Research: COVID-19 Impact on Banking Profitability in Bangladesh
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This research paper, submitted to Jagannath University, investigates the impact of the COVID-19 pandemic on the profitability of the banking sector in Bangladesh. The study employs a comprehensive methodology, including t-tests to compare financial metrics before and after the pandemic, trend analysis to visualize the impact of COVID-19 cases on key financial indicators like ROA and ROE, and regression analysis to determine the relationship between various factors. The research addresses the impact on investment income, operating profit, and net profit, among others. The findings, based on data from the Bangladesh banking sector, are presented to understand the challenges faced by the banking industry during the pandemic, with the aim of evaluating the overall effect of the pandemic on the sector's financial performance. The paper includes an introduction, literature review, detailed methodology, results, and conclusion, offering valuable insights into the resilience and performance of the banking sector during the crisis. The study aims to find out whether Covid-19 has an impact on the banking industry or not.
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A Research
on
The Impact of COVID-19 Pandemic on the Profitability
of Banking Sector: A Study on Bangladesh
SUBMITTED TO
Dr. Shaikh Mashrick Hasan, PhD
Associate Professor
Department of Finance
Jagannath University, Dhaka.
SUBMITTED BY
Group- 01
MBA 1st Semester
11th Batch
Department of Finance
Jagannath University, Dhaka
on
The Impact of COVID-19 Pandemic on the Profitability
of Banking Sector: A Study on Bangladesh
SUBMITTED TO
Dr. Shaikh Mashrick Hasan, PhD
Associate Professor
Department of Finance
Jagannath University, Dhaka.
SUBMITTED BY
Group- 01
MBA 1st Semester
11th Batch
Department of Finance
Jagannath University, Dhaka
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Letter of Transmittal
15 March, 2022
Dr. Shaikh Mashrick Hasan, PhD
Associate Professor
Department of Finance
Jagannath University, Dhaka- 1000.
Subject: Submission of research paper on “The Impact of COVID-19 Pandemic on the
profitability of Banking Sector: A Study on Bangladesh.”
Dear Sir,
It is a great delight for us to submit our research report on “The Impact of COVID-19 Pandemic
on the Profitability of Banking Sector: A Study on Bangladesh.” It was assigned to us for a
partial necessity for the fulfillment of FIN/BNK-5104 course. Throughout the study we have
tried our best to accommodate as much data and relevant information as possible.
We have always tried to consider your remarks and instructions very carefully while preparing
this report. We have tried always to follow your schedule, format and discipline. The whole
experiences of making this report enabled us to know about research processes. We are grateful
to you for providing such an opportunity.
We have tried to give my best effort on making this report informative and comprehensive
enough. Despite that there may have shortcomings. I would be grateful if you consider those
from excusable point.
Thank you for your consideration.
Sincerely Yours,
Group- 01
MBA 1st Semester
11th Batch
Department of Finance
Jagannath University, Dhaka.
15 March, 2022
Dr. Shaikh Mashrick Hasan, PhD
Associate Professor
Department of Finance
Jagannath University, Dhaka- 1000.
Subject: Submission of research paper on “The Impact of COVID-19 Pandemic on the
profitability of Banking Sector: A Study on Bangladesh.”
Dear Sir,
It is a great delight for us to submit our research report on “The Impact of COVID-19 Pandemic
on the Profitability of Banking Sector: A Study on Bangladesh.” It was assigned to us for a
partial necessity for the fulfillment of FIN/BNK-5104 course. Throughout the study we have
tried our best to accommodate as much data and relevant information as possible.
We have always tried to consider your remarks and instructions very carefully while preparing
this report. We have tried always to follow your schedule, format and discipline. The whole
experiences of making this report enabled us to know about research processes. We are grateful
to you for providing such an opportunity.
We have tried to give my best effort on making this report informative and comprehensive
enough. Despite that there may have shortcomings. I would be grateful if you consider those
from excusable point.
Thank you for your consideration.
Sincerely Yours,
Group- 01
MBA 1st Semester
11th Batch
Department of Finance
Jagannath University, Dhaka.

Group 01
Sl. No. Name ID
01 Saimoon Islam B160203007
02 Abu Raihan B160203013
03 Kayes B160203030
04 Parvej Mia B160203078
05 Monira Sultana B160203083
06 Nusrat Jahan Rima B160203098
07 Arman Hossain B160203100
08 Tulip Rashid Lima B160203101
09 Aditto Kumer Mohonto B160203113
10 Setu Ghosh B160203114
Sl. No. Name ID
01 Saimoon Islam B160203007
02 Abu Raihan B160203013
03 Kayes B160203030
04 Parvej Mia B160203078
05 Monira Sultana B160203083
06 Nusrat Jahan Rima B160203098
07 Arman Hossain B160203100
08 Tulip Rashid Lima B160203101
09 Aditto Kumer Mohonto B160203113
10 Setu Ghosh B160203114

Contents
Chapter One: Introduction...........................................................................................................1
1.1 Background of the Research..................................................................................................1
1.2 Aim of the Research..............................................................................................................2
1.3 Objectives of the Research....................................................................................................2
1.4 Research Questions................................................................................................................2
1.5 Scope of the Research............................................................................................................3
1.6 Limitations of the Research...................................................................................................3
Chapter Two: Literature Review.................................................................................................3
Chapter Three: Research Methodology......................................................................................6
3.1 Research Approaches.............................................................................................................6
3.2 Research Methods..................................................................................................................6
3.3 Data Collection Method.........................................................................................................6
3.4 Sampling Design....................................................................................................................7
3.5 Research Techniques of Analysis..........................................................................................7
Chapter Four: Analysis and Discussion......................................................................................9
4.1 Descriptive Statistics.............................................................................................................9
4.2 T-Test...................................................................................................................................10
4.2.1 T-test for ROA..............................................................................................................11
4.2.2 T-test for ROE..............................................................................................................12
4.2.3 T-test for NIM...............................................................................................................13
4.3 Trend Analysis.....................................................................................................................15
4.3.1 Investment Income........................................................................................................15
4.3.2 Net Investment Income.................................................................................................16
4.3.3 Operating Profit............................................................................................................17
Chapter One: Introduction...........................................................................................................1
1.1 Background of the Research..................................................................................................1
1.2 Aim of the Research..............................................................................................................2
1.3 Objectives of the Research....................................................................................................2
1.4 Research Questions................................................................................................................2
1.5 Scope of the Research............................................................................................................3
1.6 Limitations of the Research...................................................................................................3
Chapter Two: Literature Review.................................................................................................3
Chapter Three: Research Methodology......................................................................................6
3.1 Research Approaches.............................................................................................................6
3.2 Research Methods..................................................................................................................6
3.3 Data Collection Method.........................................................................................................6
3.4 Sampling Design....................................................................................................................7
3.5 Research Techniques of Analysis..........................................................................................7
Chapter Four: Analysis and Discussion......................................................................................9
4.1 Descriptive Statistics.............................................................................................................9
4.2 T-Test...................................................................................................................................10
4.2.1 T-test for ROA..............................................................................................................11
4.2.2 T-test for ROE..............................................................................................................12
4.2.3 T-test for NIM...............................................................................................................13
4.3 Trend Analysis.....................................................................................................................15
4.3.1 Investment Income........................................................................................................15
4.3.2 Net Investment Income.................................................................................................16
4.3.3 Operating Profit............................................................................................................17
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4.3.4 Profit before tax............................................................................................................17
4.3.5 Net profit.......................................................................................................................18
4.3.6 ROE..............................................................................................................................19
4.3.7 ROA..............................................................................................................................20
4.4 Regression Analysis.............................................................................................................21
4.4.1 Return on Assets (ROA)...............................................................................................22
4.4.2 Return on Equity (ROE)...............................................................................................23
4.4.3 Net Profit......................................................................................................................24
4.4.4 Net Investment Income.................................................................................................24
4.4.5 Operating Profit............................................................................................................25
4.5 Summary of Research Analysis...........................................................................................25
Chapter Five: Conclusion...........................................................................................................26
Chapter Six: References..............................................................................................................28
4.3.5 Net profit.......................................................................................................................18
4.3.6 ROE..............................................................................................................................19
4.3.7 ROA..............................................................................................................................20
4.4 Regression Analysis.............................................................................................................21
4.4.1 Return on Assets (ROA)...............................................................................................22
4.4.2 Return on Equity (ROE)...............................................................................................23
4.4.3 Net Profit......................................................................................................................24
4.4.4 Net Investment Income.................................................................................................24
4.4.5 Operating Profit............................................................................................................25
4.5 Summary of Research Analysis...........................................................................................25
Chapter Five: Conclusion...........................................................................................................26
Chapter Six: References..............................................................................................................28

1
Chapter One: Introduction
A bank is a type of financial institution that is permitted to accept deposits and provide loans.
Financial services such as wealth management, currency exchange, and safe deposit schemes
may be offered by banks. It accepts public deposits and develops demand deposits while issuing
loans. It is very important for both consumers and businesses. Banks are the blood of the
economy. The banking system plays a very important role in the economic life of the nation. The
total money circulation of the economy is done through the banks. In a rapid growth
development country like Bangladesh, banks play a crucial role in ensuring that funds are
distributed evenly across the economy's several sectors. Banks must also sustain profitability to
preserve their long-term survival. The main goal of the bank is to earn profit for its shareholders
and the banking system's goal is to give economic security.
1.1 Background of the Research
A strong banking system helps to build up a strong economy in a country. Through a proper and
efficient banking system, international trade, its payment system, remittance, employment scope,
transaction procedure become easier and swift that means it can easily be said, the whole
economic system can be boosted up through an efficient banking system. In Bangladesh, there
are 61 scheduled banks including 6 state-owned commercial banks, 3 specialized banks, and 43
private commercial banks which play a proficient role to boost the economic condition in
Bangladesh. In 43 private commercial banks, there are 33 commercial banks and 10 non-
conventional banks (Islami Shariah Based Private Commercial Banks).
So, the banking industry has a proficient role in any country's economy, any adverse situation
especially macroeconomic factors can prejudice the economic condition not only of the banking
sector but also the economic condition of the whole country. After the first detection of Covid-19
on 31st December in 2019 in Wuhan city of China, this SARS-CoV-2 virus was rapidly spread
almost all over the world. Due to the swift spread of Covid-19, different types of business
organizations, financial institutions even if educational institutions are kept shut down when
there is a high possibility of widespread Covid-19 and the mortality rate of people. In the cases
of lockdown, most of the employees have to work from home to continue the day-to-day
operations of banks. Many employees of the ranking indusiate infected and also died due to
Chapter One: Introduction
A bank is a type of financial institution that is permitted to accept deposits and provide loans.
Financial services such as wealth management, currency exchange, and safe deposit schemes
may be offered by banks. It accepts public deposits and develops demand deposits while issuing
loans. It is very important for both consumers and businesses. Banks are the blood of the
economy. The banking system plays a very important role in the economic life of the nation. The
total money circulation of the economy is done through the banks. In a rapid growth
development country like Bangladesh, banks play a crucial role in ensuring that funds are
distributed evenly across the economy's several sectors. Banks must also sustain profitability to
preserve their long-term survival. The main goal of the bank is to earn profit for its shareholders
and the banking system's goal is to give economic security.
1.1 Background of the Research
A strong banking system helps to build up a strong economy in a country. Through a proper and
efficient banking system, international trade, its payment system, remittance, employment scope,
transaction procedure become easier and swift that means it can easily be said, the whole
economic system can be boosted up through an efficient banking system. In Bangladesh, there
are 61 scheduled banks including 6 state-owned commercial banks, 3 specialized banks, and 43
private commercial banks which play a proficient role to boost the economic condition in
Bangladesh. In 43 private commercial banks, there are 33 commercial banks and 10 non-
conventional banks (Islami Shariah Based Private Commercial Banks).
So, the banking industry has a proficient role in any country's economy, any adverse situation
especially macroeconomic factors can prejudice the economic condition not only of the banking
sector but also the economic condition of the whole country. After the first detection of Covid-19
on 31st December in 2019 in Wuhan city of China, this SARS-CoV-2 virus was rapidly spread
almost all over the world. Due to the swift spread of Covid-19, different types of business
organizations, financial institutions even if educational institutions are kept shut down when
there is a high possibility of widespread Covid-19 and the mortality rate of people. In the cases
of lockdown, most of the employees have to work from home to continue the day-to-day
operations of banks. Many employees of the ranking indusiate infected and also died due to

