Analyzing Non-Performing Loans (NPLs) at Agrani Bank Limited

The assignment discusses the challenges of managing non-performing loans (NPLs) in the banking sector, with a focus on Agrani Bank Limited. It examines the causes and consequences of NPLs, including their impact on the bank's profitability and capital base. The study reveals that Agrani Bank Limited has struggled to recover defaulted loans due to various factors, including slow execution of decrees by courts and inadequate risk management practices. Recommendations are provided for improving NPLs management, including diversifying loan portfolios, identifying high-risk borrowers, and enhancing employee training.

A Report on
Non-Performing Loan and Its Impacts on Profitability
of Agrani Bank Limited
Submitted To,
Abu Taleb
Professor
Department of Banking and Insurance
Faculty of Business Studies
University of Dhaka
Submitted By,
Gazi Rahat
ID: 22-124
Department of Banking and Insurance
Faculty of Business Studies
University of Dhaka

Chapter-One: Introduction

1. 00 Introduction
For economic development, a country needs balanced and feasible flow of saving investment
process. Bangladesh now is in developing phase because of rapid growth in RMG sector but this
growth is also hampered by the underdeveloped capital market, raise of Non-performing loans
both on private commercial and state owned commercial banks. The intermediary activity of a
bank is providing loans to the potential investors by checking their credit worthiness.
It is known that profitability of a bank is reduces by the NPL , because banks cannot generate the
appropriate interest income from the classified loans. When a bank has high number of loan
defaults than the bank has to set aside a portion of income as a loss reserve.
At present, the Agrani Bank limited having unfavorable position of NPLs compare to other
private commercial banks in Bangladesh. “Bad Loan” management is the most unsatisfactory
performance in the bank, which consistently accounts for more that 80% of total NPLs. This
scenario is clearly saying that the inefficiency of the credit management to tackle the “flow
problem of bad loans”. Therefore, the first challenge facing Agrani Bank Limited is how to
address the flow problem of bad loans.
In Bangladesh there are nine state run banks and there are accounted for 51.27% of total NPL of
TK.1,16288.31 crore in banking sector. According to the ministry of finance Agrani bank has the
percentage of NPL in first quarter of 2019 is 16.67% and in second quarter it went down to
14.5%.
1.01 Background
Non-performing loans (NPL) or classified loans have a demolishing impact not only on overall
banking sector in Bangladesh but also on the whole economy of the country. Reasons behind the
classified loans are willful defaulters who are unwilling to repay the loans and next reason is
loans go to down grade because of poor business performance due to changes in the political
economy and environmental changes. For this NPL, provisions should be set aside on classified

loans. This report has carry the actual reasons of NPL and the impacts of NPL on the
profitability, deposits and in banking operation. Bank’s NPL rose by 20.23 percent or tk. 15,037
crores in the space of just six months to june 2019, that is higher than cost or expenses for
development budget of last fiscal year. Increasing trend of NPL has the significant effects
because of bad loans on the profitability, total deposits and also on operation of the banking
system. Internationally tolerable level for NPLS is 2%-3% of total loans where in Bangladesh,
NPLs is 20.23 of total loans according to Bangladesh Bank. In the meantime, state-owned banks
are incurring NPLs in the highest rate than the others like PCBs, FCBs, DFIs or Specialized
Banks in Bangladesh.
This study will identify the actual picture of non-performing loans (NPLs) of banking sector in
Bangladesh. This report will also state the reasons and facts of non-performing loans (NPLs).
This study will figure out the way to rescue our banking sector from this bad practice through
proper analysis and documentation. For conducting this research collection of secondary data
relating to financial position and policies from Agrani Bank Limited.
1.02 Objectives of the study
 To know the current scenario of non- performing loan of Agrani bank of Bangladesh.
 To familiar with loan granting supervision and monitoring process of Agrani bank of
Bangladesh.
 To identify the ever increasing trend of non-performing loan of the bank.
 To examine the impacts of non-performing loan of the bank.
 To put forward some suggestion and recommendation to lessen the non-performing loan
burden of the bank.
1.03 Methodology
In this research the used methods are quantitative and qualitative. Here I will try to Measure the
condition of NPL and how the profitability is affected by the defaulter especially on Agrani Bank
Bangladesh Ltd. In this research time series data of Agrani bank limited will be used to show the
NPL condition of the bank. It is a research on trend analysis on the degree and direction of the
NPLs and its profitability.

