclays Bank

Barclays Bank 2012 2013 2014 2015 2016

ROA 1.68% 2.12% 1.52% 1.91% 1.86%

ROE 0.06% 2.01% 1.28% 0.95% 3.96%

NIM 168.94% 86.81% 53.59% 28.60% -188.94%

Capital Adequacy 3.97% 4.83% 4.86% 5.88% 5.88%

Asset Quality 2.65% 2.89% 2.43% 2.41% 2.03%

Management Efficiency 652.03 19.02 23.60 32.55 6.75

Liquidity 8.78 0.75 2.79 2.49 2.31

28

From exhibit 4.1 above the trends for selected CAMELS Ratings for Barclays Bank is

as shown above. Earlier, the specifications for the CAMELS model had been

illustrated and for Barclays Bank it can said that each of the dimensions has been a

stable performance overtime but in other instances showing a sharp decline. For

instance, the trend for capital adequacy for Barclays Bank is as shown below.

Figure 4.1: Graphical trend for Barclays Bank Capital Adequacy

The trend for capital adequacy for the Barclays Bank depicts to have been increasing

from the year 2012-2016. It means the management has been in a position to cater for

the emerging needs for additional capital for the last five years.

Another important analysis went to asset quality where the trend depicts as follows.

Figure 4.2: Graphical trend for Barclays Bank Asset Quality

29

In terms of assets quality, the depiction is that Barclays Bank has had a declining trend for the

past five years. It means the management kept losing its ability to administer its assets over

the last five years.

Moving on below is a trend for Barclays Bank Management Efficiency ratio.

Figure 4.3: Graphical trend for Barclays Bank Management Efficiency

The trend for management efficiency shows a very deep destabilisation. It means at Barclays

Bank the management has been losing its capability to effectively utilise the retained

earnings. In other words, the management has not been in a position to raise sufficient capital

through retained earnings for the period 2012-2016. However, between 2013-2014 there is

indication management efficiency at Barclays Bank has been having a steady growth but this

is negligible compared to the previous deep destabilisation in the period 2012-2013.

The other depiction is for liquidity which can be used to interpret the degree to which

Barclays Bank for the period 2012-2017, the management has been in a position to

effectively identify, measure or monitor its liquidity position. It is the same as the capacity of

the bank to have been able to offset its short-term obligations. The trend is a shown below.

30

Figure 4.4: Graphical trend for Barclays Bank Liquidity

The indication is that in the period 2012-2017 Barclays Bank has been having a weak

liquidity position even if in the year 2013-2014 it had shown some stronger performance.

However, since the drop in 2012-2013 the liquidity has been somewhat weak. It means the

management has not been well successful in keeping good eye on the liquidity status of the

bank overtime.

The next similar analysis shall go to the case of Standard Chartered Bank. The raw data has

also been illustrated below for the period 2012-2016.

Exhibit 4.2: Raw Data for Standard Chartered Bank

Standard Chartered Bank 2012 2013 2014 2015 2016

ROA 2.87% 2.61% 2.34% 2.28% 2.01%

ROE 10.82% 8.97% 5.79% -4.53% -0.39%

NIM 24.82% 38.96% 52.28% 36.02% 20.29%


Asset Quality 1.38% 1.25% 1.60% 1.69% 1.61%

Management Efficiency 3.83 4.47 6.78 -6.96 -73.61

Liquidity 0.93 0.98 0.91 0.92 0.87

The trend for capital adequacy for Standard Charted Bank is as shown in figure 4.5 below.

31

Figure 4.5: Graphical trend for SC’s Capital Adequacy

The indication is that Standard Chartered Bank has had a growing trend for its capital

adequacy. It is an indication for increasing capacity of the management to cater for the

dynamic changing needs requiring additional capital. Indeed, inasmuch as the ability declined

in the period 012-2014 it shows to have improved in 2014-2015 though slightly declining in

2016. However, compared to Barclays Bank capital adequacy it is arguable that Standard

Chartered Bank has been struggling with its ability to generate additional capital to cater for

emerging needs in the business.

The other analysis shall look at asset quality performance at SC for the identified period. See

figure 4.6 below.

Figure 4.6: Graphical trend for SC’s Asset Quality

32

In the trend above it can be seen that asset quality at Standard Chartered Bank has actually

been stable since from 2013 down the years to 2016. Therefore, the management has been in

a position to effectively utilise its assets since 2013.

The trend of management efficiency for SC is as shown below.

Figure 4.7: Graphical trend for SC’s Management Efficiency

In the trend for management efficiency it can be seen that in 2012-2014 it has been growing

meaning at that period the management of Standard Chartered bank had capacity to generate

capital through retained earnings. However, in 2014 to 2016 the trend shows to have been

weak to even hit negative results in the year 2016. It means at present SC could be struggling

with its capital needs and the retained earnings are not sufficient to bail it. In other words, the

company lacks sufficient retained earnings to bail its capital needs.