2
Covid-19. Besides, many business organizations become defaulted for being g failures in their
business organizations. So Covid-19 has a strong impact on the banking industry in any country.
In Bangladesh the first covid was identified on 8th March in 2020. According to the Bangladesh
Bank report, 27237 employees of commercial Banks included the government state, and private
commercial banks are infected in Covid-19. Besides, almost 143 bankers are died due to Covid-
19. From the Covid period, financial institutions of Bangladesh instate-owned owned as well as
private commercial banks have to limit their office hours as well as employees in several times in
lockdown phenomenon. That induces the reduction of their profit because after identified of
Covid-19, non-performing loans grew more than 7% according to Bangladesh Bank in the period
January- March of 2021. The amount of nonperforming loans is almost Tk. 950.85 billion during
the mentioned period. Most of the banks experience lower operating profit and net profit through
the government of Bangladesh offered many stimulus packages to boost up the economic
condition of the banking industry.
1.2 Aim of the Research
The study aims to find out whether Covid-19 has an impact on the banking industry or not.
1.3 Objectives of the Research
As the title of the study is Impact of Covid-19 on Banking Industry in Bangladesh so there are
some specific objectives of this study. These are a) t-test (hypothesis test to determine
significance difference in sample mean) between before covid-19 period and after Covid-19
period in Return on Asset (ROA), Return on Equity (ROE) and Net Interest Margin (NIM), b)
Trend Analysis to show the impact of investment Income, Net Investment Income, Profit Before
Tax, Operating profit, Net profit After Tax, ROA and ROE based on a confirmed case of Covid-
19, Test Positivity Rate and Death Cases and c) Regression Analysis (statistical measure to
determine the relationship between dependent variables and independent variables).
1.4 Research Questions
What’s the impact of Covid-19 on the banking sector profitability in Bangladesh?
Is the fluctuation of profitability occur in banking industry with the fluctuation of Covid-
19?
Covid-19. Besides, many business organizations become defaulted for being g failures in their
business organizations. So Covid-19 has a strong impact on the banking industry in any country.
In Bangladesh the first covid was identified on 8th March in 2020. According to the Bangladesh
Bank report, 27237 employees of commercial Banks included the government state, and private
commercial banks are infected in Covid-19. Besides, almost 143 bankers are died due to Covid-
19. From the Covid period, financial institutions of Bangladesh instate-owned owned as well as
private commercial banks have to limit their office hours as well as employees in several times in
lockdown phenomenon. That induces the reduction of their profit because after identified of
Covid-19, non-performing loans grew more than 7% according to Bangladesh Bank in the period
January- March of 2021. The amount of nonperforming loans is almost Tk. 950.85 billion during
the mentioned period. Most of the banks experience lower operating profit and net profit through
the government of Bangladesh offered many stimulus packages to boost up the economic
condition of the banking industry.
1.2 Aim of the Research
The study aims to find out whether Covid-19 has an impact on the banking industry or not.
1.3 Objectives of the Research
As the title of the study is Impact of Covid-19 on Banking Industry in Bangladesh so there are
some specific objectives of this study. These are a) t-test (hypothesis test to determine
significance difference in sample mean) between before covid-19 period and after Covid-19
period in Return on Asset (ROA), Return on Equity (ROE) and Net Interest Margin (NIM), b)
Trend Analysis to show the impact of investment Income, Net Investment Income, Profit Before
Tax, Operating profit, Net profit After Tax, ROA and ROE based on a confirmed case of Covid-
19, Test Positivity Rate and Death Cases and c) Regression Analysis (statistical measure to
determine the relationship between dependent variables and independent variables).
1.4 Research Questions
What’s the impact of Covid-19 on the banking sector profitability in Bangladesh?
Is the fluctuation of profitability occur in banking industry with the fluctuation of Covid-
19?
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3
1.5 Scope of the Research
The aim of our research paper is to find out whether Covid-19 has an impact on the banking
industry or not. So, the main scope in this area is to realize the difficulties of banking sector,
collecting financial information from website of particular banks, different articles & central
bank’s website. During preparing the research paper, the main concerned area was how to
acquire useful and relevant information and find out which methods is useful to prove the impact
on Covid-19 on banking industry.
1.6 Limitations of the Research
Every research has some limitations. This research paper is not exceptional than others. It has
also some limitations like inadequacy of related information, limited time period and lack of
knowledge are some important limitations faced during doing that study.
Chapter Two: Literature Review
The whole world is affected ambivalently due to the covid-19 pandemic after first detected on
31st December in 2019. The adverse impact the of the economy is mainly due to the closing
down of organization when covid-19 outbreak severely in a particular area. As the result,
banking industries of all country unifaces many more different challenges. Bangladesh’s banking
industry is not exceptional as others. This industry has already identified a lot of scams and
inconsistencies in both conventional and non-conventional banks inadequacy of corporate
governance, excessive level of non-performing loan, shortfall of required capital, delay
procedure in the repayment of the loan. These challenges have been begun at the first wave of
covid-19 in Bangladesh which is also sustained in present and the conditions of the banking
sector is becoming worst day by day though government has taken some initiatives and stimulus
packages
Covid-19 has also adverse impact on banking sector in Indonesia also. Darjana, D., Wiryono, S.
K., & Koesrindartoto, D. P. (2022). The objectives of this paper are to find out the pandemic’s
impact on the banking sector in Indonesia. For this, the research paper used data from 2011 to
2020. This study evaluates the credit performance of banking sector in pandemic period which is
not satisfactory level compared to non-pandemic period. In this research paper, they used
Difference-in-Differences Analysis. This analysis is also known as DID which is one of the most
1.5 Scope of the Research
The aim of our research paper is to find out whether Covid-19 has an impact on the banking
industry or not. So, the main scope in this area is to realize the difficulties of banking sector,
collecting financial information from website of particular banks, different articles & central
bank’s website. During preparing the research paper, the main concerned area was how to
acquire useful and relevant information and find out which methods is useful to prove the impact
on Covid-19 on banking industry.
1.6 Limitations of the Research
Every research has some limitations. This research paper is not exceptional than others. It has
also some limitations like inadequacy of related information, limited time period and lack of
knowledge are some important limitations faced during doing that study.
Chapter Two: Literature Review
The whole world is affected ambivalently due to the covid-19 pandemic after first detected on
31st December in 2019. The adverse impact the of the economy is mainly due to the closing
down of organization when covid-19 outbreak severely in a particular area. As the result,
banking industries of all country unifaces many more different challenges. Bangladesh’s banking
industry is not exceptional as others. This industry has already identified a lot of scams and
inconsistencies in both conventional and non-conventional banks inadequacy of corporate
governance, excessive level of non-performing loan, shortfall of required capital, delay
procedure in the repayment of the loan. These challenges have been begun at the first wave of
covid-19 in Bangladesh which is also sustained in present and the conditions of the banking
sector is becoming worst day by day though government has taken some initiatives and stimulus
packages
Covid-19 has also adverse impact on banking sector in Indonesia also. Darjana, D., Wiryono, S.
K., & Koesrindartoto, D. P. (2022). The objectives of this paper are to find out the pandemic’s
impact on the banking sector in Indonesia. For this, the research paper used data from 2011 to
2020. This study evaluates the credit performance of banking sector in pandemic period which is
not satisfactory level compared to non-pandemic period. In this research paper, they used
Difference-in-Differences Analysis. This analysis is also known as DID which is one of the most

4
widely and applicable method for evaluation of impact. They also implement regression
discontinuity design to evaluate credit performance of banking sector in Indonesia.
Barua, B., & Barua, S. (2021). This article determines the potential effects of the pandemic on
Bangladesh's banking industry where the researchers used Bangladesh as a case study of a
developing economy. The banking sector in Bangladesh has already experienced a high quantity
of non-performing loans (NPLs), and the pandemic is a strong influencer to enhance this
problem. Based on three specific dimensions, the research paper determines the implications of
the COVID-19 epidemic. These three dimensions are - firm value, capital adequacy, and interest
income which are under various NPL shock circumstances where state-designed stress testing
model is used. Here the researcher uses a quantitative technique for creating a theoretical
framework and scenario-based assessments of COVID-19 on the basis of Bangladeshi banking
sector. The article employs a stress testing model established and prescribed for the banking
industry by Bangladesh Bank to provide scenario-based estimates of the expected impacts on
banks.
Miah, M. D., Suzuki, Y., & Uddin, S. S. (2021). This paper aims to assess the probable impact
of COVID-19 on the Islamic banking system in Bangladesh. As covid-19 has a wide impact on
banking industry, how much the bad impact of this needs to determine. So, this paper use mean-
variance test, baseline regression model, Robustness Check model. The mean difference between
prior and subsequent to the Covid-19 outbreak in Bangladesh's sector is statistically significant,
according to the findings. COVID-19 has a strong negative influence on Bangladesh's banking
industry in terms of premium growth, and penetration, according to the baseline regression
results. The coefficients' findings are both reliable and economically significant.
Marcu, M. R. (2021). This paper contributes to the academic research by finding action that has
taken during the pandemic period of Covid-19. In this paper, it is also showed the difference of
the crisis period of 2008-2009 and the Covid-19 period. Obviously, the crisis of Covid-19
pandemic is not similar to the other crisis because this crisis is related to the health issues as a
result the solution of this crisis is also different form others. This pandemic situation influenced
the whole economy adversely. As the banking sector plays an important role in an economy, the
effect of Covid-19 is enormous. The only major way to reduce the effect is maintaining customer
widely and applicable method for evaluation of impact. They also implement regression
discontinuity design to evaluate credit performance of banking sector in Indonesia.
Barua, B., & Barua, S. (2021). This article determines the potential effects of the pandemic on
Bangladesh's banking industry where the researchers used Bangladesh as a case study of a
developing economy. The banking sector in Bangladesh has already experienced a high quantity
of non-performing loans (NPLs), and the pandemic is a strong influencer to enhance this
problem. Based on three specific dimensions, the research paper determines the implications of
the COVID-19 epidemic. These three dimensions are - firm value, capital adequacy, and interest
income which are under various NPL shock circumstances where state-designed stress testing
model is used. Here the researcher uses a quantitative technique for creating a theoretical
framework and scenario-based assessments of COVID-19 on the basis of Bangladeshi banking
sector. The article employs a stress testing model established and prescribed for the banking
industry by Bangladesh Bank to provide scenario-based estimates of the expected impacts on
banks.
Miah, M. D., Suzuki, Y., & Uddin, S. S. (2021). This paper aims to assess the probable impact
of COVID-19 on the Islamic banking system in Bangladesh. As covid-19 has a wide impact on
banking industry, how much the bad impact of this needs to determine. So, this paper use mean-
variance test, baseline regression model, Robustness Check model. The mean difference between
prior and subsequent to the Covid-19 outbreak in Bangladesh's sector is statistically significant,
according to the findings. COVID-19 has a strong negative influence on Bangladesh's banking
industry in terms of premium growth, and penetration, according to the baseline regression
results. The coefficients' findings are both reliable and economically significant.
Marcu, M. R. (2021). This paper contributes to the academic research by finding action that has
taken during the pandemic period of Covid-19. In this paper, it is also showed the difference of
the crisis period of 2008-2009 and the Covid-19 period. Obviously, the crisis of Covid-19
pandemic is not similar to the other crisis because this crisis is related to the health issues as a
result the solution of this crisis is also different form others. This pandemic situation influenced
the whole economy adversely. As the banking sector plays an important role in an economy, the
effect of Covid-19 is enormous. The only major way to reduce the effect is maintaining customer