1.3.01 Research design
A research design is considered as the framework or plan for a study that guides as well as helps
the data collection and analysis of data. The research design may be exploratory descriptive and
experimental for the present study. The descriptive and experimental research design is adopted
for this project. For this study purpose, I have conducted the time series data of Agrani Bank
Bangladesh Ltd. to evaluate the impact of non-performing loans on profitability of the bank.
1.3.02 Data Collection
The data collection has been done from different journals and other reliable secondary sources to
find out the effect of NPLs on profitability and data from Agrani Bank Ltd.
1.3.03 Data Analysis
The data is collected from different authentic sources and analyzed to get the hints and facts
about the presumption that is whether there has impact of non-performing loan on profitability.
There has been taken Secondary data to analyzed the regression and correlation among the
dependent and independent variables. Dependent and independent variables have been taken to
assess the association among them.
1.04 Problem Statement
The mandatory aim of commercial bank is to generate profit by collecting the deposits from the
customers of surplus units of money and lend loans to the people of deficit units of the financial
sectors of a country. The purpose of our Banking sector is also the same. Non-performing loans
are hampering the regular business activities of state owned commercial banks. Our state owned
commercial banks follows rules and regulations from the Bank Company Act 1991 and time-to-
time guidelines of Bangladesh bank. The most dangerous thing for our banking industry is the
NPLs and it is increasing. The Bangladesh Bank is on the way to solve this problem. They are
increasing the provisions for classified loans to reduce aggressive lending. However, the amount
of NPLs is not controlled by the commercial banks. My research proposal is to identify the
causes of non-performing loans, its actual amount, and find out the ways to get round the NPLs.

Chapter-Two: Literature Review

2.00 Literature Review
Nonperforming loans (“NPLs”) means when banks financial asset no longer receive the
installment payment and or interest as scheduled. It known as non-performing because it reduce
loan performance or bank income generate from its loan products. Choudhury and Adhikary
(2002) stated that NPL is a “multiclass” concept but rather not a “uniclass”, which means that
NPLs can be classified into different varieties usually based on the “length of overdue” of the
said loans. In the eve of financial crisis NPLs are worked as a typical byproduct. It is an
occasional accident of the lending process not a basic product of the lending function, one that
has enormous potential to deepen the severity and duration of financial crisis and to complicate
macroeconomic management (Podderand Al Mamun, 2004).
That is because it (NPLs) bring down depositors confidence in the banking sectors, piling up
unproductive economic resources and impeding the resource allocation process. On the other
hand, Lack of diverted uses of funds, proper customer verification, real estate business slow
pace, political instability, weak supervision power of central bank etc. are the root causes of NPL
in Bangladesh. Sustainable banking activities are given priority by the authors which means
future resources will not be compromised to augment the today’soutputs.
The argument is that if NPL remains in the growing trend by taking the path of aggressive banki
ng like buying bad loans, giving the loans to traditional defaulters, massive influence of the inter
nal customers of banks and board of directors in sanctioning poor loans to political people, sustai
nability will be compromised Repetitive restructuring of loans is appeared as good loans in the
financial statement of banks which are actually not good loans.
Such types of activities help to demonstrate superior performance in bank operations, resulting in
increased bank profitability, which encourages investors to have a good relationship with banks a
nd customers, particularly depositors, face problems with withdrawing their deposited fundsbank
s should therefore take appropriate measures to create transparency in the sanctioning of credit, a
nd bangladesh bank should take some steps to ensure that commercial banks and nationalize ban
ks are subject to serious inspection of every loan application before penalizing loans to potential
customers. (alam, shafiqul, mahbubul haq, md., & kader, abul, 2015,

Mohanty (2006)states that financial risk increases in the banking sectors that causes the liquidity
crisis if the risk is not quickly eliminated. These crises not only lower the living of standard but
also can erase much of the successes of economic reform overnight.
Desai and Farmer (2001)argued that the expansion of credit policy during the early liberation
period, aimed at comparatively easier lending, merely increased credit nominally within the econ
omy. Neverthelessit also created a large number of willing history defaulters who subsequently u
ndermined banks ' financial health through the "sick industry syndrome."Nevertheless, in the 199
0s a broadbased financial initiativewas implemented in the name of FSRP, enlisting World Bank
support to restore the country's financial discipline. The banking industry has since implemented
"prudential rules" for the classification and provisioning of loans (Bangladesh Bank, 2014).
Certain rules, legislation, and instruments such as loan ledger book, loan risk analysis manual, pe
rformance planning program, interest rate reform, and the 1990 Money Loan Court Act were also
enacted to encourage safe, efficient and stable banking procedure. Surprisingly, Bangladesh's ba
nking system has yet to free itself from the grip of the NPL fiasco, even after so many steps. The
question thus arises, what are the reasons behind such a large proportion of nonperforming loans
in the economy of Bangladesh?
Is it because of the banks ' ' flexibility in identifying NPLs ' or lack of successful ' recovery strate
gies? Alt-ernatively, is this due to weak legal status of non-performing loans legislation? He
present study focused primarily on the above issue with a view to assisting policymakers in
formulating concrete steps concerning sound management of NPLs in Bangladesh. (Boi.gov.bd,
2015)
Government interest rate policy leads significantly to ineffective loans in a paper published by
Hossian and Hoque. They also reported that loans default in emerging and developed economies
is growing despite the banking remedial steps. Remedial practices for securing repayment of
installments or complete loans given to major corporations or industrial sectors are facing
problems with their loan recovery. Measures to recover loans from customers are like offering
fresh loans to help customers struggle to reinvigorate their company to run profitability,
rescheduling loans, legal proceeding, interest rate as a penalty etc. are failing back to recover
default loan from customers.