Lastly, is the trend for liquidity for SC which has been depicted below.

33

Figure 4.8: Graphical trend for SC’s Liquidity

The liquidity performance for SC Bank shows to have been decreasing overtime meaning the

company’s management has not been in a position to effectively monitor, identify and control

the ability to cater for its current short-term obligations through its available current assets.

However, in the period 2012-2013 the trend shows to have increased but then going

downwards from 2013-2016.

The next question would be whether the CAMELS Ratings for Barclays Bank and Standard

Chartered Bank have anything in common or any correlated trends. In order to illustrate this,

a correlation matrix was developed as shown below.

Exhibit 4.3: Correlation analysis for CAMELS’ Ratings for SC and Barclays Bank

Correlation matrix (Pearson):

Barclays Bank Standard Chartered Bank

Variables Capital

Adequacy

Asset

Quality

Management

Efficiency

Liqu

idity

Capital

Adequacy

Asset

Quality

Management

Efficiency

Liqu

idity

Capital

Adequacy

1 -0.733 -0.088 0.413 0.915 0.663 -0.698 -0.647

Asset

Quality

-0.733 1 0.401 -0.739 -0.445 -0.785 0.805 0.986

Management

Efficiency

-0.088 0.401 1 0.204 -0.112 0.248 0.769 0.325

Liquidity 0.413 -0.739 0.204 1 0.018 0.947 -0.196 -0.829

Capital

Adequacy

0.915 -0.445 -0.112 0.018 1 0.323 -0.625 -0.315

Asset

Quality

0.663 -0.785 0.248 0.947 0.323 1 -0.306 -0.834

Management

Efficiency

-0.698 0.805 0.769 -0.196 -0.625 -0.306 1 0.707

Liquidity -0.647 0.986 0.325 -0.829 -0.315 -0.834 0.707 1

Values in bold are different from 0 with a significance level alpha=0.05

Source of Data: (Developed using Excel Correlation Analysis)

34

In the correlation matrix it can be seen that at no point is the trend for Barclays Bank

correlating to Standard Charted Bank; it means the CAMELS Ratings for each of the

institutions have been conditioned to the situations of the banks. In other words, the capital

adequacy, asset quality, liquidity and management efficiency for the two banks have not been

moving in the same direction. The reason for making such a judgment is due to the fact that

none of the p values are less than 0.05 which allows for 5% margin of error in terms of

claiming for a correlated trend.

Having said that the next analysis shifted to the trend covering the selected two government-

owned banks; in this case Royal Bank of Scotland and Bank of England. The raw data for the

mentioned banks is as shown below.

Exhibit 4.4: Raw Data for Bank of England

Bank of England 2012 2013 2014 2015 2016

ROA 0.00% 0.00% 0.00% 0.00% 0.00%

ROE 2.51% 3.28% 5.25% 5.27% 4.55%

NIM -0.55% -0.34% 0.12% 0.09% 0.12%


Asset Quality 0.00% 0.00% 0.00% 0.00% 0.00%

Management Efficiency 5.62 4.52 3.16 3.18 3.00

Liquidity 1.39 1.30 1.21 1.21 1.20

The trend for capital adequacy, asset quality, management efficiency and liquidity for the

Bank of England is as shown in exhibit 4.5 for the period 2012-2016. The trend is as shown

below using a graphical model for each of the CAMELS Ratings as estimated.

Figure 4.9: Graphical trend for BoE Capital Adequacy

35

Looking at the trend for the capital adequacy for the Bank of England, it can be seen that

from 2012-2014 it has been declining but then gradually rising towards 2016. It means

despite the decline from 2012-2014 the management of BoE has been capable of addressing

requirements for additional capital.

Figure 4.10: Graphical trend for BoE Asset Quality

In the case for Asset Quality the indication is that BoE has not had challenges nor successes

in terms of the management’s capacity to administer effectively the assets. The trend

indicates a neutral performance more or less.

Figure 4.11: Graphical trend for BoE Management Efficiency

Moving on is the performance for management efficiency for BoE which depicts to have

declined in the period 2012-2014 then rising a bit towards 2015 and slightly declining again

towards 2016; probably, this can be attributed to the BREXIT effect but just as an

36

unsubstantiated assumption. All the same, the indication is that at BoE the management

seemed to have had slight challenges in providing for required capital via retained earnings.

Figure 4.12: Graphical trend for BoE Liquidity

The trend for liquidity for BoE shows to have the same movement with that for management

efficiency. For instance, it depicts to have declined towards 2016. The overall judgment is

that the management for BoE has not effectively controlled and monitored the liquidity

position of the bank over time.

The other analysis shall go to the CAMELS Ratings for the Royal Bank of Scotland. The raw

data results are as shown below.