5
relationship by coping with the need of customers, adopting the innovations, digitalized the
banking processes.
Al Numairy, H. A., Al Essa, S. R., Alshamsi, A. S., Ahli, H. I., Al Zarooni, S. A., & Webb, H.
(2022). The research shows us how the United Arab Emirate deals with the new pandemic
situation. When crisis occurs, the drivers of an economy will not know how to deal with that new
situation beacause the result of any crisis is not consistent with others.
Collins, C. C., Remigius, I. U., & Amarachi, I. A. U. (2022). The study specifically determines
the effect of Covid-19 lockdown and social distancing on the efficiency the in the banking sector
of Nigeria. These two determinants affect the whole banking sector in Nigeria. The established
hypothesis is tested by the single regression. The sample size is determined at 364 respondents
and the questionnaires have been established to collect the data. The empirical result of the study
is covid-19 has a significant impact on the corporate effectiveness of the banking sector
negatively in Nigeria. The study concluded that to reduce the negative impact of the banking
sector of Nigeria should introduce digitalized banking services to serve regular customers as well
as potential customers.
(X Li, H Feng, S Zhao, DA Carter - Finance Research Letters, 2021), by diversifying, Banks can
potentially reduce the variability of their revenue by traditional lending activities into noninterest
revenue sources. After invigoration of the effect of COVID-19 on the relation between inerest
and bank profit and risk found a result that it tightened the credit standards and reduce the
demand for many types of loans. Noninterest revenue sources are positively related to
performance and inversely related to risk and it is consistent with a beneficial diversification
effect during the pandemic.
Juergensen, J.; Guimón, J.; Narula, R. European SMEs amidst the COVID-19 crisis: Assessing
impact and policy responses. J. Ind. Bus. Econ. 2020, examining 8000 Spanish Companies,
stated that the COVID-19 has significantly affected their activities, reducing financial liquidity
and
Profitability which declines the economic activity in Spain since 2002. Borri, N.; di Giorgio, G.
Systemic risk and the COVID challenge in the European banking sector. J. Bank Finance. 2021,
confirmed by the study that credit risk costs increase because of the COVID-19 pandemic which
impacts the bank’s size.
relationship by coping with the need of customers, adopting the innovations, digitalized the
banking processes.
Al Numairy, H. A., Al Essa, S. R., Alshamsi, A. S., Ahli, H. I., Al Zarooni, S. A., & Webb, H.
(2022). The research shows us how the United Arab Emirate deals with the new pandemic
situation. When crisis occurs, the drivers of an economy will not know how to deal with that new
situation beacause the result of any crisis is not consistent with others.
Collins, C. C., Remigius, I. U., & Amarachi, I. A. U. (2022). The study specifically determines
the effect of Covid-19 lockdown and social distancing on the efficiency the in the banking sector
of Nigeria. These two determinants affect the whole banking sector in Nigeria. The established
hypothesis is tested by the single regression. The sample size is determined at 364 respondents
and the questionnaires have been established to collect the data. The empirical result of the study
is covid-19 has a significant impact on the corporate effectiveness of the banking sector
negatively in Nigeria. The study concluded that to reduce the negative impact of the banking
sector of Nigeria should introduce digitalized banking services to serve regular customers as well
as potential customers.
(X Li, H Feng, S Zhao, DA Carter - Finance Research Letters, 2021), by diversifying, Banks can
potentially reduce the variability of their revenue by traditional lending activities into noninterest
revenue sources. After invigoration of the effect of COVID-19 on the relation between inerest
and bank profit and risk found a result that it tightened the credit standards and reduce the
demand for many types of loans. Noninterest revenue sources are positively related to
performance and inversely related to risk and it is consistent with a beneficial diversification
effect during the pandemic.
Juergensen, J.; Guimón, J.; Narula, R. European SMEs amidst the COVID-19 crisis: Assessing
impact and policy responses. J. Ind. Bus. Econ. 2020, examining 8000 Spanish Companies,
stated that the COVID-19 has significantly affected their activities, reducing financial liquidity
and
Profitability which declines the economic activity in Spain since 2002. Borri, N.; di Giorgio, G.
Systemic risk and the COVID challenge in the European banking sector. J. Bank Finance. 2021,
confirmed by the study that credit risk costs increase because of the COVID-19 pandemic which
impacts the bank’s size.
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Chapter Three: Research Methodology
The research methodology includes the overall procedure of research which includes data
collection, retrieving, analyzing, and implementing appropriate tools and techniques to find out
the solution. A research method is a part of research methodology which means tools and
techniques selecting procedures to find out the solution of research. There are two types of
research methodology used for finding the solution of the research. The first one is a comparative
case study in which individual or organizational researchers involves and data is collected
through primary sources. And the second one is a systematic review in which research studies
various research papers, journals, articles, etc. Data is collected through secondary data sources
and literature reviews used for every research paper.
3.1 Research Approaches
Methodological approaches are the information and techniques to solve the research. There are
two types of approach one quantitative approach where numerical data is used and various
statistical tools are applied to find out the solution, the second qualitative approach is done via
qualitative data and the results occur based on descriptive modeling (Chakrabarti, 2014). In this
research paper, a quantitative approach will be used to find out the solution to the research
problem.
3.2 Research Methods
The research method is a part of research methodology which means tools and techniques
selecting procedures to find out the solution of research. In this part, we discuss the method of
data collection and tools-techniques used for analyzing the data.
Chapter Three: Research Methodology
The research methodology includes the overall procedure of research which includes data
collection, retrieving, analyzing, and implementing appropriate tools and techniques to find out
the solution. A research method is a part of research methodology which means tools and
techniques selecting procedures to find out the solution of research. There are two types of
research methodology used for finding the solution of the research. The first one is a comparative
case study in which individual or organizational researchers involves and data is collected
through primary sources. And the second one is a systematic review in which research studies
various research papers, journals, articles, etc. Data is collected through secondary data sources
and literature reviews used for every research paper.
3.1 Research Approaches
Methodological approaches are the information and techniques to solve the research. There are
two types of approach one quantitative approach where numerical data is used and various
statistical tools are applied to find out the solution, the second qualitative approach is done via
qualitative data and the results occur based on descriptive modeling (Chakrabarti, 2014). In this
research paper, a quantitative approach will be used to find out the solution to the research
problem.
3.2 Research Methods
The research method is a part of research methodology which means tools and techniques
selecting procedures to find out the solution of research. In this part, we discuss the method of
data collection and tools-techniques used for analyzing the data.

7
3.3 Data Collection Method
There are two types of data collection methods. One is primary sources and another one is
secondary sources. Here we collect data from secondary sources. As our research is based on the
banking industry in Bangladesh, we collect data based on a sample basis. The way of choosing
10 banks from all banks in Bangladesh is described next.
3.4 Sampling Design
Sampling design means a way of sample drawn from the population. In this research banking
industry is our population. From this population, first, we divide banks into two sides one is
Islamic banks and another is conventional banks. Then we make plan 4 banks choose from
Islamic banks and 6 banks choose from conventional banks. Then select 4 Islamic banks based
on capitalization (one high capitalized bank which is Islamic Bank Bangladesh Ltd., one low
capitalized bank which is Social Islamic Bank Limited and the next two are mid capitalized
banks). In the same way, 6 conventional banks are selected (One high capitalized, one low, and
the other 4 mid capitalized banks). The selected bank’s name is given below_
Al-Arafa Islami Bank Limited
Social Islami Bank Limited
First Security Islami Bank Limited
Islami Bank Bangladesh Limited
Jamuna Bank Limited
NCC Bank Ltd.
National Bank Limited
Mercantile Bank Limited
South East Bank Limited
Bank Asia
3.5 Research Techniques of Analysis
Research techniques are the procedures of data analysis to find out the research solution. Our
research topic is, “The Impact of COVID-19 on the Banking Sector of Bangladesh”. Here we try
to find out the profitability of the banking industry before COVID is significantly different from
3.3 Data Collection Method
There are two types of data collection methods. One is primary sources and another one is
secondary sources. Here we collect data from secondary sources. As our research is based on the
banking industry in Bangladesh, we collect data based on a sample basis. The way of choosing
10 banks from all banks in Bangladesh is described next.
3.4 Sampling Design
Sampling design means a way of sample drawn from the population. In this research banking
industry is our population. From this population, first, we divide banks into two sides one is
Islamic banks and another is conventional banks. Then we make plan 4 banks choose from
Islamic banks and 6 banks choose from conventional banks. Then select 4 Islamic banks based
on capitalization (one high capitalized bank which is Islamic Bank Bangladesh Ltd., one low
capitalized bank which is Social Islamic Bank Limited and the next two are mid capitalized
banks). In the same way, 6 conventional banks are selected (One high capitalized, one low, and
the other 4 mid capitalized banks). The selected bank’s name is given below_
Al-Arafa Islami Bank Limited
Social Islami Bank Limited
First Security Islami Bank Limited
Islami Bank Bangladesh Limited
Jamuna Bank Limited
NCC Bank Ltd.
National Bank Limited
Mercantile Bank Limited
South East Bank Limited
Bank Asia
3.5 Research Techniques of Analysis
Research techniques are the procedures of data analysis to find out the research solution. Our
research topic is, “The Impact of COVID-19 on the Banking Sector of Bangladesh”. Here we try
to find out the profitability of the banking industry before COVID is significantly different from

