Impact of Performing Loans on Profitability of Banks in UK

This study analyzes the impact of performing loans and financial indicators on profitability of banks in UK. It identifies the financial variables affecting profitability of UK banking industry and studies the impact of loans on banking sector profitability in UK.

The IMPACT OF
PERFORMING LOANS ON
the PROFITABILITY OF
BANKS

ABSTRACT
The banks have a commercial role to play in form of lending to important businesses and thus
has a wide number of operations attached to it. In the operations, there are a number of variables
such as loan to assets, bank size to assets, capital adequacy measured by assets, performing loans
affecting profitability of banks which again measured by return on assets and return on equity
come in to play. The significance of these variables are important for the business as well as its
investors. They are one of the important financial determiners of the financial position of the
company. Banks having these variables in check perform well in operations and contribute
economically to the country’s economic scenario. The study revealed findings of these variables
in which some variables were found to be positive as well as some negative in relation to profits
and total deposits of organisations. The scenario was based on banks of UK where there was also
seen corelation between the variables. There were variables found which were independent and
influencing the profits of the organisation in a major way such as loans. The revenue sources can
be termed as performing loans which increase the bank’s profitability and thus is an important
variable for progression of organisation. There were factors like capital adequacy which were
regulatory measures for liquidity but affecting profitability in a negative way which was
highlighted.
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TABLE OF CONTENTS
ABSTRACT.....................................................................................................................................2
TABLE OF CONTENTS.................................................................................................................3
CHAPTER 1: INTRODUCTION....................................................................................................4
Background of study....................................................................................................................4
Aims and objectives.....................................................................................................................5
Research questions.......................................................................................................................5
Dissertation Structure...................................................................................................................5
CHAPTER 2: LITERATURE REVIEW.........................................................................................8
Theme 1: The financial variables affecting profitability of UK banking industry......................8
Theme 2: The effect of financial variables on banking industry of UK......................................9
Theme 3: The impact of loans on banking sector profitability in UK.......................................10
CHAPTER 3: RESEARCH METHODOLOGY...........................................................................14
Research type.............................................................................................................................14
Research approach.....................................................................................................................14
Data collection...........................................................................................................................14
Sample........................................................................................................................................14
Data Analysis.............................................................................................................................15
Reliability and validity...............................................................................................................15
Research limitation....................................................................................................................15
CHAPTER 4: DATA ANALYSIS................................................................................................18
Theme 1: Bank capital to assets ratio........................................................................................18
Theme 2: Capital Adequacy ratio..............................................................................................20
Theme 3: Statistics excluding outliers.......................................................................................22
Theme 4: Regression analysis....................................................................................................23
Theme 5: Multicollinearity........................................................................................................24
CHAPTER 5: CONCLUSION......................................................................................................27
CHAPTER 6: RECOMMENDATIONS........................................................................................28
REFERENCES..............................................................................................................................29
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CHAPTER 1: INTRODUCTION
Background of study
The aim of this assignment is to study the impact of performable loans and financial
indicators on profitability of banks in UK. The banks play a vital role in economy of a nation,
there are several operations undertaken by banks like savings being kept as deposits, giving
interest on the savings to customers and perform operations of lending for businesses to grow.
Loans form a vital part in a bank’s business as this is the chief revenue source for banks in UK
(Sungheetha and Sharma, 2020). The UK banking system does not have high interest rates on
savings accounts but are ahead in loan performance. The banking sector stability is necessary for
growth of a nation’s economy. There are parameters which indicate the financial performance of
the bank and are judged through various parameters like solvency, profitability and liquidity. UK
banking sector has a number of banks working in private sector, international banks and
government banks. UK currently has 344 banks working and with physical banking, there has
been a steady growth in online and mobile banking too (Arkes, 2019). The Regulatory body of
banking in UK is Financial Conduct Authority and country has a central bank which is Bank of
England and is state owned. The services provided here are of current accounts, savings
accounts, overdrafts and loans, mortgages and insurance. Apart from these, banking sector also
provides mobile banking and business banking through digital measures.
It has been pointed out by experts that banks act as intermediaries facilitating economic
growth and improvement in financial stability. UK banks in previous decades have acted as a
channel for economic growth and emphasised on measures of financial inclusion in which the
villages have been included. Through this exercise, financial parameters have been kept in
consideration to maintain a check on profitability such ass return on investment and equity.
Talking of the UK banking sector, it is one of the most prominent in Europe, which accounts for
about a quarter of the banking assets with the Europe. From the statistical report of Bank of
England, assets in total amounted to above GBP 5 trillion at 2014 end. The UK banking sector is
one of the biggest banking centre internationally accounting for around 20 percent of the cross
border lending of the world. The nation has one of the important finance centres which has
increase of foreign banks presence. This can be gauged from the presence of 150 deposit taking
subsidiaries of foreign in UK which are from 56 different nations. Foreign banks account for
more than 55 percent of UK assets of banking sector.