Exhibit 4.5: Raw data for Royal Bank of Scotland

Royal Bank of Scotland 2012 2013 2014 2015 2016

ROA 1.23% 1.05% 0.95% 1.58% 1.58%

ROE 99.80% 94.53% 49.81% 382.07% 752.49%

NIM 51.40% 41.37% 36.95% 55.80% 61.70%


Asset Quality 1.14% 2.19% 3.16% 4.15% 1.98%

Management Efficiency 0.68 0.44 -1.04 1.00 0.42

Liquidity 1.27 1.23 1.19 1.06 1.00

Capital adequacy performance for the RBS is as shown in figure 4.12. It depicts stability as

from 2013-2014 but then declining in the years 2015-2016. It means the management

somewhat struggled with addressing capital needs for the bank in the period 2014-2016. See

the trend below.

37

Figure 4.13: Graphical trend for RBS for Capital Adequacy

In terms of asset quality, the trend in figure 4.13 shows that in 2012-2015 it has been stable

and in the path 2016 showing to be a declining performance. All in all, it can be asserted that

the management of RBS has been consistent in effectively administering its assets despite the

decline in 2016.

Figure 4.14: Graphical trend for RBS for Asset Quality

38

In figure 4.14 below, the depiction is that from 2012-2014 the trend for management

efficiency has been a deep decline. It means at this period RBS management was not capable

of providing needed capital through the available retained earnings. But, the trend further

indicates that RBS had improved its management efficiency from 2014-2015 but then

declining one more time towards 2016.

Figure 4.15: Graphical trend for RBS for Management Efficiency

The liquidity performance for RBS as shown in figure 4.15 below indicates to have been

slightly going down from 2012-2016. It is indication that the management of the bank has not

sufficiently been in a position to identify, monitor and control the liquidity position of the

company.

Figure 4.16: Graphical trend for RBS for Liquidity

39

The next analysis was to show if there was any linearity between the trends for Bank of

England and Royal Bank of Scotland for their reductions made for its CAMEL Ratings.

Therefore, a correlation analysis was administered and the results are as shown in exhibit 4.6

below.

Exhibit 4.6: Correlation analysis between performance for RBS and BoE

Capital

Adequacy

Asset

Quality

Management

Efficiency

Liquidity Capital

Adequacy

Asset

Quality

Management

Efficiency

Liquidity

Capital

Adequacy

1

Asset

Quality

-0.6776 1

Management

Efficiency

-0.7712 0.3128 1

Liquidity -0.6770 0.1102 0.9680 1

Capital

Adequacy

0.4963 -0.3890 0.1060 0.1106 1

Asset

Quality

0.6841 -0.8068 -0.3727 -0.1440 0.2552 1

Management

Efficiency

-0.6410 0.8211 0.3005 0.2191 -0.5670 -0.3772 1

Liquidity -0.5117 0.9723 0.1433 -0.0815 -0.2956 -0.8145 0.7103 1

The shaded region is the point where RBS and BoE data can be compared linearly; for

instance, capital adequacy (0.4963), asset quality (-0.8068), management efficiency (0.3005)

and liquidity (-0.0815) depicts variations in linearity relationship. However, the actual

interpretation is that capital adequacy and management efficiency have been a moderate

linearity for BoE and RBS and asset quality and liquidity been a weak but negative linearity.

4.2 Descriptive Statistics

The descriptive statistics for the data specially to estimate the measure of central tendency

and dispersion rates in the financial information used for CAMELS Rating has been

developed next. This and more to be explicated in due course.

Exhibit 4.7: Descriptive Statistics for Barclays Bank

Barclays

Bank

Capital

Adequacy

Asset

Quality

Management

Efficiency

Liquidity

Mean 0.0508 0.0248 146.7900 3.4240

Median 0.0486 0.0243 23.6000 2.4900

Standard

Deviation

0.0081 0.0032 282.5909 3.0965

Range 0.0191 0.0086 645.2800 8.0300

Minimum 0.0397 0.0203 6.7500 0.7500

Maximum 0.0588 0.0289 652.0300 8.7800

Sum 0.2542 0.1241 733.9500 17.1200

Count 5 5 5 5

40

The descriptive statistics for Barclays Bank data depicts that the mean for capital adequacy

has been (.0508) and asset quality been at (0.0248), management efficiency (146.79) and

liquidity (3.4240). Only the standard deviation for management efficiency (282.59) show to

be greater than the mean implying that it has been the financial parameter that has deviated

from the mean performance.