8
during COVID profitability. To find out this solution various statistical analyses were used for
this research paper which are descriptive statistics, t-test, trend analysis, and regression analysis.
Descriptive Statistics: descriptive statistics describe coefficients or characteristics that
summarize our data set. In this research, two types of descriptive statistics were conducted. One
is a central tendency that defines the central value of data and another one is a measure of
dispersion which measures the variability of the data set. Mean and median are done for
measuring central tendency and the standard deviation is a measure for dispersion.
T-Test: A T-test is a hypothesis testing test. It is a part of inferential statistics where this analysis
determines if there is a significant difference between the two groups. If the two groups are
similar is called a pair group and if the two are not similar is called an unpaired group. For paired
group, the paired-samples t-test calculates for hypothesis testing. On the other hand, for the
unpaired group, the unpaired samples t-test calculates for hypothesis testing. In this analysis, we
conduct paired samples t-test for our hypothesis testing. This measurement is done for a
measurement that is taken from the different periods.
Trend Analysis: Trend analysis is a type of technique that is used in technical analysis that
attempts to predict future movements of variables based on recent or historical
observed trend data. Trend analysis attempt to spot a pattern for the variables after observing the
historical data and according to that pattern it predicts how the future movement of variables
might be.
Regression Analysis: Regression analysis is a statistical tool that shows the relationship between
different variables (one dependent variable and one more independent variable). By using
historical data regression shows how dependent variable affected by the independent variable or
variables. Then it helps the analyst to forecast future change of dependent variable by using their
relationship.
during COVID profitability. To find out this solution various statistical analyses were used for
this research paper which are descriptive statistics, t-test, trend analysis, and regression analysis.
Descriptive Statistics: descriptive statistics describe coefficients or characteristics that
summarize our data set. In this research, two types of descriptive statistics were conducted. One
is a central tendency that defines the central value of data and another one is a measure of
dispersion which measures the variability of the data set. Mean and median are done for
measuring central tendency and the standard deviation is a measure for dispersion.
T-Test: A T-test is a hypothesis testing test. It is a part of inferential statistics where this analysis
determines if there is a significant difference between the two groups. If the two groups are
similar is called a pair group and if the two are not similar is called an unpaired group. For paired
group, the paired-samples t-test calculates for hypothesis testing. On the other hand, for the
unpaired group, the unpaired samples t-test calculates for hypothesis testing. In this analysis, we
conduct paired samples t-test for our hypothesis testing. This measurement is done for a
measurement that is taken from the different periods.
Trend Analysis: Trend analysis is a type of technique that is used in technical analysis that
attempts to predict future movements of variables based on recent or historical
observed trend data. Trend analysis attempt to spot a pattern for the variables after observing the
historical data and according to that pattern it predicts how the future movement of variables
might be.
Regression Analysis: Regression analysis is a statistical tool that shows the relationship between
different variables (one dependent variable and one more independent variable). By using
historical data regression shows how dependent variable affected by the independent variable or
variables. Then it helps the analyst to forecast future change of dependent variable by using their
relationship.
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Chapter Four: Analysis and Discussion
Particular
s
Before COVID During COVID
Observation Mean Median S.D. Observation Mean Median S.D.
Investmen
t Income 10
23949.63 20205.88 13223.3
6
10 29461.74 24290.89 18013.83
Net
Investmen
t Income
10 7962.12 6143.24 6237.10 10 8298.32 5943.70 8102.89
Operating
Income
10 10679.02445 7963.4665 9040.46 10 11432.49367 7476.165 10748.63
Profit
Before Tax
10 4906.554395 3829.901235 2749.19 10 4807.129323 4173.263636 2343.01
Net Profit 10 2536.23879 2191.704231 1103.15 10 2626.754844 2401.778362 863.69
ROA 10 0.86% 0.88% 0.24% 10 0.62% 0.59% 0.23%
ROE 10 11.39% 11.41% 1.62% 10 9.65% 9.19% 2.81%
4.1 Descriptive Statistics
Table 1: Result of Descriptive Statistics
Chapter Four: Analysis and Discussion
Particular
s
Before COVID During COVID
Observation Mean Median S.D. Observation Mean Median S.D.
Investmen
t Income 10
23949.63 20205.88 13223.3
6
10 29461.74 24290.89 18013.83
Net
Investmen
t Income
10 7962.12 6143.24 6237.10 10 8298.32 5943.70 8102.89
Operating
Income
10 10679.02445 7963.4665 9040.46 10 11432.49367 7476.165 10748.63
Profit
Before Tax
10 4906.554395 3829.901235 2749.19 10 4807.129323 4173.263636 2343.01
Net Profit 10 2536.23879 2191.704231 1103.15 10 2626.754844 2401.778362 863.69
ROA 10 0.86% 0.88% 0.24% 10 0.62% 0.59% 0.23%
ROE 10 11.39% 11.41% 1.62% 10 9.65% 9.19% 2.81%
4.1 Descriptive Statistics
Table 1: Result of Descriptive Statistics

10
Observations: Observation shows number data set used for analysis. For our analysis we taken
10 years data of before COVID (2010-2019) that’s why observation is ten and 1 year data set
taken during COVID but for 10 banks that’s why number of observation is ten. Before COVID
10 year’s data are convert into single year by doing weighted average.
Mean: Mean is a measure of descriptive statistics which is calculated by the average of data set.
From the table we see that during COVID value of investment income, net investment income
and operating income’s mean is higher than before COVID profit. But the case is reverse in case
of ROA, ROE and NIM which are higher in before COVID. The reason behind this profitability
percentage is decrease during COVID period according to amount of asset and equity available
to the bank. In case of ROA 0.86% before COVID but during COVID which is 0.62%.
Median: Median is the middle value among the list of data. For determining mean value at first
data sorted into ascending or descending order. Median of profit before tax, ROA, ROE and NIM
are higher before COVID period than during COVID time. In case of first three factors which is
different because in terms of money profit was increased but in according to asset, equity amount
that not increase. Median in case of ROA is 0.88% before COVID but 0.59% during COVID
which is far less.
Standard Deviation: Standard deviation is the square root of variance which measures variance
or dispersion of data set. More and more data are dispersed that provide more inaccurate result.
In case of ROA and ROE dispersion of data is lower both during COVID and before COVID but
this dispersion is higher in case of investment income, net investment income. In case of ROA
SD is 0.24% before COVID and 0.23% during COVID.
4.2 T-Test
In this research paper, two independent variables use for this hypothesis testing (t-test) one is
before COVID19 profitability of bank and during COVID profit. For this research paper, 10
banks were selected based on 4 selected Islamic Shariah-based banks and 6 selected from
conventional banks. The banks choose based on some random basis and average asset and
liability not very highly capitalized bank not lower capitalized bank. Here t-test is conducted for
10 banks’ returns on asset (ROA), return on equity (ROE), and net interest margin (NIM).
Observations: Observation shows number data set used for analysis. For our analysis we taken
10 years data of before COVID (2010-2019) that’s why observation is ten and 1 year data set
taken during COVID but for 10 banks that’s why number of observation is ten. Before COVID
10 year’s data are convert into single year by doing weighted average.
Mean: Mean is a measure of descriptive statistics which is calculated by the average of data set.
From the table we see that during COVID value of investment income, net investment income
and operating income’s mean is higher than before COVID profit. But the case is reverse in case
of ROA, ROE and NIM which are higher in before COVID. The reason behind this profitability
percentage is decrease during COVID period according to amount of asset and equity available
to the bank. In case of ROA 0.86% before COVID but during COVID which is 0.62%.
Median: Median is the middle value among the list of data. For determining mean value at first
data sorted into ascending or descending order. Median of profit before tax, ROA, ROE and NIM
are higher before COVID period than during COVID time. In case of first three factors which is
different because in terms of money profit was increased but in according to asset, equity amount
that not increase. Median in case of ROA is 0.88% before COVID but 0.59% during COVID
which is far less.
Standard Deviation: Standard deviation is the square root of variance which measures variance
or dispersion of data set. More and more data are dispersed that provide more inaccurate result.
In case of ROA and ROE dispersion of data is lower both during COVID and before COVID but
this dispersion is higher in case of investment income, net investment income. In case of ROA
SD is 0.24% before COVID and 0.23% during COVID.
4.2 T-Test
In this research paper, two independent variables use for this hypothesis testing (t-test) one is
before COVID19 profitability of bank and during COVID profit. For this research paper, 10
banks were selected based on 4 selected Islamic Shariah-based banks and 6 selected from
conventional banks. The banks choose based on some random basis and average asset and
liability not very highly capitalized bank not lower capitalized bank. Here t-test is conducted for
10 banks’ returns on asset (ROA), return on equity (ROE), and net interest margin (NIM).

11
4.2.1 T-test for ROA
Paired Differences
T df Sig (2-
tailed)Mean
Std.
Deviatio
n
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Two
samples
paired
t-test
0.24% 0.1862% 0.0589% 0.11% 0.38% 4.125 9 0.002580
Here we use 10 banks before COVID and during COVID ROA for the t-test. The calculation
procedure describes below.
Mean is the average difference between two groups. Formula (Before COVID ROA-
After COVID ROA)/Number of Observations
Standard Deviation: Standard deviation of two dependent groups.
Standard error is calculated by (standard deviation/square root (Observations))
T: T denotes t-statistics for paired T-test.
df denotes for degrees of freedom which is n-1.
4.2.1 T-test for ROA
Paired Differences
T df Sig (2-
tailed)Mean
Std.
Deviatio
n
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Two
samples
paired
t-test
0.24% 0.1862% 0.0589% 0.11% 0.38% 4.125 9 0.002580
Here we use 10 banks before COVID and during COVID ROA for the t-test. The calculation
procedure describes below.
Mean is the average difference between two groups. Formula (Before COVID ROA-
After COVID ROA)/Number of Observations
Standard Deviation: Standard deviation of two dependent groups.
Standard error is calculated by (standard deviation/square root (Observations))
T: T denotes t-statistics for paired T-test.
df denotes for degrees of freedom which is n-1.
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Significance (2-tailed) denotes for p-value which defines significance level for a given
degree of freedom.
The two hypotheses for this test are_
H0: μ1= μ2 (The ROA is equal for two dependent variables)
H1: μ1≠μ2 (The ROA don’t equal for two dependent variables)
From the result we can interpret that, there is a positive correlation between the two groups
because (r = 0.69, p = .002580) that means the return on assets before COVID and after COVID
are positively correlated. From the table we find that in 95% confidence level lower value is
0.11% and the higher value is 0.38%, so the average difference between during COVID and after
COVID in the case for upper value and the lower value is 0.245%. The value we get here is
0.002580 which is in the rejected region of the null hypothesis at a significance level of 5% in
degrees of freedom 9. So, the alternative hypothesis is accepted (H1: μ1≠μ2). So according to
ROA before COVID19 profit is significantly different from during COVID19 ROA according to
the two-tail t-test.
4.2.2 T-test for ROE
Paired Differences
T df Sig (2-
tailed)Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Two
samples
paired
t-test
1.74% 0.02243 0.00709 0.1309% 3.34% 2.44668582 9 0.03695
Significance (2-tailed) denotes for p-value which defines significance level for a given
degree of freedom.
The two hypotheses for this test are_
H0: μ1= μ2 (The ROA is equal for two dependent variables)
H1: μ1≠μ2 (The ROA don’t equal for two dependent variables)
From the result we can interpret that, there is a positive correlation between the two groups
because (r = 0.69, p = .002580) that means the return on assets before COVID and after COVID
are positively correlated. From the table we find that in 95% confidence level lower value is
0.11% and the higher value is 0.38%, so the average difference between during COVID and after
COVID in the case for upper value and the lower value is 0.245%. The value we get here is
0.002580 which is in the rejected region of the null hypothesis at a significance level of 5% in
degrees of freedom 9. So, the alternative hypothesis is accepted (H1: μ1≠μ2). So according to
ROA before COVID19 profit is significantly different from during COVID19 ROA according to
the two-tail t-test.
4.2.2 T-test for ROE
Paired Differences
T df Sig (2-
tailed)Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Two
samples
paired
t-test
1.74% 0.02243 0.00709 0.1309% 3.34% 2.44668582 9 0.03695