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Despite the proliferation in banking services, lending in business has been an important
component of banks’ activities and other institutions of depository. It has been found in studies
that in around every European country, loans to firms and households account for around 55 %
of total bank assets with other earning assets which accounted for the rest.
The UK banking sector has been experiencing good growth substantially recently, with
witness to rapid expansion in assets. In the literature review provided there have been facts
investigating about the bank profitability determinants for UK. A number of variables such as
loan to assets, capital adequacy, performing loans and market concentration have been
considered in this regard and facts about them influencing profitability of UK banking sector
discussed. The difference between performing and non-performing loan is simple that in
performing loan borrower pays its debt payment on time while in non-performing borrower can't.
If any assets of the bank remain due up to 90 days than it is considered as performing assets and
loan while if any assets of the bank remain due even after the 90 days than it is considered as
non-performing assets and loan.
Aims and objectives
Aim:
 To study the impact of performable loans and financial indicators on profitability of
banks in UK.
Objectives:
 To identify the financial variables affecting profitability of UK banking industry.
 To analyse the effect of financial variables on banking industry of UK.
 To study the impact of loans on banking sector profitability in UK.
Research questions
The research seeks to find answers to these following questions:
Q.1. How have the financial variables affected performance and profitability of banks?
Dissertation Structure
Chapter 1: Introduction
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In this section of the dissertation and thesis, scholar will select the research topic and
determine the aims and objectives of the research along with the research question. This section
will also describe the background of the study on topic of impact of performing loans on
profitability of UK banks.
Chapter 2: Literature Review
This section of thesis will cover the secondary research on the research topic where
various authors views and opinions are considered. In this, various theme related to research
objectives are prepared in order to achieve the same.
Chapter 3: Research methodology
In this section, the methods will be present and select with the help of which scholar will
do research. This includes selection of research type, approach, data collection method,
sampling, data analysis, reliability and validity and research limitations.
Chapter 4: Data analysis
The data analysis section of the dissertation will cover the various tables and graphs
which describe the variables of performing and non-performing loans along with their impact on
UK banking sector. The analysis will be done using the thematic analysis method of qualitative
research in which scholar will prepare various themes, ratios formula, tables and graphs.
Chapter 5: Conclusion
The conclusion part of the thesis will conclude the key facts and points cover in this
whole research. This section will conclude what factors and results that scholar has identified
while conducting whole research.
Chapter 6: Recommendation
This is the last chapter of thesis where proper recommendation is provided to the readers
that they need to adopt. This section is basically present in the bullet points so that readers can
understand the part quickly and easily. The section covers the banking rules and regulation
which is recommended to the UK bank to deals with financial crises.
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CHAPTER 2: LITERATURE REVIEW
Literature review (LR) is one of the most important section of the whole dissertation and
thesis which state views and opinion of the different authors on the specific research topic. The
aims of this chapter in this dissertation is to achieve the research objectives in the best
manner possible. In this section various authors views which may be in favour and against the
research topic such as impact of performing loans on profitability of banks. This part will
basically analyse the existing research using journal articles, high-quality industry publication
books etc. with a view of understanding research objectives.
Theme 1: The financial variables affecting profitability of UK banking industry
As per Nuhiu, Hoti and Bektashi, (2017), banks make profits by earning money more
than what they pay in expenses. Bank’s major portion of profit comes from the fees being
charged on services and interest being earned from assets. Author Le and Ngo (2020) say that
many factors like liquidity, operational expenses and commercial banks on the performance
which gets measured by return on assets and return on equity. According to study, the findings
were that return on assets and return on equity had an impact on the profitability of banks. Loan
to deposit ratio or loan to assets is used for assessing liquidity of bank by comparison of total
loans to the total deposits of the same period. It is expressed in percentage form and if the ratio is
high, meaning the bank may not possess sufficient liquidity for covering fund requirements
which are not seen before. The ratio being low shall mean that bank may not have enough
earnings as it can be.
However, on the other side, Author Altavilla, Boucinha and Peydró (2018), credit risk
has been a factor where the banks need to work. There has been a rise in non-performing loans
effect on banks’ profitability in UK. With the financial crisis in past decade, an upsurge of non-
performing loans was seen and this became a major concern affecting banks’ profitability. The
literature reviews the effect of both performing and non-performing loans as an effect on
profitability of the banks.
Loan to deposit ratio for UK banks has been said to be 80 to 90%. Loan to deposit ratio, as per
author, if it is 100% shall mean bank giving loan to customers for every dollar received in
deposits. The ratio reflects of the ability of bank for covering losses of loans and withdrawal of
customers. If deposits of bank show increase, new clients are brought on-board. The loan to
assets lets investors be sure that there is enough liquidity for covering loans in view of economic
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downturn which may result in default of loans. The loan to assets also is a variable which
indicates how well bank attracts and retains customers.