Exhibit 4.8: Descriptive Statistics for Standard Chartered Bank

Standard

Chartered

Bank

Capital

Adequacy

Asset

Quality

Management

Efficiency

Liquidity

Mean 0.0714 0.0151 -13.0980 0.9220

Median 0.0724 0.0160 3.8300 0.9200

Standard

Deviation

0.0047 0.0018 34.2407 0.0396

Range 0.0113 0.0044 80.3900 0.1100

Minimum 0.0644 0.0125 -73.6100 0.8700

Maximum 0.0757 0.0169 6.7800 0.9800

Sum 0.3572 0.0753 -65.4900 4.6100

Count 5 5 5 5

The mean performance for Standard Chartered Bank has been captured: for instance, capital

adequacy (0.0714), asset quality (0.0151), management efficiency (-13.0980) and liquidity

(0.9220). However, the management efficiency also showing a standard deviation of 34.2407

which means it was the parameter that exceedingly deviated from the mean performance.

Exhibit 4.9: Descriptive Statistics for Bank of England

Bank of

England

Capital

Adequacy

Asset

Quality

Management

Efficiency

Liquidity

Mean 0.0093 0.0000 3.8960 1.2620

Median 0.0084 0.0000 3.1800 1.2100

Standard

Deviation

0.0016 0.0000 1.1422 0.0823

Range 0.0037 0.0000 2.6200 0.1900

Minimum 0.0076 0.0000 3.0000 1.2000

Maximum 0.0113 0.0000 5.6200 1.3900

Sum 0.0464 0.0000 19.4800 6.3100

Count 5 5 5 5

41

Exhibit 4.10: Descriptive Statistics for Royal Bank of Scotland

Royal

Bank of

Scotland

Capital

Adequacy

Asset

Quality

Management

Efficiency

Liquidity

Mean 0.0028 0.0252 0.3000 1.1500

Median 0.0028 0.0219 0.4400 1.1900

Standard

Deviation

0.0017 0.0116 0.7849 0.1151

Range 0.0045 0.0301 2.0400 0.2700

Minimum 0.0009 0.0114 -1.0400 1.0000

Maximum 0.0054 0.0415 1.0000 1.2700

Sum 0.0139 0.1262 1.5000 5.7500

Count 5 5 5 5

For the Bank of Scotland, the mean performance for the financial parameters depicts capital

adequacy (.0028), asset quality (.0252), management efficiency (.3000), and liquidity

(1.1500). The standard deviation for management efficiency is at 0.7849 indicating to be the

parameter that was not consistent to the mean performance.

Inference 1: The judgment from the descriptive statistics is that only management efficiency

for all the banks i.e. privately-owned and government-controlled that shows to have

increasingly deviated from the mean performance

4.3 Further analysis on CAMELS Model Application to Banks

4.3.1 Applications based on correlation analysis

In order to discuss further on CAMELS Ratings explained above, the researcher will then

move to introducing detailed correlations and regressions so as to confirm how the financial

performance of the selected banks have impacted on key profitability trends namely ROE,

ROA and NIM. In fact, from the onset it was noted that the three would be adopted as the

main dependent variables in the quest to determine the influence of the selected CAMEL

Ratings to the profitability of the banks.

ROA = f (CA, L, AQ, ME) ……. (Model One)

ROE = f (CA, L, AQ, ME) ……. (Model Two)

NIM = f (CA, L, AQ, ME) ……. (Model Three)

The three models are the way in which the regression model may be effected and

determination made as to whether capital adequacy, liquidity, asset quality and management

efficiency have positively influenced the different profitability measures for private-owned

banks and government owned banks and whether the same has differences. In other words,

have private-owned banks had positive influence on profitability performance than

42

government owned banks? Or vice versa? The detailed analysis shall be developed in due

course of the report.

However, for the purpose of the present dissertation on the equation model II was

implemented and hopefully the two other equation models may be pursued in future research.

Exhibit 4.11: Correlation analysis for Barclays Bank


Variables ROA ROE NIM Capital

Adequacy

Asset

Quality

Managemen

t Efficiency

Liquidit

y

ROA 1 0.353 -0.156 0.345 0.297 -0.336 -0.521

ROE 0.353 1 -0.912 0.641 -0.585 -0.632 -0.615

NIM -0.156 -0.912 1 -0.811 0.851 0.603 0.499

Capital

Adequacy

0.345 0.641 -0.811 1 -0.678 -0.771 -0.677

Asset Quality 0.297 -0.585 0.851 -0.678 1 0.313 0.110

Management

Efficiency

-0.336 -0.632 0.603 -0.771 0.313 1 0.968

Liquidity -0.521 -0.615 0.499 -0.677 0.110 0.968 1


The shaded region features the area that can be used to make judgment on the level at which

ROA, ROE and NIM can be justifiably said to have linear relationship to capital adequacy,

asset quality, management efficiency and liquidity of Barclays Bank. Clearly, only capital

adequacy and ROA (.345) and ROE (.641) indicate a moderate and strong linearity meaning

they positively have moved in the same trend performance. It means better performance of

capital adequacy has been a better performance for ROA and NIM. But, NIM (-0.811) shows

a negative and weak linearity meaning there is inverse relationship to capital adequacy at

Barclays Bank. Moving on, asset quality shows to have a positive linearity to ROA (0.297)

and NIM (0.851); management efficiency (.603) and liquidity (.499) also depict a positive

and strong linear relationship with NIM. However, a negative linearity is evident between

asset quality (-.585) and ROE, management efficiency (-.632) and ROE; the same case

applying to liquidity (-.521) which shows negative linearity to ROA and liquidity (-.615) and

ROE. In general outlook, it can be assumed to be a strong argument that asset quality,

management efficiency and liquidity at Barclays Bank has not significantly related to the

performance under ROE and ROA of the bank but has been positive to NIM.