13
The two hypotheses for this test are_
H0: μ1= μ2 (The ROE is equal for two dependent variables)
H1: μ1≠μ2 (The ROE don’t equal for two dependent variables)
From the result we can interpret that, there is a positive correlation between the two groups
because (r = 0.60, p = .003695) that means the return on equity before COVID and after COVID
are positively correlated. From the table we find that in 95% confidence level lower value is
0.1309% and the higher value is 3.34%, so the average difference between during COVID and
after COVID in the case for upper value and the lower value is 1.74%. The value we get here is
0.003695 which is in the rejected region of the null hypothesis at a significance level of 5% in
degrees of freedom 9. So, the alternative hypothesis is accepted (H1: μ1≠μ2). So according to
ROE before COVID19 profit is significantly different from during COVID19 ROE according to
the two-tail t-test.
4.2.3 T-test for NIM
Paired Differences
T df Sig (2-
tailed)
Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Two
samples
paired t-
test
0.64% 0.00348 0.00110 0.39% 0.8906% 5.8366 9 0.000248
The two hypotheses for this test are_
The two hypotheses for this test are_
H0: μ1= μ2 (The ROE is equal for two dependent variables)
H1: μ1≠μ2 (The ROE don’t equal for two dependent variables)
From the result we can interpret that, there is a positive correlation between the two groups
because (r = 0.60, p = .003695) that means the return on equity before COVID and after COVID
are positively correlated. From the table we find that in 95% confidence level lower value is
0.1309% and the higher value is 3.34%, so the average difference between during COVID and
after COVID in the case for upper value and the lower value is 1.74%. The value we get here is
0.003695 which is in the rejected region of the null hypothesis at a significance level of 5% in
degrees of freedom 9. So, the alternative hypothesis is accepted (H1: μ1≠μ2). So according to
ROE before COVID19 profit is significantly different from during COVID19 ROE according to
the two-tail t-test.
4.2.3 T-test for NIM
Paired Differences
T df Sig (2-
tailed)
Mean
Std.
Deviation
Std.
Error
Mean
95% Confidence
Interval of the
Difference
Lower Upper
Two
samples
paired t-
test
0.64% 0.00348 0.00110 0.39% 0.8906% 5.8366 9 0.000248
The two hypotheses for this test are_

14
H0: μ1= μ2 (The NIM is equal for two dependent variables)
H1: μ1≠μ2 (The NIM don’t equal for two dependent variables)
From the result we can interpret that, there is a positive correlation between the two groups
because (r = 0.82, p = .00248) that means the return on assets before COVID and after COVID
are positively correlated. From the table we find that in 95% confidence level lower value is
0.39% and the higher value is 0.8906%, so the average difference between during COVID and
after COVID in the case for upper value and the lower value is 0.64%. The value we get here is
0.002580 which is in the rejected region of the null hypothesis at a significance level of 5% in
degrees of freedom 9. So, the alternative hypothesis is accepted (H1: μ1≠μ2). So according to NIM
before COVID19 profit is significantly different from during COVID19 NIM according to the
two-tail t-test.
From the previous three t-test analysis, we see in all three t-tests the result is in the rejected
region. That means for ROA, ROE, and NIM for all profitability ratios are significantly different
between two dependent variables. So, we can say that before COVID and during COVID
profitability of the banking industry in Bangladesh is significantly different.
H0: μ1= μ2 (The NIM is equal for two dependent variables)
H1: μ1≠μ2 (The NIM don’t equal for two dependent variables)
From the result we can interpret that, there is a positive correlation between the two groups
because (r = 0.82, p = .00248) that means the return on assets before COVID and after COVID
are positively correlated. From the table we find that in 95% confidence level lower value is
0.39% and the higher value is 0.8906%, so the average difference between during COVID and
after COVID in the case for upper value and the lower value is 0.64%. The value we get here is
0.002580 which is in the rejected region of the null hypothesis at a significance level of 5% in
degrees of freedom 9. So, the alternative hypothesis is accepted (H1: μ1≠μ2). So according to NIM
before COVID19 profit is significantly different from during COVID19 NIM according to the
two-tail t-test.
From the previous three t-test analysis, we see in all three t-tests the result is in the rejected
region. That means for ROA, ROE, and NIM for all profitability ratios are significantly different
between two dependent variables. So, we can say that before COVID and during COVID
profitability of the banking industry in Bangladesh is significantly different.
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15
4.3 Trend Analysis
Here we used trend analysis on investment income, net investment income, Operating profit,
profit before tax, net profit, ROA, ROE with the confirmed Covid-19 case & Covid-19 death
case & tried to find a relation between those variables. The sample collected for this research are
Al-Arafa Islami Bank Limited, Social Islami Bank Limited, First Security Islami Bank Limited,
Islami Bank Bangladesh Limited, NCC Bank Ltd., National Bank Limited, Mercantile Bank
Limited, South East Bank Limited & Bank Asia. Data were presented in quarter form. Jan –
March (1st Quarter), April – June (2nd Quarter), July – September (3rd Quarter) & October -
December (4th Quarter). Data of those variables are the simple averages of all the banks. Data of
confirmed Covid-19 case & Covid-19 death case are also shown in quarter form.
4.3.1 Investment Income
Investment Income refers to the amount of money that the bank collects through investment &
loans. It is the amount is collected as interest income & as profit. Here we present the average
investment income of the above banks in each quarter of 2020 with the confirmed Covid-19 case
& Covid-19 death case.
4.3 Trend Analysis
Here we used trend analysis on investment income, net investment income, Operating profit,
profit before tax, net profit, ROA, ROE with the confirmed Covid-19 case & Covid-19 death
case & tried to find a relation between those variables. The sample collected for this research are
Al-Arafa Islami Bank Limited, Social Islami Bank Limited, First Security Islami Bank Limited,
Islami Bank Bangladesh Limited, NCC Bank Ltd., National Bank Limited, Mercantile Bank
Limited, South East Bank Limited & Bank Asia. Data were presented in quarter form. Jan –
March (1st Quarter), April – June (2nd Quarter), July – September (3rd Quarter) & October -
December (4th Quarter). Data of those variables are the simple averages of all the banks. Data of
confirmed Covid-19 case & Covid-19 death case are also shown in quarter form.
4.3.1 Investment Income
Investment Income refers to the amount of money that the bank collects through investment &
loans. It is the amount is collected as interest income & as profit. Here we present the average
investment income of the above banks in each quarter of 2020 with the confirmed Covid-19 case
& Covid-19 death case.

16
In the above graph, it is represented that average investment income in the 1st quarter was quite
high & both the confirmed Covid-19 case & Covid-19 death case was in a negligible amount.
But as the period goes by both the confirmed Covid-19 case & the Covid-19 death case started to
increase and as a result of this increase in the Covid-19, the average investment income started to
fall. This is clearly shown in the 2nd quarter. In the 3rd quarter, both the confirmed Covid-19 cases
& Covid-19 death case took a massive turn and increased a lot than the previous two quarters
and the effect of it has clearly shown the impact on the investment income. In the 4th quarter, as
the Covid-19 cases started to fall once, again investment income started to rise. This clearly
shows that there is a relationship between investment income with the confirmed Covid-19 case
& Covid-19 death case. And they have an inverse relationship between them.
4.3.2 Net Investment Income
It is the amount of profit that the banks get after paying profits on deposit. It is calculated by
deducting profit paid on deposit from investment income. It is an important variable to consider,
in evaluating banking profitability because it is the gross profit of a bank. Here a graph is shown
to represent the impact of the confirmed Covid-19 case & Covid-19 death case on net investment
income.
In the above graph, it is represented that average investment income in the 1st quarter was quite
high & both the confirmed Covid-19 case & Covid-19 death case was in a negligible amount.
But as the period goes by both the confirmed Covid-19 case & the Covid-19 death case started to
increase and as a result of this increase in the Covid-19, the average investment income started to
fall. This is clearly shown in the 2nd quarter. In the 3rd quarter, both the confirmed Covid-19 cases
& Covid-19 death case took a massive turn and increased a lot than the previous two quarters
and the effect of it has clearly shown the impact on the investment income. In the 4th quarter, as
the Covid-19 cases started to fall once, again investment income started to rise. This clearly
shows that there is a relationship between investment income with the confirmed Covid-19 case
& Covid-19 death case. And they have an inverse relationship between them.
4.3.2 Net Investment Income
It is the amount of profit that the banks get after paying profits on deposit. It is calculated by
deducting profit paid on deposit from investment income. It is an important variable to consider,
in evaluating banking profitability because it is the gross profit of a bank. Here a graph is shown
to represent the impact of the confirmed Covid-19 case & Covid-19 death case on net investment
income.

17
Average net investment income was high in the 1st quarter when there were no covid-19 cases.
When the confirmed Covid-19 case & Covid-19 death case started to increase, net investment
income started to fall. Both in the 2nd & 3rd quarter when Covid-19 cases increased, net
investment income falls. In the fourth quarter when cases started to improve it also improved
bans average net investment income. So-net investment income also showed an inverse
relationship with the confirmed Covid-19 case & Covid-19 death case.
4.3.3 Operating Profit
Operating Profits the income which is generated from basic banking operations. It is calculated
by adding operation income with net investment income and subtracting operation expenses.
Here a graph is shown to represent impact of the confirmed Covid-19 case & Covid-19 death
case on operating income
Average net investment income was high in the 1st quarter when there were no covid-19 cases.
When the confirmed Covid-19 case & Covid-19 death case started to increase, net investment
income started to fall. Both in the 2nd & 3rd quarter when Covid-19 cases increased, net
investment income falls. In the fourth quarter when cases started to improve it also improved
bans average net investment income. So-net investment income also showed an inverse
relationship with the confirmed Covid-19 case & Covid-19 death case.
4.3.3 Operating Profit
Operating Profits the income which is generated from basic banking operations. It is calculated
by adding operation income with net investment income and subtracting operation expenses.
Here a graph is shown to represent impact of the confirmed Covid-19 case & Covid-19 death
case on operating income
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Just like investment income & net investment income the trend line of operating income is also
has shown the same impact. At the 1st quarter the operating income were at high and when the
confirmed Covid-19 case & Covid-19 death case started to increase, the operating income also
shown downfall in the 2nd & 3rd quarter. When in the 4th quarter Covid-19 cases decreases, it
shows that operating income has increased. So, there is clearly a relationship between operating
income & Covid-19 cases. And the relationship is inverse.
4.3.4 Profit before tax
Profit before tax is the amount of money that bank collects before providing tax to the
government. It is calculated by subtracting noninterest expenses from Operating profit. Here we
represent the average profit before tax of the banks in four quarter of 2020 along with the covid-
19 confirmed case and death case.
Just like investment income & net investment income the trend line of operating income is also
has shown the same impact. At the 1st quarter the operating income were at high and when the
confirmed Covid-19 case & Covid-19 death case started to increase, the operating income also
shown downfall in the 2nd & 3rd quarter. When in the 4th quarter Covid-19 cases decreases, it
shows that operating income has increased. So, there is clearly a relationship between operating
income & Covid-19 cases. And the relationship is inverse.
4.3.4 Profit before tax
Profit before tax is the amount of money that bank collects before providing tax to the
government. It is calculated by subtracting noninterest expenses from Operating profit. Here we
represent the average profit before tax of the banks in four quarter of 2020 along with the covid-
19 confirmed case and death case.