Theme 2: The effect of financial variables on banking industry of UK
Increase in assets, according to Nuhiu, Hoti and Bektashi, (2017), will mean banks will
have more money to lend. Loans are regarded as an asset to the banks as it gives interest income.
As Le and Ngo (2020) highlights, the bank’s proper management is done by loan to assets. If
bank is not having an increase in deposits and deposits shrink, bank will have less of money for
lending. The loan-to-assets ratio gives a risk measure since loans are risky and have a higher
return expected than other assets of bank, like securities of government. Thus, one may expect a
relationship that is positive between the performance measure and the variable. It may be the
case, although, with banks that are increasing quickly their book of loan having to pay a high
cost for their requirements of funding and this can reduce the impact being positive on
profitability.
In banking productivity and output are difficult for estimation due to problems in
definition, joint products and issues which a bank service provides in actual. For avoiding this
problem, researchers who took interest in banking industry performance have looked at
profitability often. Accounting data used also has made appeal. Market data is available mainly
for the biggest firms in industry, so they are more limited in accounting data. Also, regulators
relied heavily on figures of accounting in evaluation of the financial condition of the firm. The
UK banks’ earnings quality shall be examined through use of return on assets. Also, the results
have been based on using the return for ROE. The review suggests that bank profitability is
determined by factors which are internal and external to the bank. The measures of performance
not being risk adjusted shall make use of variables for indicating impact on profitability of banks.
In contrast to above statement, Le and Ngo (2020), state that capital adequacy refers to
the bank’s ratio of capital in relation to the risk-weighted assets and current liabilities. Capital
adequacy is decided by central bank and banking regulatory body of UK for preventing the
commercial banks from taking of excess leverage which can also make them go insolvent. The
commercial banks have to maintain a level of capital which is adequate for absorbing the risk
and providing return to the investors which is reasonable. The bank’s ability in this aspect is
measured in terms of capital adequacy ratio prescribed by central bank. Central Bank’s main
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objective of UK is to maintain the requirements of capital adequacy to ensure the capital required
for withstanding of the risk. The Central Bank of UK requires the banks to maintain a ratio of
21.6% (Nuhiu, Hoti and Bektashi, 2017) and these are in accordance with the regulatory
guidelines also. The prominent components in calculating capital adequacy ratio is retained
earnings and reserves. The net interest income being the important aspect of the banks’ revenue
segment, it helps in determining the profitability level.
As per Altavilla, Boucinha and Peydró (2018), performing loans are the ones which
have been made payments by borrowers and thus have a positive effect on profitability of banks.
In UK, there is a ratio of performing and non-performing loans where non-performing loans. The
non-performing loans ratio stood at 1.1% in December 2018 in comparison of 0.7%.
The bank market share variables and the concentration ratio are calculated on the base of
of the national markets’ size, i.e. total assets of banking sector. However, the Xu, Hu and Das
(2019), state that the Firm-specific market share (MSH), is said as the assets of bank divided by
assets’ total value of all banks in the nation and in Bankscope of Fitch. These measures were
utilised for capturing both the efficient hypothesis and the traditional concentration-performance
relationship.
Bank size measured by the assets is one of the bank prosperity measures. Total assets are
measured by the assets owned by bank. The inclusion is not limited to balances and cash,
advances and loans to the banks as well as securities of debt.
Theme 3: The impact of loans on banking sector profitability in UK
Assets can be of nature of real estate, cash, bonds, marketable securities etc. Bank size
growth in assets will be increase in capital for the bank. As of UK, in the end of 2019, HSBC
total assets valued to around two trillion British pounds with bank headquarter in London as the
leading bank in rank. The Royal Bank of Scotland has value of around 723 billion British pounds
which has secured the fourth position in the ranking of largest banks by assets value.
Measure employed for determining bank size is market capitalising and it has been found that
HSBC is the largest bank in market capitalisation terms trading on London Stock Exchange and
in Europe. Bank assets increase is thus an important financial variable or indicator for it.
As stated by Le and Ngo, (2020), return on assets indicates how profitable company is relative to
total assets. It indicates how well company uses its assets in terms of profitability. It is said that
ROA is very useful for comparison of companies of the same industry. For example,
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Return on assets for service oriented firms like banks can be higher significantly than ROA for
organisations which are capital-intensive like utility companies and construction. It basically tells
about earnings that were generated from capital invested. The Return on assets may substantially
vary and dependent highly on industry. On using ROA as a comparative measure, it will be
better for comparison of Return on assets against previous numbers of the organisation. ROA
gives an idea of the company’s effectiveness in money conversion which is invested in net
income. Higher the number of ROA, it is better as organisation earns money more on less of
investment. It has been felt that the formula for ROA is most suitable to banking organisations.
The balance sheets of bank represent the real value of assets and liabilities as they are carried at
market value.