Authors also distinguished between the defaulters that are regular defaulters, and those who are n
ot. Typically default happens when lenders are prepared to repay their loans but are unable to. Ha
bitual defaults occur when lenders can repay but don't want to repay their loans. They decided to
view us that interest rate policy has a major effect on the borrowers ' default loan rate. Not only i
s the reluctance of lenders not a prime component of defaults but even the policy of government i
nterest rates will lead to the non-repayment of payments.
That means high interest rates lead to high default rates for the borrowers. From 1995 to 2008, th
e interest rate for industrial loans has nearly doubled (10 to 17 per cent). Since the companies bea
r high interest rates on industrial loans, they often are incapable of repaying their borrowed mone
y when the role of industry in the economy is not good or safe. From the hypothesis testing, auth
ors found that a strong negative association exists between loan default and high market interest r
ate introduced by Bangladesh government. (Ziaul Hoque, Mohammad, Zakir Hossain,
Mohammad, 2008,

Chapter-Three: Overview of Agrani Bank
Limited & Conceptual Framework of NPL

3.01 Overview of Agrani Bank Limited
Agrani Bank Limited, a state owned leading commercial bank with 956 outlets strategically
located in almost all the commercial areas throughout Bangladesh, overseas Exchange Houses
and hundreds of overseas Correspondents, came into being as a Public Limited Company on
May 17, 2007 with a view to take over the business, assets, liabilities, rights and obligations of
the Agrani Bank which emerged as a nationalized commercial bank in 1972 immediately after
the emergence of Bangladesh as an independent state. Agrani Bank Limited started functioning
as a going concern basis through a Vendors Agreement signed between the ministry of finance,
Government of the People's Republic of Bangladesh on behalf of the former Agrani Bank and
the Board of Directors of Agrani Bank Limited on November 15, 2007 with retrospective effect
from 01 July, 2007..
Table 01: Balance Sheet Matrix BDT in Crores
Particulars 2018 2017 2016 2015 2014
Authorized Capital 2500 2500 2500 2500 2500
Paid Up Capital 2072 2072 2072 2072 2072
Reserve Fund 2009 1938 1744 1747 1693
Total Shareholder’s
Equity
4159 4073 3658 4468 3957
Deposits 62193 53035 49405 43998 38392
Advances 39575 31912 26587 24480 23509
Investments 15923 17088 22754 20570 15228
Fixed Assets 1478 1556 1578 1595 1545
Total Assets 78915 67392 62357 56535 49487
Table 02: Credit Quality
Classified Loans 6993 5570 6804 4640 3966
Provision for Unclassified
Loans
322 394 502 459 325
Provision for classified Loans 2965 2750 3057 2245 1930
Provision for Contingent
Liabilities
123 123 84 90 84
Percentage of NPLs to Total
Loans & Advances
17.67% 17.45% 25.59% 18.96% 16.96%

3.02 Conceptual Framework
3.2.01 Non-Performing Loans (NPLs)
Nonperforming loans (NPLs) were widely used by lending institutions as a measure of asset
quality,and are frequently associated with both developed and developing world failures and
financial crises.Banks need a ranking and classification system for loans to facilitate credit
monitoring and control in theirlending portfolios.The loan portfolio of a bank can be divided
into five major groups, namely, in order to pass, special note, substandard, doubtful and loss.
Macroeconomic and structural factors influence NPLs which are demonstrated by empirical
studies. One of the common macro-economic factors are GDP growth, inflation and interest
rates, while size and lending policy are known as micro-economic variables (Greenidge and
Grosvenor, 2010).
“Nonperforming loans (“NPLs”) refer to those financial assets from which banks
no longer receive interest and/or installment payments as scheduled. They are
known as non-performing because the loan ceases to “perform” or generate
income for the bank
--David Woo
3.2.02 Categories of Loans and Advances
According to the master Circular: Loan classification and provisioning (BRPD Circular No. 14)
loans and advances of commercial banks in Bangladesh are grouped into four (4) categories for
the purpose of classification these are (Bangladesh Bank, 2012), -
a) Continuous Loan: A continuous or revolving loan is a loan, where you can withdraw the loan
amount or agreed amount in one go, or in parts. Examples are- Cash Credit, Overdraft, etc.
b) Demand Loan: The loans when the lender demands the money, the borrower must pay. Such
as: Forced LIM, PAD, etc.