43

Exhibit 4.12: Correlation analysis for Standard Chartered Bank


Variables ROA ROE NIM Capital

Adequacy

Asset

Quality

Management

Efficiency

Liquidity

ROA 1 0.808 0.040 -0.252 -0.740 0.739 0.721

ROE 0.808 1 0.115 -0.577 -0.837 0.511 0.585

NIM 0.040 0.115 1 -0.809 0.074 0.660 0.305

Capital Adequacy -0.252 -0.577 -0.809 1 0.255 -0.567 -0.296

Asset Quality -0.740 -0.837 0.074 0.255 1 -0.377 -0.815

Management

Efficiency

0.739 0.511 0.660 -0.567 -0.377 1 0.710

Liquidity 0.721 0.585 0.305 -0.296 -0.815 0.710 1


For the case of Standard Chartered Bank, it shows capital adequacy and ROA (-.252), ROE (-

.577) and NIM (-.809) have not had supported relationship. The same case for asset quality

where ROA (-.740), ROE (-.837) show a negative linearity and only a weak but positive

relationship can be justified for NIM (.074). Moving on management efficiency depicts to

have strong significant relationship to ROA (.739), ROE (.511) and NIM (.660); the same

case for liquidity given the significance results for ROA (.721), ROE (.585) and NIM (.305).

Compared to Barclays Bank, capital adequacy, asset quality, management efficiency and

liquidity depict a stronger and significant relationship to profitability performance.

That been said the next analysis shall go to correlation analysis for government-led banks

selected in the report. They included Bank of England and Royal Bank of Scotland.

Exhibit 4.13: Correlation analysis for Bank of England (BoE)

Bank of England ROA ROE NIM Capital

Adequac

y

Asset

Quality

Managemen

t Efficiency

Liquidit

y

ROA 1

ROE 0.3525 1

NIM -0.1556 -0.9118 1

Capital Adequacy 0.3448 0.6409 -0.8109 1

Asset Quality 0.2971 -0.5846 0.8507 -0.6776 1

Management

Efficiency

-0.3361 -0.6316 0.6032 -0.7712 0.3128 1

Liquidity -0.5211 -0.6151 0.4986 -0.6770 0.1102 0.9680 1

The correlation matrix for Bank of England captures the degree to which capital adequacy,

asset quality, management efficiency and liquidity relate to ROA, ROE and NIM have been

44

captured. Clearly, capital adequacy shows positive relationship to ROA (.3448) and ROE

(.6409) but a negative correlation to NIM (-.8109). Asset quality and NIM (.8507) depict a

significant and strong correlation and the same been evident under management efficiency

and NIM (.6032) and liquidity and NIM (.4986).

Exhibit 4.14: Correlation analysis for Royal Bank of Scotland

Royal Bank of

Scotland

ROA ROE NIM Capital

Adequacy

Asset

Quality

Management

Efficiency

Liquidity

ROA 1

ROE 0.8599 1

NIM 0.9584 0.8630 1

Capital Adequacy -0.9117 -0.8197 -0.9359 1

Asset Quality 0.1917 0.0536 -0.0908 0.1009 1

Management

Efficiency

0.6916 0.3667 0.6960 -0.8281 -0.0968 1

Liquidity -0.8114 -0.9186 -0.7076 0.6511 -0.4350 -0.2153 1

In the case of Bank of England, the evident observation is that management efficiency has

positive and significant relationship to ROA (.6916), ROE (.3667) and NIM (.6960). It is the

main financial parameter within CAMEL Ratings that shows to have significant positive

relationship to profitability of the bank. Asset quality, on the other hand, shows to have weak

but positive linear relationship to ROA (.1917) and ROE (.05360). All other financial

parameters such as capital adequacy and liquidity have all the instances showing negative

linear relationship with various levels of the RBS profitability trend.

4.3.2 Applications based on regression analysis

In the regression model the focus is to practically determine the three model equations

illustrated earlier on the link across NIM, ROA, and ROE to capital adequacy, liquidity,

management efficiency and asset quality. The regression results are as depicted in exhibit

4.15-4.18. But, it was stated earlier that the following equation model would be considered.

ROE = f (CA, L, AQ, ME) ……. (Model Two)

However, due to regression error occasioned by few observations in the data portfolio i.e.

because the years covered were 2012-2016 the outputs could not be generated sufficiently.