Return on Equity measures financial performance being calculated by net income being
divided by equity of shareholders. As shareholder’s equity is got by assets of company minus the
debt Return on Equity is considered return on net assets. Return on Equity is deemed bad or
good on comparing to what is normal along the stock peers. Normal ROE in utility sector can be
10% or less. On the other side Xu, Hu and Das (2019), the investors refer analysis of ROE with
sustainable growth rate model. Investors can utilise the model for making future estimates for
stock identification that may pose risk as of going ahead of growth ability that is sustainable. The
growth rate that is far above or below the sustainable rate requires investigation that is additional.
The equity-to-assets ratio (EA) can be said to be a measure of the capital strength overall.
The ratio is a measurement of capital adequacy, and captures the safety and soundness in general
of the financial institutions. A decline of this ratio indicate an increase either in financing of debt
banks‟ total assets (while holding total assets constant), or a decrease in banks‟ total assets
(while holding total equity constant), or both over space and time. Irrespective of that, this is an
increase in risk of banks, and also, in cost-to-capital of banks. The capital structure theory states
that a high use of debt (equity) financing in a range, called the target capital structure, may
reduce in actual (increase) cost of capital of firms. Thus, a positive (negative) coefficient
estimate for equity-to-assets indicates an efficient (inefficient) management of banks‟ capital
structure.
Hypothesis:
Previous studies have looked into the relationship between credit risk management and
commercial bank profitability in Europe. As a result, it becomes a topic worth researching. We'll
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do our research using the information we've gathered from the annual reports of UK's top banks,
from 2007 to 2012. All of the signs that have been discussed in earlier chapters have been
explained. Credit risk management and commercial bank profitability were chosen to be
presented. As a result, the following hypotheses have emerged:
Hypothesis 1: The null hypothesis is that there is no relationship between CAR, NPLR, and
commercial bank ROE.
Alternative hypothesis: There is a link between CAR, NPLR, and the return on investment (ROI)
of banks that deal with commerce.
CAR and NPLR are credit risk management indicators, as previously indicated (J Arkes, 2019).
One of the metrics of profitability is return on investment (ROI). This hypothesis is used to
determine whether or not there is a link between commercial bank ROE, CAR, and NPLR.
2nd Hypothesis: 50
The null hypothesis is that there is no link between CAR, NPLR, and ROA of banks that deal
with commerce.
Alternative hypothesis: There is a link between CAR, NPLR, and the return on investment (ROI)
of banks that deal with commerce.
The hypothesis is written in the same way as hypothesis 1, but it uses ROA as the variable.
Another indicator of profitability is the independent variable.
Hypothesis 3
Null hypothesis: The relationship between CAR, NPLR, and ROE remains stable throughout
time.
Alternative hypothesis: CAR, NPLR, and ROE have a positive association changing throughout
time (Daoud, J.I., 2017).
This hypothesis is used to see if the link between CAR and ROE is stable regarding the
relationship between NPLR and ROE.
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Hypothesis 4
Null hypothesis: The relationship between CAR, NPLR, and ROA remains unchanged
throughout time.
Alternative hypothesis: CAR, NPLR, and ROA have a positive association changing throughout
time.
The purpose of this hypothesis is to see if the link between ROA and CAR is stable regarding the
relationship between ROA and NPLR (Daoud, 2017).
Summary
This chapter has been followed the aims and objectives of the research and for this the
refrences from the introduction chapter was taken. This section finds and analysis the views of
the different author on the variable of performing and non-performing loans. The section
provides a clear insight about the various ratios which further helpful for the achievement of the
research objectives. This section also present the various hypothesis created in order to identify
the relation between the variables.
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CHAPTER 3: RESEARCH METHODOLOGY
Research Methodology (RM) is basically state the methods that scholars will use to do
research on topic such as impact of performing loan on profitability of banks. In this section, the
selection of research type, approach will be take place along with the source of data collection.
This is important part of whole thesis because it will help the readers to evaluate the reliability
and validity of the research. The analysis of data will also discussed in this chapter to achieve the
aims and objectives of the thesis. The aim of this section is to identify the methods that will
be used to conduct the research along with inclusion of reliability and validity and research
limitations.
Research type
The approaches for research are qualitative as well as quantitative. In the research,
qualitative types of research has been used for gaining information about the topic.
Research approach
This states about different approach which research uses in order for collection of
analysis and interpreting information which is necessary. Inductive and deductive approaches are
the ones used for research analysis and evaluating information. Inductive approach has been used
here for interpretation and for data analysis and information (Nuhiu, Hoti and Bektashi, 2017).
Data collection
It specifies methods used by scholar for gathering relevant and sufficient information. In
the research, primary and secondary method of research has been used for gathering information
through journals. The study about financial variables has been collected from authenticated
journals covering data of UK commercial banks. The empirical data has been collected of two
types- of dependent and independent variables. The dependent variables have been classified as
Return on Equity and Return on Assets (Xu, Hu and Das, 2019). The independent variables are
the factors affecting bank profitability like bank size, loan to assets etc.