19
1 2 3 4
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
Profit Before Tax
Death Case Confirmed case Profit Before Tax
Here we see that in the 2nd & 3rd quarter profit before tax show a decreasing trend with the
increasing trend of confirmed covid-19 cases and death case. In the 4th quarter with the falling
down of covid-19 and death case, once again profit before tax started to increase. So, it clearly
shows a inverses relationship of profit before tax with the confirmed covid-19 cases & Death
cases.
4.3.5 Net profit
Net profit is the amount of money that a bank earns after deducting all operating cost, interest,
and tax expenses over a given period of time from the investment income. It is the actual amount
of profit that a corporation earns from its activities. Here a graph is shown of average net profit
of each of the four quarter in the year 2020 along with the confirmed covid-19 cases & death
cases.
1 2 3 4
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
Profit Before Tax
Death Case Confirmed case Profit Before Tax
Here we see that in the 2nd & 3rd quarter profit before tax show a decreasing trend with the
increasing trend of confirmed covid-19 cases and death case. In the 4th quarter with the falling
down of covid-19 and death case, once again profit before tax started to increase. So, it clearly
shows a inverses relationship of profit before tax with the confirmed covid-19 cases & Death
cases.
4.3.5 Net profit
Net profit is the amount of money that a bank earns after deducting all operating cost, interest,
and tax expenses over a given period of time from the investment income. It is the actual amount
of profit that a corporation earns from its activities. Here a graph is shown of average net profit
of each of the four quarter in the year 2020 along with the confirmed covid-19 cases & death
cases.

20
1 2 3 4
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
Net Profit
Death Case Confirmed case Net Profit
In the above graph, the result is all the same from what we have seen in the previous
profitability’s. The effect of Covid-19 and death cases also have an inverse relationship with net
profit. The average net profit of the banks in the Quarters of year 2020 has a up and down trend.
With the increase of independent variables, net profit shown a downfall in the 2nd & 3rd quarter
and with the decrease of independent variables, net Profit has shown a positive trend in the 1st &
4th quarter. So net profit also has an inverse relationship.
4.3.6 ROE
The return on equity is a measure of the profitability of a business in relation to the equity which
is calculated by dividing net income by shareholders' equity. Return on Equity (ROE) is the
return on net assets of the corporations.
1 2 3 4
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
Net Profit
Death Case Confirmed case Net Profit
In the above graph, the result is all the same from what we have seen in the previous
profitability’s. The effect of Covid-19 and death cases also have an inverse relationship with net
profit. The average net profit of the banks in the Quarters of year 2020 has a up and down trend.
With the increase of independent variables, net profit shown a downfall in the 2nd & 3rd quarter
and with the decrease of independent variables, net Profit has shown a positive trend in the 1st &
4th quarter. So net profit also has an inverse relationship.
4.3.6 ROE
The return on equity is a measure of the profitability of a business in relation to the equity which
is calculated by dividing net income by shareholders' equity. Return on Equity (ROE) is the
return on net assets of the corporations.
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1 2 3 4
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
ROE
Death Case Confirmed case ROE
As the net income of the banks decrease along with the increase of the confirmed covid-19 cases
& death cases, it also has impact on the ROE. ROE were in decreasing trend in 2nd & 3rd
quarter when Covid-19 started to spread. And when the spreading started to slow down in the
last quarter of the year, ROE have seen some positive result.
4.3.7 ROA
It shows how profitable a corporation is in relation with its Total asset. It is calculated by
dividing net income by total asset of the firm. It is an important measure of profitability for the
banks as banks are in a business of providing loans and investment. Here a graph is given where
the average ROA of some banks are given in 4 quarter of 2020 with the confirmed covid-19
cases & death cases of four quarter of 2020 to represent the relationship they possess.
1 2 3 4
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
ROE
Death Case Confirmed case ROE
As the net income of the banks decrease along with the increase of the confirmed covid-19 cases
& death cases, it also has impact on the ROE. ROE were in decreasing trend in 2nd & 3rd
quarter when Covid-19 started to spread. And when the spreading started to slow down in the
last quarter of the year, ROE have seen some positive result.
4.3.7 ROA
It shows how profitable a corporation is in relation with its Total asset. It is calculated by
dividing net income by total asset of the firm. It is an important measure of profitability for the
banks as banks are in a business of providing loans and investment. Here a graph is given where
the average ROA of some banks are given in 4 quarter of 2020 with the confirmed covid-19
cases & death cases of four quarter of 2020 to represent the relationship they possess.

22
1 2 3 4
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
ROA
Death Case Confirmed case ROA
We have seen that in all the other trend analysis, the data shows a negative trend in the 2nd &
3rd quarter. But here in ROA, it is quite the same as 1st quarter despite an increased Covid-19
case and death case. The reason behind this is that due to Covid-19, investment & providing loan
of banks decrease in this quarter. That’s why total assets didn't improve much. That’s why
despite of decreasing net profit ROA didn’t have much impact in 2nd quarter. But the last two
quarters clearly represent a negative relation of ROA with confirmed covid-19 case and death
cases.
Summary of Trend Analysis: Here in the trend analysis, all the profitability have shown a
negative effect on the increase of Covid-19 cases and death cases. ROA, ROE, net profit,
operating profit, net investment income, net income all have shown a downfall in the 2nd & 3rd
quarter when Covid-19 cases and death cases increased. But when in the 4th quarter Covid-19
cases started to fall, profitability takes a positive turn. So it clearly shows that profitability of the
Banking Industry has a negative relation with the covid-19 cases & death cases. In the
conclusion, we can say Covid-19 has an impact on the profitability of the Banking industry.
1 2 3 4
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
45.00%
50.00%
ROA
Death Case Confirmed case ROA
We have seen that in all the other trend analysis, the data shows a negative trend in the 2nd &
3rd quarter. But here in ROA, it is quite the same as 1st quarter despite an increased Covid-19
case and death case. The reason behind this is that due to Covid-19, investment & providing loan
of banks decrease in this quarter. That’s why total assets didn't improve much. That’s why
despite of decreasing net profit ROA didn’t have much impact in 2nd quarter. But the last two
quarters clearly represent a negative relation of ROA with confirmed covid-19 case and death
cases.
Summary of Trend Analysis: Here in the trend analysis, all the profitability have shown a
negative effect on the increase of Covid-19 cases and death cases. ROA, ROE, net profit,
operating profit, net investment income, net income all have shown a downfall in the 2nd & 3rd
quarter when Covid-19 cases and death cases increased. But when in the 4th quarter Covid-19
cases started to fall, profitability takes a positive turn. So it clearly shows that profitability of the
Banking Industry has a negative relation with the covid-19 cases & death cases. In the
conclusion, we can say Covid-19 has an impact on the profitability of the Banking industry.

23
4.4 Regression Analysis
Regression analysis is a reliable method of identifying which variables have an impact on a topic
of interest. The process of performing a regression allows you to confidently determine which
factors matter most, which factors can be ignored, and how these factors influence each other. It
is a set of statistical methods used for the estimation of relationships between a dependent
variable and one or more independent variables. It can be utilized to assess the strength of the
relationship between variables and for modeling the future relationship between them.
Regression is also used for forecasting an effect and trend forecasting.
Here we have conducted a series of regression analyses to determine the strength and character
of the relationship between one dependent variable and a series of independent variables.
Variables for this analysis are taken as follows:
Independent Variables Dependent Variable
Confirmed Covid-19 Case
ROA (Model 1)
ROE (Model 2)
Covid-19 Death Case.
Net Investment Income (Model 3)
Operating Profit (Model 4)
Net profit (Model 5)
By using confirmed Covid-19 case & Covid-19 death case as independent variables a series of
regression analyses have taken place. In the 1st analysis, ROA is taken as a dependent variable. In
the following ROE, Net Profit, Net Investment Income & Operating Profit were the dependent
variables. The formula of regression analysis is,
Y = a + bX1(Confirmed Covid-19 Case) + cX2(Death Case) + ϵ
Here, Y= Dependent Variable, X1= independent variable 1(Confirmed Covid-19 Case), X2=
independent variable 2(Confirmed Death Case)
b & c = Slope
a= Intercept. ϵ = Residual (error)
4.4 Regression Analysis
Regression analysis is a reliable method of identifying which variables have an impact on a topic
of interest. The process of performing a regression allows you to confidently determine which
factors matter most, which factors can be ignored, and how these factors influence each other. It
is a set of statistical methods used for the estimation of relationships between a dependent
variable and one or more independent variables. It can be utilized to assess the strength of the
relationship between variables and for modeling the future relationship between them.
Regression is also used for forecasting an effect and trend forecasting.
Here we have conducted a series of regression analyses to determine the strength and character
of the relationship between one dependent variable and a series of independent variables.
Variables for this analysis are taken as follows:
Independent Variables Dependent Variable
Confirmed Covid-19 Case
ROA (Model 1)
ROE (Model 2)
Covid-19 Death Case.
Net Investment Income (Model 3)
Operating Profit (Model 4)
Net profit (Model 5)
By using confirmed Covid-19 case & Covid-19 death case as independent variables a series of
regression analyses have taken place. In the 1st analysis, ROA is taken as a dependent variable. In
the following ROE, Net Profit, Net Investment Income & Operating Profit were the dependent
variables. The formula of regression analysis is,
Y = a + bX1(Confirmed Covid-19 Case) + cX2(Death Case) + ϵ
Here, Y= Dependent Variable, X1= independent variable 1(Confirmed Covid-19 Case), X2=
independent variable 2(Confirmed Death Case)
b & c = Slope
a= Intercept. ϵ = Residual (error)
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Results from regression analysis are given below:
Particulars ROA ROE Net Profit Net
Investment
Income
Operating
Profit
Intercept 0.001953954***
(101.1712)
0.029987414
(6.7805)
787.3897928
(7.4415)
2573.52873
(3.5748)
3007.414764
(0.7532)
Death Case -0.0000013505*
(-24.4056)
0.00001591
(1.2559)
0.110729319
(0.3652)
0.88496028
(0.4290)
3.920646491
(0.3427)
Confirmed
case
0.0000000179*
(20.9002)
-0.00000029
(-1.4649)
-0.002779778
(-0.5940)
-0.01593526
(-0.5005)
-0.059116746
(-0.3348)
Observations 4 4 4 4 4
Significance F 0.030357817 0.452653658 0.523425138 0.829604796 0.945629299
Adjusted R
Square
0.997235209 0.385313999 0.178078374 -1.064732351 -1.682644313
Note: The symbols ***, **, and * represent significance levels of P value of 0%-0.01%, 0.11%-1%,
and 1%-5%, respectively
Table 2: Result of Regression Analysis
4.4.1 Return on Assets (ROA)
The coefficient of the intercept is 0.001953954 & the t stat is 101.1712. Both the result is quite
satisfactory. The P-value of this regression model is 0.006292295 which is much below 1%. We
know the lower the P-value the better it is. So, P-Value should be as low as possible. At a 95%
confidence level, P-value should be lower than 5%. Here P-value is below 1% which indicates
that we are 99% confident that the analysis is correct & the relationship is significant. The
coefficient of death case and confirmed case are respectively -0.0000013505 & 0.0000000179.
This indicates that if the death case increases by 1% & the other variable remain constant then
ROA will decrease by -0.0000013505%. And if confirmed case increases by 1% & the other
Results from regression analysis are given below:
Particulars ROA ROE Net Profit Net
Investment
Income
Operating
Profit
Intercept 0.001953954***
(101.1712)
0.029987414
(6.7805)
787.3897928
(7.4415)
2573.52873
(3.5748)
3007.414764
(0.7532)
Death Case -0.0000013505*
(-24.4056)
0.00001591
(1.2559)
0.110729319
(0.3652)
0.88496028
(0.4290)
3.920646491
(0.3427)
Confirmed
case
0.0000000179*
(20.9002)
-0.00000029
(-1.4649)
-0.002779778
(-0.5940)
-0.01593526
(-0.5005)
-0.059116746
(-0.3348)
Observations 4 4 4 4 4
Significance F 0.030357817 0.452653658 0.523425138 0.829604796 0.945629299
Adjusted R
Square
0.997235209 0.385313999 0.178078374 -1.064732351 -1.682644313
Note: The symbols ***, **, and * represent significance levels of P value of 0%-0.01%, 0.11%-1%,
and 1%-5%, respectively
Table 2: Result of Regression Analysis
4.4.1 Return on Assets (ROA)
The coefficient of the intercept is 0.001953954 & the t stat is 101.1712. Both the result is quite
satisfactory. The P-value of this regression model is 0.006292295 which is much below 1%. We
know the lower the P-value the better it is. So, P-Value should be as low as possible. At a 95%
confidence level, P-value should be lower than 5%. Here P-value is below 1% which indicates
that we are 99% confident that the analysis is correct & the relationship is significant. The
coefficient of death case and confirmed case are respectively -0.0000013505 & 0.0000000179.
This indicates that if the death case increases by 1% & the other variable remain constant then
ROA will decrease by -0.0000013505%. And if confirmed case increases by 1% & the other