Therefore, it was difficult to analyse the values for Anova and beta values in the regression

models for each bank. In that case, the researcher could not proceed to state whether model

two equation could be acceptable to arrive at any decisions for single banks. Principally

speaking, the regression analysis was not effectively executed in the present dissertation

basing on individual banks but a random model was done for the two banks combined to be

45

able to make a general evaluation on the banks. The results for Barclays Bank combined with

Standard Chartered Bank are as shown below.


SUMMARY OUTPUT

Regression Statistics

Multiple R 0.8213

R Square 0.6746

Adjusted R Square 0.4143

Standard Error 0.0352

Observations 10

ANOVA

df SS MS F

Significan

ce F

Regression 4 0.0128 0.0032 2.5916 0.1622

Residual 5 0.0062 0.0012

Total 9 0.0190

Coefficien

ts

Standar

d Error t Stat P-value

Lower

95%

Upper

95%

Lower

95.0%

Upper

95.0%

ROE 0.7289 0.2452 2.9721 0.0311 0.0985 1.3593 0.0985 1.3593

Capital Adequacy -6.4704 2.5349 -2.5526 0.0511 -12.9864 0.0457

-

12.9864 0.0457

Asset Quality -13.4465 4.5918 -2.9284 0.0327 -25.2500 -1.6429

-

25.2500 -1.6429

Management

Efficiency 0.0001 0.0002 0.4307 0.6847 -0.0004 0.0006 -0.0004 0.0006

Liquidity -0.0194 0.0181 -1.0706 0.3333 -0.0659 0.0271 -0.0659 0.0271

The output for the adjusted R Square gives a result of 0.4143 meaning 41.43% of the cases

for capital adequacy, asset quality, management efficiency and liquidity of Barclays Bank

and Standard Chartered Bank explains the trend for ROE. Therefore, it can be concluded that

the two selected private banks do receive as much as 41.43% of support from the CAMEL

Ratings threshold in creating wealth for the shareholders. Moving on, is the output for the

Anova which shows to be at 0.1622; that shows a low significance meaning the entire

regression model is spurious i.e. nonsense and cannot be used to determine or make decision

on the argument that ROE for Barclays Bank and Standard Chartered Bank has been

positively influenced or contributed to by capital adequacy, asset quality, management

efficiency and liquidity status of the two firms. Due to this the researcher concluded that it is

46

a weak argument to posit a positive relationship between ROE and the four parameters

mentioned within CAMELS Ratings threshold in the selected banks.

Having said that the regression results for Bank of England combined with Royal Bank of

Scotland are as shown below.


SUMMARY OUTPUT

Regression Statistics

Multiple R 0.9141

R Square 0.8356

Adjusted R Square 0.7041

Standard Error 1.3298

Observations 10.0000

ANOVA

df SS MS F

Significan

ce F

Regression 4.0000 44.9395 11.2349 6.3533 0.0339

Residual 5.0000 8.8417 1.7683

Total 9.0000 53.7812

Coefficien

ts

Standard

Error t Stat P-value

Lower

95%

Upper

95%

Lower

95.0%

Upper

95.0%

ROE 21.5303 6.4321 3.3473 0.0204 4.9959 38.0646 4.9959 38.0646

Capital Adequacy -440.9473 215.6353 -2.0449 0.0963 -995.2554 113.3607

-

995.2554 113.3607

Asset Quality -8.0888 51.6483 -0.1566 0.8817 -140.8550 124.6774

-

140.8550 124.6774

Management

Efficiency 0.5445 0.3860 1.4105 0.2175 -0.4478 1.5368 -0.4478 1.5368

Liquidity -15.3500 5.4725 -2.8049 0.0378 -29.4175 -1.2824 -29.4175 -1.2824

The results for the Adjusted R Square are at .7041; it means for the government-owned banks

approximately 70.41% of ROE is explained by the trend for capital adequacy, asset quality,

management efficiency and liquidity. This shows a greater effect compared to Barclays Bank

and Standard Chartered Bank on basis of the results for the adjusted R Square. It is also

representative that there is more goodness-of-fit between ROE and capital adequacy, asset

quality, management efficiency and liquidity for government-owned banks compared to

privately-managed banks. Moving on, the Anova results indicate a significance value of

0.0339 which is a reason to take the entire regression model acceptable towards making

decisions on the issues in question. Better still; the model supports the model that ROE for

government-controlled banks in the UK can be attributed to trends in the parameters within

47

CAMELS Ratings. However, looking at each of the p-values for the regression only liquidity

(β = -15.3500, P-Value = .0378) shows to have significant influence to ROE but capital

adequacy (β = -440.95, P-Value = .0963), management efficiency (β = .5445, P-Value =

.2175) and asset quality (β = -8.0888, P-Value = .8817) do not because their significance

levels exceed the 5% margin of error required to rejected the null hypothesis: in this case, that

ROE has been positively influenced by the latter four financial parameters as envisioned in

the CAMELS Ratings.