Sample
For research purpose, commercial banks of UK like HSBC, Barclays, Royal Bank of
Scotland, Standard Chartered Bank. These form the list of top UK banks and data required from
selected variables has been taken from financial statements of the banks.
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Data Analysis
This explains how data has been interpreted so individuals studying the research can
understand easily about the same. Thematic and SPSS are two different methods which are used
for data analysis concerning to various studies. The researcher has used thematic analysis of
information through graphs and table usage for presenting relevant information about data.
Reliability and validity
The sources used are reliable and valid by researcher for collecting information from
different journals and books. In addition to this, scholar made sure that information is gathered
from articles which have been published recently so that they are reliable for users.
Research limitation
The limitation for research is limited time frame and resources for completing the study.
The scholar has although made use of available time and resources for gathering right
information to be communicated. Limited resources being present, the researcher will try
extracting more information from different source for making research fruitful.
Model
The study relates financial variables to impact of them on profitability of banks. For the purpose,
it will be required to find the relation between credit and indicators of profitability and regression
model shall be used to find the dependent and independent factors. A regression linear model is
outlined in equation 1 where dependent variables are indicated by ‘Y’ and ‘X’ are factors
independent. ‘C’ shows the coefficient. Y=c+ f(x).
Apart from regression analysis, descriptive analysis and correlation analysis are performed also.
The descriptive analysis gives the calculation of basic statistical formulas of central tendencies
such as mean, median, mode and standard deviations. The central tendencies reflect the average
of particular variables while standard deviation indicate the data variability or the standard error
(Bouzgarrou, Jouida and Louhichi, 2018).
The link between credit risk and profitability indicator may be found through correlation
analysis. The correlation analysis is utilised for finding the association of indicator of
profitability. The formula for coefficient of correlation is popular for finding correlations.
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It has assumption that results have to remain in range of -1 to +1. Results near to +1 depict
strong correlation and linkage between variables and results closer to -1 show weak relationship.
If the result is zero, then it depicts that the two variables do not have any relation at all
(Bouzgarrou, Jouida and Louhichi, 2018).
The model of regression consists of profitability measures ROA and ROE depending on five
types of indicators of credit risk which are CRIMP- Credit Risk because of impairments,
CRNPL- Credit risk because of non-performing loans, BS- bank size, GR- Growth and LV-
leverage. Independent variables have been entered in regression equations as follows:
Return on Assets (ROAi,t) =c0 +αCRIMP i,t+ βCRNPL i,t+ χBS i,t+ δGR i,t+ LVi,t+ εi,t
Return on Equity (ROEi,t) =c0 +αCRIMP i,t+ βCRNPL i,t+ χBS i,t+ GR i,t+ γLVi,t+ εi,t
In this formula, the dependent variables is ROA i.e., return on assets and ROE i.e., return
on equity. While on the other hand, independent variable is bank size.
Regression models depict the percentage variability of variables that are independent. ‘R square’
shows the relation between independent and dependent variables where R represents square root
of R. The value of R shows independent variables which are in association with ROA and ROE.
Likewise, “adjusted R square” shows the independent variables with dependent in order to
validate decisions on regression model.
Model R R Square Adjusted R
Square
Standard error of
estimate
1 0.530 0.281 0.192 4.01
2 0.391 0.154 0.048 16.801
Dependent
variables
Measure Formula Impact (+/-)
1. ROA Net income/Total
assets
2 ROE Net income/
Shareholder
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equity
Independent
variables
Bank size Total assets +
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CHAPTER 4: DATA ANALYSIS
Data analysis is a process of inspecting, cleansing, transforming and modelling data related to
research objectives with the goal of discovering information and supporting decision-making. As
in the present dissertation, qualitative type of research is selected along with the thematic data
analysis method. This section represents the analysis of data in literature review form where all
the specified research questions will be answered with the use of formula, tables and charts. The
aim of data analysis section of thesis is to present the data which is collected earlier in
simpler ways which spread awareness and motivations.
This is a part of research methodology which states the way scholar will analyse the
information gathered from sources which are different so that facts which are useful can be
summed up in limited timeframe and cost. Researcher make utilisation of different tools of
analytics in order to analyse and interpret data for taking right decision by people interested at
right time. The approaches basically used for analysis of data is thematic. In thematic,
researchers use the theme of graph, table and pie chart for representing the drive information so
that stakeholder or interest individuals of study may easily know the efforts (Sungheetha and
Sharma, 2020). On the note contrary, SPSS is a software which is used mainly in quantitative
study or study of complex statistical which is not an approach to data analysis. Therefore it can
be stated that SPSS software package is mainly created for management and statistical analysis
related to social science data. So out of the both of the above data analysis method the researcher
has make use of Thematic analysis as it used in qualitative analysis and helps in in-depth and
better representation of information in form of graphs and charts.