25
variable remain constant then ROA will increase by 0.0000000179%. The relationship of the
confirmed Covid-19 case with ROA is positive. The reason behind it is that confirmed covid-19
cases don’t affect much of the bank’s operations as death cases do. Here the observations are 4
quarters. Significance F of this analysis is 0.030357817. That means at 95% confidence level
null hypothesis (all betas of the independent variable are zero) is rejected, so the alternative
hypothesis (at least on beta is not equal to 0) is accepted. That means this report is at a 95%
confidence level that the independent variables can explain the dependent variable. There is a
relationship between confirmed Covid-19 cases & Covid-19 death cases with ROA of banks. The
adjusted R Square of the analysis is 0.997235209. which indicates the variation of the dependent
variable, 99.72% explained by the variation of the independent variables & this model also
passes the goodness of fit test.
4.4.2 Return on Equity (ROE)
Co efficient of the intercept is 0.029987414 & the t stat is 6.7805. The Co efficient of the
intercept is quite satisfactory. The P value of this regression model is 0.0932173720762114,
which is more than 5%. We know the lower the P-value the better it is. So, P-Value should be as
low as possible. At a 95% confidence level, P-value should be lower than 5%. Here P value is
higher than 5% which indicates that the relationship is insignificant. Coefficient of death case
and confirmed case are respectively 0.0000159 & -0.00000029. Which indicates that if death
case increases by 1% & the other variable remain constant then ROE will increase by 0.0000159
%. And if confirmed case increases by 1% & the other variable remain constant then ROE will
decrease by 0.00000029%. Here the observations are 4 quarters. Significance F of this analysis is
0.452653657554521. That means at 95% confidence level null hypothesis (all betas of the
independent variable are zero) is accepted, so the alternative hypothesis (at least on beta is not
equal to 0) is rejected. That means this report is at a 95% confidence level that the independent
variables cannot explain the dependent variable. So, there is no relationship between confirmed
Covid-19 cases & Covid-19 death cases with ROE of banks. Adjusted R Square of the analysis is
0.385313998907543. which indicates the variation of dependent variable, 38.53% explained by
the variation of the independent variables & this model also doesn’t passes the goodness of fit
test.
variable remain constant then ROA will increase by 0.0000000179%. The relationship of the
confirmed Covid-19 case with ROA is positive. The reason behind it is that confirmed covid-19
cases don’t affect much of the bank’s operations as death cases do. Here the observations are 4
quarters. Significance F of this analysis is 0.030357817. That means at 95% confidence level
null hypothesis (all betas of the independent variable are zero) is rejected, so the alternative
hypothesis (at least on beta is not equal to 0) is accepted. That means this report is at a 95%
confidence level that the independent variables can explain the dependent variable. There is a
relationship between confirmed Covid-19 cases & Covid-19 death cases with ROA of banks. The
adjusted R Square of the analysis is 0.997235209. which indicates the variation of the dependent
variable, 99.72% explained by the variation of the independent variables & this model also
passes the goodness of fit test.
4.4.2 Return on Equity (ROE)
Co efficient of the intercept is 0.029987414 & the t stat is 6.7805. The Co efficient of the
intercept is quite satisfactory. The P value of this regression model is 0.0932173720762114,
which is more than 5%. We know the lower the P-value the better it is. So, P-Value should be as
low as possible. At a 95% confidence level, P-value should be lower than 5%. Here P value is
higher than 5% which indicates that the relationship is insignificant. Coefficient of death case
and confirmed case are respectively 0.0000159 & -0.00000029. Which indicates that if death
case increases by 1% & the other variable remain constant then ROE will increase by 0.0000159
%. And if confirmed case increases by 1% & the other variable remain constant then ROE will
decrease by 0.00000029%. Here the observations are 4 quarters. Significance F of this analysis is
0.452653657554521. That means at 95% confidence level null hypothesis (all betas of the
independent variable are zero) is accepted, so the alternative hypothesis (at least on beta is not
equal to 0) is rejected. That means this report is at a 95% confidence level that the independent
variables cannot explain the dependent variable. So, there is no relationship between confirmed
Covid-19 cases & Covid-19 death cases with ROE of banks. Adjusted R Square of the analysis is
0.385313998907543. which indicates the variation of dependent variable, 38.53% explained by
the variation of the independent variables & this model also doesn’t passes the goodness of fit
test.

26
4.4.3 Net Profit
Co efficient of the intercept is 787.3897928 & the t stat is 7.4415. The Co efficient & the t stat of
the intercept is not satisfactory. The P value of this regression model is 0.08504, which is more
than 5%. We know the lower the P-value the better it is. So, P-Value should be as low as
possible. At a 95% confidence level, P-value should be lower than 5%. Here P value is higher
than 5% which indicates that the relationship is insignificant. Coefficient of death case and
confirmed case are respectively 0.110729 & -0.0027797. Which indicates that if death case
increases by 1% & the other variable remain constant then net profit will increase by 0.110729
%. And if confirmed case increases by 1% & the other variable remain constant then net profit
will decrease by 0.0027797%. Here the observations are 4 quarters. Significance F of this
analysis is 0.523425. That means at 95% confidence level null hypothesis (all betas of the
independent variable are zero) is accepted, so the alternative hypothesis (at least on beta is not
equal to 0) is rejected. That means this report is at a 95% confidence level that the independent
variables cannot explain the dependent variable. So, there is no relationship between confirmed
Covid-19 cases & Covid-19 death cases with net profit of banks. Adjusted R Square of the
analysis is 0.17807837. which indicates the variation of dependent variable, 17.81% explained
by the variation of the independent variables & this model also doesn’t passes the goodness of fit
test.
4.4.4 Net Investment Income
Co efficient of the intercept is 2573.52873 & the t stat is 3.5748. The Co efficient & the t stat of
the intercept is not satisfactory. P value is too high that doesn’t pass the goodness of fitness.
Significance F of this analysis is 0.8296. That means at 95% confidence level null hypothesis (all
betas of the independent variable are zero) is accepted, so the alternative hypothesis (at least on
beta is not equal to 0) is rejected. That means this report is at a 95% confidence level that the
independent variables cannot explain the dependent variable. So, there is no relationship between
confirmed Covid-19 cases & Covid-19 death cases with net investment income of banks.
4.4.3 Net Profit
Co efficient of the intercept is 787.3897928 & the t stat is 7.4415. The Co efficient & the t stat of
the intercept is not satisfactory. The P value of this regression model is 0.08504, which is more
than 5%. We know the lower the P-value the better it is. So, P-Value should be as low as
possible. At a 95% confidence level, P-value should be lower than 5%. Here P value is higher
than 5% which indicates that the relationship is insignificant. Coefficient of death case and
confirmed case are respectively 0.110729 & -0.0027797. Which indicates that if death case
increases by 1% & the other variable remain constant then net profit will increase by 0.110729
%. And if confirmed case increases by 1% & the other variable remain constant then net profit
will decrease by 0.0027797%. Here the observations are 4 quarters. Significance F of this
analysis is 0.523425. That means at 95% confidence level null hypothesis (all betas of the
independent variable are zero) is accepted, so the alternative hypothesis (at least on beta is not
equal to 0) is rejected. That means this report is at a 95% confidence level that the independent
variables cannot explain the dependent variable. So, there is no relationship between confirmed
Covid-19 cases & Covid-19 death cases with net profit of banks. Adjusted R Square of the
analysis is 0.17807837. which indicates the variation of dependent variable, 17.81% explained
by the variation of the independent variables & this model also doesn’t passes the goodness of fit
test.
4.4.4 Net Investment Income
Co efficient of the intercept is 2573.52873 & the t stat is 3.5748. The Co efficient & the t stat of
the intercept is not satisfactory. P value is too high that doesn’t pass the goodness of fitness.
Significance F of this analysis is 0.8296. That means at 95% confidence level null hypothesis (all
betas of the independent variable are zero) is accepted, so the alternative hypothesis (at least on
beta is not equal to 0) is rejected. That means this report is at a 95% confidence level that the
independent variables cannot explain the dependent variable. So, there is no relationship between
confirmed Covid-19 cases & Covid-19 death cases with net investment income of banks.
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4.4.5 Operating Profit
Co efficient of the intercept is 3007.414764 & the t stat is 0.7532. The Co efficient & the t stat of
the intercept is not satisfactory. P value is too high that doesn’t pass the goodness of fitness.
Significance F of this analysis is 0.945629299. That means at 95% confidence level null
hypothesis (all betas of the independent variable are zero) is accepted, so the alternative
hypothesis (at least on beta is not equal to 0) is rejected. That means this report is at a 95%
confidence level that the independent variables cannot explain the dependent variable. So, there
is no relationship between confirmed Covid-19 cases & Covid-19 death cases with operating
profits of the banks.
Summary of Regression: A powerful statistical method that allows examining the relationship
between two or more variables of interest is called regression analysis. Here in the above part of
regression analysis, we have shown the relationship between ROA, ROE, Net Profit, Operating
profit, net investment income with Confirmed covid-19 cases and Covid-19 death cases. Here we
have seen that ROA is the only dependent variable that has a significant relationship with
confirmed Covid-19 cases & death cases. The significance of other dependent variables was at a
rejected level. The adjusted R square of ROA is also significant which is near 100%. That means
confirmed covid-19 cases & Death cases can 100% explain ROA. But other dependent variables
didn’t explain much by the independent variables. From the above regression analysis, we
concluded that there is a significant relationship between ROA with confirmed covid-19 cases &
Covid-19 death cases.
4.5 Summary of Research Analysis
To determine whether there is a significant difference between profit before Covid-19 & profit
during Covid-19, we have conducted some analyses like two-tail T-test, trend analysis &
regression analysis. From our analysis on two tail T-tests, we have found that profit is
significantly different from profit before Covid-19 to profit during Covid-19. In the t-test, we
have done our analysis on ROA, ROE, and NIM. From our analysis in trend analysis, we have
seen that there is an inverse relationship between confirmed Covid-19 cases & Covid-19 death
cases. From that analysis, we have found that in the 2nd & 3rd quarter of the year2020, when
Covid-19 cases started to rise, all the profitability’s & profitability ratios of the bank’s decreased
& when Covid-19 cases fall in the 4th quarter, profitability’s begin to rise again. From that
4.4.5 Operating Profit
Co efficient of the intercept is 3007.414764 & the t stat is 0.7532. The Co efficient & the t stat of
the intercept is not satisfactory. P value is too high that doesn’t pass the goodness of fitness.
Significance F of this analysis is 0.945629299. That means at 95% confidence level null
hypothesis (all betas of the independent variable are zero) is accepted, so the alternative
hypothesis (at least on beta is not equal to 0) is rejected. That means this report is at a 95%
confidence level that the independent variables cannot explain the dependent variable. So, there
is no relationship between confirmed Covid-19 cases & Covid-19 death cases with operating
profits of the banks.
Summary of Regression: A powerful statistical method that allows examining the relationship
between two or more variables of interest is called regression analysis. Here in the above part of
regression analysis, we have shown the relationship between ROA, ROE, Net Profit, Operating
profit, net investment income with Confirmed covid-19 cases and Covid-19 death cases. Here we
have seen that ROA is the only dependent variable that has a significant relationship with
confirmed Covid-19 cases & death cases. The significance of other dependent variables was at a
rejected level. The adjusted R square of ROA is also significant which is near 100%. That means
confirmed covid-19 cases & Death cases can 100% explain ROA. But other dependent variables
didn’t explain much by the independent variables. From the above regression analysis, we
concluded that there is a significant relationship between ROA with confirmed covid-19 cases &
Covid-19 death cases.
4.5 Summary of Research Analysis
To determine whether there is a significant difference between profit before Covid-19 & profit
during Covid-19, we have conducted some analyses like two-tail T-test, trend analysis &
regression analysis. From our analysis on two tail T-tests, we have found that profit is
significantly different from profit before Covid-19 to profit during Covid-19. In the t-test, we
have done our analysis on ROA, ROE, and NIM. From our analysis in trend analysis, we have
seen that there is an inverse relationship between confirmed Covid-19 cases & Covid-19 death
cases. From that analysis, we have found that in the 2nd & 3rd quarter of the year2020, when
Covid-19 cases started to rise, all the profitability’s & profitability ratios of the bank’s decreased
& when Covid-19 cases fall in the 4th quarter, profitability’s begin to rise again. From that