4.3.3 Predicting Corporate Failure using Altman Score

As indicated earlier, the current dissertation intended to evaluate the degree of corporate

failure for the selected banks using Altman Score model. The Altman Z-score serves as a test

for credit–strength that can be used to check for the potential for bankruptcy. In

implementing the Altman Z score the main financial data and analysis based on the bank’s

annual reports. For instance, financial ratios such as liquidity, profitability, leverage, activity

and solvency were used in predicting the extent of probability of any of the institutions been

solvent. In other words, whether private-banks have high likelihood to be insolvent compared

to those that are directly government-controlled. It is worth stating that prediction of

corporate failure was applied on financial period 2016; the results are as shown below.

Exhibit 4.17: Altman Score Analysis and Implementation

Parameters Bank of

England

Royal Bank of

Scotland

Barclays

Bank

Standard

Chartered Bank

Working Capital 4,590 54717 49208 35,104

Total Assets 405,758 74413 1213126 646,692

Retained Earnings 3,011 7,995 30,531 48,658

EBIT 233,000 2214 3,230 409

Market Value of Equity 4,590 54,717 71,365 48,658

Total Liabilities 401,168 19696 1141761 598,034

Sales 626,000 14,606 14,541 13,010

Current Assets 405,758 74413 1125677 632,173

Current Liabilities 401,168 19696 1076469 597,069

Bank of

England

Royal Bank of

Scotland

Barclays

Bank

Standard

Chartered Bank

Constant Z

Score

Return to Assets 0.5742 0.0298 0.0027 0.0006 3.3

Sales to Total Assets 1.5428 0.1963 0.0120 0.0201 1

Equity to Debt 0.0114 2.7781 0.0625 0.0814 0.6

Working Capital to

Total Assets

0.0113 0.7353 0.0406 0.0543 1.2

Retained Earnings to

Total Assets

0.0074 0.1074 0.0252 0.0752 1.4

Altman Scores 3.4686 2.9941 0.1422 0.2415

48

The Altman scores indicate differences in the case for government-led banks and private-

managed banks. For instance, the Bank of England has an Altman score of 3.4686 compared

to the Royal Bank of Scotland at 2.9941. The two scores exceed the threshold for > 2.99

meaning they are financially sound and they do not cause panic for bankruptcy in the future.

However, both the Barclays Bank and Standard Chartered Bank indicate to have the Altman

Scores below 1.81 threshold. For instance, the former approximates at .1422 and the latter

.2415 which means they risk bankruptcy in the future. Generally, the comparative judgment

is that government-owned banks depict no fears for corporate failure while those with

minimal government influence risk bankruptcy.

49

5.0 CHAPTER FIVE: CONCLUSION, IMPLICATIONS, RECOMMENDATIONS

In the dissertation, the findings so far depict varying trends in the case of private-managed

banks in this case Barclays Bank and Standard Chartered Bank and government-led banks

which included Royal Bank of Scotland and Bank of England. From a far it has been evident

that at some point government-led banks have had a better performance and private-managed

banks exhibiting weak financial performance. On the other hand, government-led banks

depicting low potential for going bankruptcy whilst private-led banks showing high degree of

bankruptcy.

In the introduction part of the dissertation, the purpose was to develop a critical assessment of

the financial performance of government-owned and privately-owned banks in the United

Kingdom relying on CAMELS Ratings and Altman Score. The understanding of the category

of banks was provided for in the definition part of the dissertation so as to eliminate possible

misunderstanding the reader would have over what constituted a private bank and a

government-owned bank. That been the case, the private banks picked from the many of them

were the Standard Chartered Bank and Barclays Bank. On the other hand, the government-

owned banks selected from a number were Bank of England and Royal Bank of Scotland.

The key objectives sought in the research included:







iii. To recommend strategic paths for both privately-owned banks and

government-owned banks in the United Kingdom towards future

financial sustainability

In a successful manner, the researcher managed to address each of the objectives using

appropriate models and demonstrated how the selected banks scored. In the process of

implementing the models the variables were split into dependent and independent so as to

demonstrate fully the stature of the financial performances of selected banks in terms of

capital adequacy, liquidity, asset quality and management efficiency where these were the

main parameters used to effect the CAMELS Ratings. From the findings it was established

that for Barclays Bank capital adequacy has been positive upwards which was constructed to

50

mean that the management had not had difficulties raising capital to cater for the emerging

needs.

On the contrary, sharp drops were evident in Barclays Bank in terms of asset quality,

management efficiency and liquidity. Therefore, the conclusion is that for the bank the

management has been struggling in effectively utilising its assets, optimising its retained

earnings and capacity to offset current liabilities using available current assets. For that

reason, the researcher concluded that Barclays Bank as a sample representative of private-

owned banks in the United Kingdom does not show positive performance basing on key

CAMELS Ratings. However, only capital adequacy did show that Barclays Bank still

financially sound but in the respect to effective use of its capital generated.