Theme 1: Bank capital to assets ratio
It is the ratio of bank capital and reserve to total assets. Reserve and Capital have inclusion of
funds contribution by owners, earnings retained, special and general reserves, valuation
adjustment and provisions. The capital has inclusion of tier 1 capital that is a common factor in
UK banking systems and regulatory capital, including type of debt instruments which does not
need to be paid again if there is a requirement of funds for maintaining capital levels. Total assets
have inclusion of financial and non-financial assets. Following is ratio of bank to assets as
follows of UK banks:
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Table:1 Capital to assets ratio from year 2008 to 2018
Year Ratio
2008 5.5
2009 3.5
2010 5.3
2011 5.3
2012 5.1
2013 5.5
2014 6.3
2015 5.6
2016 6.8
2017 7
2018 6.8
Graphical Presentation of capital to asset ratio from year 2008 to 2018
Interpretation: It can be seen that in 2008, the ratio was 5.5, declined in 2009 and again went up
the next year. The ratio got above 6 of bank to assets in 2014 and was recorded below 6 the
following year. Ratio touched highest with 7 in 2017 and in 2018 it was reported to be 6.81%
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according to World Bank collection of UK banks. Bank to assets ratio of around 8 % is
considered to be good ratio.
Theme 2: Capital Adequacy ratio
Capital ratio show capital of bank as a percent of risk-weighted assets. The requirements for UK
banks were raised after Basel III accord and phased in month of Jan 2015, with a requirement of
CET1 ratio of 4.5 percent. UK largest banks have been in continuation of meeting minimum
requirement till fourth quarter of 2019.
Table:2 Capital Adequacy Ratio of UK Banks
Bank name Percentage of CET1 ratio
Royal Bank of Scotland 16.22%
HSBC Holdings 14.6%
Standard Chartered Plc 13.68%
Barclays Plc 13.45%
Lloyds Banking Group Plc 13.3%
Graphical Presentation of capital adequacy ratio of UK banks
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Interpretation: Through the graph, it can be seen that Royal Bank of Scotland has topped the
chart with 16.22% in capital adequacy followed by HSBC at 14.6%. Lloyds Banking is the last
one with 13.3%.
According to the Brook and Arnold (2018) research, a bank's profitability is influenced
by elements such as management, size, location, and time. The author also came to the
conclusion that both internal and external determinants have an impact on a bank's profitability.
The research focuses on credit risk through non-performing loans, which is one of the internal
determinants of commercial bank profitability. We need to incorporate a control variable to rule
out the chance that the association is attributable to other causes. We chose the size of the bank
as our control variable, following the Montgomery, Peck and Vining, (2021) methodology. Firm
size has been studied in the past. It has been measured on a variety of grounds, and it is claimed
that it does.
Firm size has been measured on a variety of grounds in prior studies, and it is believed
that it makes no difference which measure of firm size is utilised. One typical metric that has
been found to be the most effective is the natural log of total asset is a measure of business size
that can be used interchangeably.
To provide a quick overview of our findings, we've included the descriptive statistics for our
variables (CAR, NPLR, LNTA, ROA, and ROE) for commercial banks in the United Kingdom
from 2007 to 2012. According to the histogram of we assume that all variables follow a normal
distribution.
There are four ratios among the variables in Table . The profitability of banks is
measured by ROA and ROE, while credit risk management is represented by CAR, that is
Capital Adequacy Ratio and NPLR, that is non-performing loan rate. After removing the outliers,
the total number of observations for each variable is 275. From the indicator with the largest
spread is ROE, which has the highest standard deviation in which 11.35 is the standard deviation.
The standard deviations of the other indices are less than 3.The difference in ROE ratio between
the greatest and lowest values is 112.90. The biggest ratio is 38.4 percent, while the smallest is -
74.5 percent, implying that our study's sample banks have a higher level of diversification in
their ROE ratio.
In order to do the regression analysis, there is need to gather the data related to the
variables of performing loan. Four ratios, including outliers, are summarised in table 3. After
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eliminating the outliers, the average ROE is 6.14, with 4.85 changes while including the outliers.
We also notice that the ROA spread is 5.53 percent, with a maximum observation of 3.58
percent.
A minimum of -1.95 percent observation is required. ROA has a standard deviation of 0.56. The
extreme value in a somewhat pattern affects the %. CAR is valuable. From 34.7 percent to 5.9%,
the percentage has changed. CAR has a mean of 14 percent. Before when outliers are removed,
the CAR mean is nearly identical to 14.06, indicating that outliers have a minor impact on the
CAR indication. The highest NPLR value is 16.11 percent, and the tiniest vasculature
(Montgomery, Peck and Vining, 2021).