28
analysis, we have concluded that Covid-19 hurts the bank’s profitability. From the regression
analysis, we have found that there is a significant relationship between ROA with confirmed
Covid-19 cases & Covid-19 death cases. And the dependent variable is nearly 100% explained
by the independent variables.
So from that analysis, it has been found there are significant differences between profit before
Covid-19 & profit during Covid-19. Covid-19 have a significant relationship & negative effect
on the bank’s profitability’s.
Chapter Five: Conclusion
The report is prepared to find out the impact of the banking industry under the covid19 situation.
Is there any significant difference in the profitability of the bank at pre and post-condition of
covid 19? The report is prepared based on three analyses that are t-test, trend analysis, and
regression analysis.
Under the t-test the null hypothesis is the return on asset, return on equity and net interest margin
is equal for pre and posts condition o0f covid19. At the 5% significance level there is a
significant difference in return on asset, return on equity, and net interest margin under the two
time period. So the conclusion is all null hypothesis is rejected and the alternative hypothesis is
accepted.
At trend line analysis, the report is sha own graphical presentation of investment income, net
investment income, operating profit, profit before tax, and net profit after tax. In trend line
analysis the financial year is divided into four quarters and shows that the profitability is affected
by the death case and confirmed case of covid 19. When the death case and confirmed case have
increased the profitability of the bank is decreased. There is a negative relationship of
profitability.
analysis, we have concluded that Covid-19 hurts the bank’s profitability. From the regression
analysis, we have found that there is a significant relationship between ROA with confirmed
Covid-19 cases & Covid-19 death cases. And the dependent variable is nearly 100% explained
by the independent variables.
So from that analysis, it has been found there are significant differences between profit before
Covid-19 & profit during Covid-19. Covid-19 have a significant relationship & negative effect
on the bank’s profitability’s.
Chapter Five: Conclusion
The report is prepared to find out the impact of the banking industry under the covid19 situation.
Is there any significant difference in the profitability of the bank at pre and post-condition of
covid 19? The report is prepared based on three analyses that are t-test, trend analysis, and
regression analysis.
Under the t-test the null hypothesis is the return on asset, return on equity and net interest margin
is equal for pre and posts condition o0f covid19. At the 5% significance level there is a
significant difference in return on asset, return on equity, and net interest margin under the two
time period. So the conclusion is all null hypothesis is rejected and the alternative hypothesis is
accepted.
At trend line analysis, the report is sha own graphical presentation of investment income, net
investment income, operating profit, profit before tax, and net profit after tax. In trend line
analysis the financial year is divided into four quarters and shows that the profitability is affected
by the death case and confirmed case of covid 19. When the death case and confirmed case have
increased the profitability of the bank is decreased. There is a negative relationship of
profitability.

29
The profitability of the banking industry is also analyzed by regression analysis. So the impact of
covid19 is affected all over the banking industry profitability. It is mostly affected the return on
assets of the bank. As we know during the covid19 situation the banking industry been closed for
a long period. As the bank is not able to operate the business and the other business that are taken
credit for beginning the business operation, so the credit amount is decreasing and net interest
income is also decreasing. In a nutshell, the profitability of the banking industry is affected
during the covid19 situation but now the banking industry is trying to overcome the problem and
raise its profitability.
The profitability of the banking industry is also analyzed by regression analysis. So the impact of
covid19 is affected all over the banking industry profitability. It is mostly affected the return on
assets of the bank. As we know during the covid19 situation the banking industry been closed for
a long period. As the bank is not able to operate the business and the other business that are taken
credit for beginning the business operation, so the credit amount is decreasing and net interest
income is also decreasing. In a nutshell, the profitability of the banking industry is affected
during the covid19 situation but now the banking industry is trying to overcome the problem and
raise its profitability.
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30
Chapter Six: References
Darjana, D., Wiryono, S. K., & Koesrindartoto, D. P. (2022). The COVID-19 Pandemic Impact
on Banking Sector. Asian Economics Letters, 3(Early View), 29955.
Haque, A., Mohona, N.T., Sultana, S. and Kulsum, U., 2021. THE IMPACT OF COVID-19 ON
THE INSURANCE INDUSTRY OF BANGLADESH. Indian Journal of Finance and
Banking, 6(1),
Barua, B., & Barua, S. (2021). COVID-19 implications for banks: evidence from an emerging
economy. SN Business & Economics, 1(1),
Miah, M. D., Suzuki, Y., & Uddin, S. S. (2021). The impact of COVID-19 on Islamic banks in
Bangladesh: a perspective of Marxian “circuit of merchant’s capital”. Journal of Islamic
Accounting and Business Research.
Marcu, M. R. (2021). The impact of the covid-19 pandemic on the banking sector. Management
Dynamics in the Knowledge Economy, 9(2),
Al Numairy, H. A., Al Essa, S. R., Alshamsi, A. S., Ahli, H. I., Al Zarooni, S. A., & Webb, H.
(2022). The Impact of COVID-19 on Bank Consumers in the UAE: A Dubai-Based Literature
Review. External Events and Crises That Impact Firms and Other Entities,
Collins, C. C., Remigius, I. U., & Amarachi, I. A. U. (2022). Impact of covid-19 pandemic on
corporate performance of banking sector in Nigeria.
X Li, H Feng, S Zhao, DA Cartar- Finance Research Letters, 2021 – Elsevier
Juergensen, J., Guimón, J. and Narula, R., 2020. European SMEs amidst the COVID-19 crisis:
assessing impact and policy responses. Journal of Industrial and Business Economics, 47(3),
Bari, M., 2021. Financial difficulty of Banking management during COVID 19 in
Bangladesh. International Journal of Finance Research, 1(2).
Chapter Six: References
Darjana, D., Wiryono, S. K., & Koesrindartoto, D. P. (2022). The COVID-19 Pandemic Impact
on Banking Sector. Asian Economics Letters, 3(Early View), 29955.
Haque, A., Mohona, N.T., Sultana, S. and Kulsum, U., 2021. THE IMPACT OF COVID-19 ON
THE INSURANCE INDUSTRY OF BANGLADESH. Indian Journal of Finance and
Banking, 6(1),
Barua, B., & Barua, S. (2021). COVID-19 implications for banks: evidence from an emerging
economy. SN Business & Economics, 1(1),
Miah, M. D., Suzuki, Y., & Uddin, S. S. (2021). The impact of COVID-19 on Islamic banks in
Bangladesh: a perspective of Marxian “circuit of merchant’s capital”. Journal of Islamic
Accounting and Business Research.
Marcu, M. R. (2021). The impact of the covid-19 pandemic on the banking sector. Management
Dynamics in the Knowledge Economy, 9(2),
Al Numairy, H. A., Al Essa, S. R., Alshamsi, A. S., Ahli, H. I., Al Zarooni, S. A., & Webb, H.
(2022). The Impact of COVID-19 on Bank Consumers in the UAE: A Dubai-Based Literature
Review. External Events and Crises That Impact Firms and Other Entities,
Collins, C. C., Remigius, I. U., & Amarachi, I. A. U. (2022). Impact of covid-19 pandemic on
corporate performance of banking sector in Nigeria.
X Li, H Feng, S Zhao, DA Cartar- Finance Research Letters, 2021 – Elsevier
Juergensen, J., Guimón, J. and Narula, R., 2020. European SMEs amidst the COVID-19 crisis:
assessing impact and policy responses. Journal of Industrial and Business Economics, 47(3),
Bari, M., 2021. Financial difficulty of Banking management during COVID 19 in
Bangladesh. International Journal of Finance Research, 1(2).

31
Mohania, S. and Mainrai, G., 2020. The COVID-19 Pandemic and its Impact on the Banking
Industry – A Case of National Bank Ltd. Indian Journal of Finance, 14(8-9).
nishat, f., 2020. COVID-19 Impact on NPLs in Corporate Sector - A study on Banking Industry
of Pakistan. SSRN Electronic Journal,
Mohania, S. and Mainrai, G., 2020. The COVID-19 Pandemic and its Impact on the Banking
Industry – A Case of National Bank Ltd. Indian Journal of Finance, 14(8-9).
nishat, f., 2020. COVID-19 Impact on NPLs in Corporate Sector - A study on Banking Industry
of Pakistan. SSRN Electronic Journal,
1 out of 36

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