In the case of Standard Chartered Bank, the trend for capital adequacy showed drops and

rises leading to the conclusion that the firm has been focused on making optimal use of the

capital available. In other words, the bank has managed to maintain a solid capital base

especially in the period 2014-2015. A good performance was seen to happen in the case of

asset quality for Standard Chartered Bank given the growth in the period 2013-2016; this can

be termed as an indication of the management’s capacity to make good use of the assets

available in the company. However, the indications were that for Standard Chartered Bank

the capacity for the management to effectively utilise retained earnings has been weak; in the

same respect, the ability to make good use of the short-term assets to cater for short-term

obligations equally depicted to have been decreasing or rather weakening overtime.

From the CAMELS Ratings analysis, the researcher observed that Barclays Bank and

Standard Chartered Bank have had financial challenges that need to be looked into to

safeguard the interests of shareholders. In fact, moving to further analysis and developments

the government-managed banks also indicated to have weak performance in various aspects

of financial performances as envisaged in CAMELS Ratings. For instance, the Bank of

England showed positive performance for its capital adequacy given the rise from 2014-2016.

But then all other aspects of financial performance such as management efficiency, liquidity

and asset quality all seemed to drop being an indication for positive performance. In the same

respect, despite the rises in RBS financial performance, the trends depict weak outputs

towards 2016 for capital adequacy, asset quality, management efficiency and liquidity. Due

to this, a conclusion ran that even the government-led selected banks in the United Kingdom

have experienced weak financial performance just as private-managed banks. For that reason,

51

paving way for equal appraisal for strategic decisions that banks across the board should

embrace to keep the revenues rising among other key performance indicators.

In connection to the findings above the analysis carried out in the present dissertation

indicated that it was not feasible to justify the contributions of capital adequacy, asset quality,

management efficiency, and liquidity towards return on equity (ROE) in the case of selected

private banks combined. Therefore, basing on the regression model undertaken in exhibit

4.15 the researcher could not justify the feasibility of a relationship between ROE and the

four financial parameters envisioned in CAMELS Ratings for Standard Chartered Bank and

Barclays Bank. This is a wakeup call to the management of the two banks to reflect in-depth

how they can enhance the capital base, increase cash flows or generally current assets and

effectively utilise the assets and retained earnings. This could be initiated through cost-

cutting measures so as to enjoy better margins. Moreover, the management for the selected

private-banks can renew its credit and lending policies so as to go for collateralised loans

because the enterprises could be losing due to defaulted loan repayments from customers. In

other words, the private-banks may consider creating more revenue streams through service

innovation and product innovation.

Contrary to the case of private banks, the assessment carried out on the Bank of England and

Royal Bank of Scotland indicated that ROE for the latter two have positively been influenced

by capital adequacy, liquidity, management efficiency, and asset quality. It means, the two

banks have been in a position to boost its profitability path for ROE supported by the four

financial indicators envisioned under CAMELS Ratings. It is due to this reason the researcher

rated financial performance of government-led banks to have a better financial performance

when compared to private-led banks. In fact, this can be supported by Altman Scores which

indicated that Barclays Bank and Standard Chartered Bank have a high risk of going bankrupt

compared to Royal Bank of Scotland and Bank of England. In that regard, private banks in

the United Kingdom require more financial stability to avoid future collapse. The

management for private banks need to be further conscious of the ongoing utilisation of

capital, retained earnings and assets so to directly contribute to the profitability of the

enterprises.

5.1 Recommendations

The strategic recommendations are as follows:

1) Private-banks and Government-led banks in the United Kingdom to focus on

increasing their revenue streams to boost income; probably, make interest income just

52

40% of the entire income and other revenue to derive from other investing activities.

In that case, defaulting from loan repayments would not have significant effects on

the income since it would be boosted by other sources.

2) The private banks and Government-led banks in the United Kingdom to monitor their

business environment externally. The effects of BREXIT, for instance, need to be

deliberated upon by the board of all banks and other external business issues; this way

enable the management of banks to keep proper evaluation and controls that will

ensure they keep eye on the financial performances

5.2 Limitations

However, the project suffered a number of limitations as follows:

i. The selection of four banks was a small sample to have made conclusive and

objective judgment about financial of banks in the United Kingdom. Thus, it would

have been much sound to have relied on a large sample. But, a large sample would

have required more data collection and analysis rendering the entire research

cumbersome.

ii. The data was extracted from annual reports as audited for the respective banks.

However, not all data was clear especially for the two selected government-led banks.

In that case, due to inconsistent financial data, the analysis developed so far may have

suffered a few errors of the actual position in the banks. This may have weakened the

reliability and validity of the findings in this dissertation.

53

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