Theme 3: Statistics excluding outliers
Table3: Statistical analysis of variable
Variable N Min Max Mean Std deviation
CAR 275 5.90 34.70 14 3.66
NPLR 275 0 16.11 2.79 2.40
LNTA 275 3.82 7.78 6.07 0.91
ROA 275 -1.95 3.58 0.25 0.56
ROE 275 -74.50 38.40 6.14 11.35
Interpretation: The above table represent the financial performing ratios of the company which
the help of which it can be analysed that whether it put positive or negative impact over the
performance and profitability of UK Banks. This table represents the number, minimum,
maximum, mean and standard deviation of the five financial ratio.
Table4: Statistics including outliers
Variable N Min Max Mean S.D
CAR% 282 5.9 34.70 14.06 3.76
NPLR% 282 0 16.11 2.83 2.45
LNTA 282 3.82 7.78 6.02 0.91
ROA% 282 -57.84 23.40 0.24 4.07
ROE% 282 -687.29 38.40 1.29 47.90
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Interpretation: The above table represent the same data i.e., number, minimum, maximum mean
and standard deviation of five financial variables but in percentage rather than in ratios. This
table interpret-ate the statistical analysis of the variables.
Result or outcome of Hypothesis
Hypothesis 1 Outcome:
In this the null hypothesis is rejected while on the other hand the alternative hypothesis is
accepted because this shows link between the CAR, NPLR and ROI.
Hypothesis 2 Outcome:
In the second hypothesis, the alternative hypothesis is accepted while null hypothesis is
rejected. It is because the alternative hypothesis indicating the relationship between the variables
such as CAR, NPLR and ROA.
Hypothesis 3 Outcome:
The third hypothesis is about the relation between CAR, NPLR and ROE in which null
hypothesis is accepted while the alternative hypothesis is rejected. It is because the null
hypothesis is showing relation between the variable.
Hypothesis 4 Outcome:
On the basis of fourth hypothesis, the alternative hypothesis is acceptable while the null
is rejected and it is because positive association and link between the CAR, NPLR and ROA.
Theme 4: Regression analysis
There is a need to design regressions to assess the associations between dependent and
independent variables in order to test the hypotheses we made in the previous section. " The
regression analysis evaluates the model's statistical validity. The method we've chosen is
ordinary Least Squares is the method used to construct the model (OLS).
There are seven assumptions to make for OLS estimators to be the best available, according to
author:
 The regression model is linear, well-defined, and has an additive error rate.
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 The population mean of the error term is zero.
 The error term has no correlation with any of the explanatory variables.
 The error term observations are unrelated to one another (no serial correlation).
 The variance of the error term is constant.
 There is no explanatory variable that is a perfect linear function of any other explanatory
variable.
 Different variables (No perfect multicollinearity).
 The error term has a regularly distributed distribution.
R2
We need to look at a metric called R2 when evaluating the overall fit of a regression equation or
the coefficient of determination, as the case may be. R2 is the proportion of the explained to the
unexplained from the total sum of squares to the sum of squares.
Theme 5: Multicollinearity
There is a possibility of multicollinearity because both CAR and NPLR are credit risk
management indicators. When one or more explanatory variables are significantly linearly
connected to one another, this is known as multicollinearity. Perfect Multicollinearity refers to
the fact that one explanatory variable is a perfect linear function of any other variable, additional
explanatory factors, which is relatively straightforward to prevent (Daoud, J.I., 2017).
Multicollinearity with flaws is referred to as "a functional relationship between two or more
independent entities that is linear. Variables that are so powerful that they have a major impact
on the estimation of the variables' coefficients "The variances and standard deviations will be
caused by multicollinearity. Estimation mistakes are expected to rise.
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Explanatory variables that are almost linearly dependent are referred to as multicollinearity.
Tables show that the highest correlation among all variables is -0.3078 (the correlation between
the two variables). NPLR and ROE are two terms that are often used interchangeably.
Researchers, on the other hand, always prefer an absolute value greater than 0.8 to be sufficient
to produce multicollinearity. In light of this, because 0.3078 is so distant from 0.8, we conclude
that multicollinearity is not an issue in one of our variables.
Theme 6: Correlation Matrix for regression(ROE)
CAR NPLR LNTA ROE
CAR 1
NPLR -0.0720 1
LNTA 0.0266 -0.0510 1
ROE -0.0652 -0.3078 -0.0503 1
Correlation matrix for regression(ROA)
CAR NPLR LNTA ROE
CAR 1
NPLR -0.0720 1
LNTA 0.0266 -0.0510 1
ROE -0.0266 -0.2218 -0.1812 1
This section of dissertation include the various ratios and their analysis. The
interpretation of the themes is done to achieve the research question and objectives of the
research. For this, the section consider various variables and measures of performing and non-
performing loans and their impact over the bank performance and profitability. The statistical
tool is being used in this chapter such as mean, standard deviation, minimum, maximum etc.
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26

CHAPTER 5: CONCLUSION
The report gave an insight of research done on financial variables. It covered variables like loan
to assets, capital adequacy and ratios like ROE and ROA to measure profitability impact on UK
banks. Performing and non-performing loans impact was also discussed. Literature review was
done of UK banks and the variables. Research methodology techniques were discussed. Data
analysis was done of variables affecting the banking system and methods of regression analysis
were used. The report did some primary research in data analysis but majorly, was on secondary
research. The performing and non-performing loans can be identified as major influencers on the
UK banking system. The report has also concluded the outcome of the four hypothesis and
identifies whether null hypothesis is accepted or alternative. With this, the report has been able to
achieve the research question and objectives in the best manner possible. Lastly, the report has
also provided the suitable recommendation to UK banks so that they can deal with the non-
performing loan borrowers and able to receive the payment before the due date of 90 days.
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CHAPTER 6: RECOMMENDATIONS
It can be recommended of research that UK banks have seen crisis in recent times and thus there
is requirement to follow the banking rules and regulations to avoid debt piling up of non-
performing assets. The following measures can be taken:
a) The UK banks must maintain a capital adequacy ratio of 8% and it has to be in proportion
with Risk-weighted assets. It shall help in facing liquidity crisis for the banks.
b) The UK banking system should follow the Basel III legal regulatory requirements which
can help in risk management for the banks and thus, help in tightening the credit risk
measures while looking after the operational as well as legal regulatory requirements.
c) The banks should follow a credit measure based on credit ratings of the individual or
organisation they are lending to avoid default of loans. NPAs can thus be controlled.
d) Monetary measures provided by Bank of England should be followed to make profits in a
sustainable manner for the banks.
e) Vigilant measures over loan sanctioning, disbursal and collections can help bank lessen
the Non-performing loans.
f) Banks have to find methods to increase the return on equity and return on assets.
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REFERENCES
Books and Journals
Altavilla, C., Boucinha, M. and Peydró, J.L., 2018. Monetary policy and bank profitability in a
low interest rate environment. Economic Policy, 33(96), pp.531-586.
Arkes, J., 2019. Regression analysis: A practical introduction. Routledge.
Batool, A. and Sahi, A., 2019. Determinants of financial performance of insurance companies of
USA and UK during global financial crisis (2007–2016). International Journal of
Accounting Research, 7(1), pp.1-9.
Bouzgarrou, H., Jouida, S. and Louhichi, W., 2018. Bank profitability during and before the
financial crisis: Domestic versus foreign banks. Research in International Business and
Finance, 44, pp.26-39.
Brook, R.J. and Arnold, G.C., 2018. Applied regression analysis and experimental design. CRC
Press.
Daoud, J.I., 2017, December. Multicollinearity and regression analysis. In Journal of Physics:
Conference Series (Vol. 949, No. 1, p. 012009). IOP Publishing.
Klein, P.O. and Weill, L., 2018. Bank profitability and economic growth.
Kumari, K. and Yadav, S., 2018. Linear regression analysis study. Journal of the practice of
Cardiovascular Sciences, 4(1), p.33.
Le, T.D. and Ngo, T., 2020. The determinants of bank profitability: A cross-country
analysis. Central Bank Review, 20(2), pp.65-73.
Le, T.D. and Ngo, T., 2020. The determinants of bank profitability: A cross-country
analysis. Central Bank Review, 20(2), pp.65-73.
Montgomery, D.C., Peck, E.A. and Vining, G.G., 2021. Introduction to linear regression
analysis. John Wiley & Sons.
Nuhiu, A., Hoti, A. and Bektashi, M., 2017. Determinants of commercial banks profitability
through analysis of financial performance indicators: evidence from Kosovo. Business:
Theory and Practice, 18, pp.160-170.
29

Nuhiu, A., Hoti, A. and Bektashi, M., 2017. Determinants of commercial banks profitability
through analysis of financial performance indicators: evidence from Kosovo. Business:
Theory and Practice, 18, pp.160-170.
Sungheetha, A. and Sharma, R., 2020. A Novel CapsNet based Image Reconstruction and
Regression Analysis. Journal of Innovative Image Processing (JIIP), 2(03), pp.156-164.
Tvaronavičienė, M., Masood, O. and Javaria, K., 2018. Preconditions of the Eurozone economic
security: how to overcome liquidity risk and cost inefficiency in leading banks of UK and
Germany. Polish journal of management studies, 18.
Valaskova, K., Kliestik, T. and Kovacova, M., 2018. Management of financial risks in Slovak
enterprises using regression analysis. Oeconomia Copernicana, 9(1), pp.105-121.
Xu, M.T., Hu, K. and Das, M.U.S., 2019. Bank profitability and financial stability. International
Monetary Fund.
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