c) Fixed Term Loan: Loans that have a fixed amount of time to repay under a specified
repayment plan will be known as fixed term loan.
d) Short-term Agricultural & Micro-Credit: It is an overdraft facility that could be used to
cover planting and working capital expenses for agri-business and related activities.
3.2.03 Basis for Loan Classification
Bangladesh Bank determined the loan classification criteria through the master Circular: Loan
classification, provisioning (BRPD Circular No. 14), loans, and advances of commercial banks in
Bangladesh are to be classified into the following (Bangladesh Bank, 2012), -
Table 3: Loan Supervision and Provisioning for Different types of Loans
Type of Loan Period Overdue Status of Classification Rate of Provision
Continuous Loan
.
3 months Unclassified 1% (except SE&CF)
2% (for SE&CF)
3 to 6 months SMA(special mention
account)
5%
6 to 9 months Sub-standard 20%
9 to 12 months Doubtful 50%
12 months and more Bad/Loss 100%
Demand Loan 3 months Unclassified 1% (except SE&CF)
2% (for SE&CF)
3 to 6 months SMA 5%

6 to 9 months Sub-standard 20%
9 to 12 months Doubtful 50%
12 months and more Bad/Loss 100%
Term Loan 3 months Unclassified
SMA
1% (except SE&CF) &
2% (SE&CF)
5%
6 months and more Sub-standard 20%
9 months and more Doubtful/Bad/Loss 100%
STAC / Micro Credit 12 months Unclassified 5%
12 to 36 months Sub-standard 5%
36 to 60 months Doubtful 5%
More than 60 months Bad/Loss 100%
Source: Banking Regulation & Policy Department, circular no. 14, (Master Circular: Loan
Classification and Provisioning), September 23, 2012, Bangladesh Bank.

3.2.04 Objective Criteria
(1) Past Due/Over Due:
 Any Continuous Loan will be treated as past due if that is not pay before the expiry date
or after the demand by the bank for repayment.
 Any Demand Loan will be treated as past due if that is not pay before the expiry date or
after the demand by the bank for repayment.
 In case of any installment(s) or part of installment(s) of a Fixed Term Loan will be
treated as past due if the amount of unpaid installment(s) is not pay before the expiry
date or after the demand by the bank for repayment
 The Short-term Agricultural and Micro-Credit if not repaid within the fixed expiry date
for repayment will be considered past due/overdue after 6 months of the expiry date.
(2) Except the Special Mention Account (SMA) all unclassified loans will be treated as
Standard.
(3) If a Continuous loan, Demand loan or a Term Loan is overdue for two months or more then it
will be put into SMA and this will be reported to the Credit Information Bureau (CIB) of
Bangladesh Bank .
(4) Any continuous loan will be classified as:
Classification Time periods after overdue
Sub-standard Beyond 3 months to less than 6 months
Doubtful Beyond 6 months to less than 9 months
Bad & loss Beyond 9 months
(6) Any Demand Loan will be classified as:
Classification Time periods (after overdue)
Sub-standard Beyond 3 months to less than 6 months
Doubtful Beyond 6 months to less than 9 months
Bad & loss Beyond 9 months

(7) In case of Fixed Term Loans: -
Classification Time periods (after overdue)
Sub-standard If the amount of installment(s) overdue more
than 03 (three) months
Doubtful If the amount of installment(s) overdue more
than 06 (six) months
Bad & loss If the amount of installment(s) overdue more
than 09 (nine) months
.
(8) The Short-term Agricultural and Micro-Credit , this loan will be considered as irregular, if it
is not paid within specific date,
Classification Time periods (after overdue)
Sub-standard after a period of 12 months
Doubtful after a period of 36 months
Bad & loss after a period of 60 months
If any loan or part of it or accrued interest thereon to any person/organization of his/its own or
related concern remains ''Overdue'' for more than 06(six) months, the borrower availing of such
loan facility will be treated as Defaulted Borrower as per Section 5(GaGa) of the Banking
Companies Act, 1991.
3.2.05 Maintenance of Provision
a) General Provision: Banks will be required to maintain General Provision in the following
way (Bb.org.bd, (2012) :
 Provision of 0.25% against all unclassified loans of SME has to be maintained.
 Provision of 5% on the unclassified loan for Consumer Financing and 2% on Housing
Finance and Loans for Professional.
 Provision of 2% on unclassified amount to Stock Holders, Brokerage House and
Merchant Bank.

 There have to be a 5% provision on outstanding loans remained in Special Mention
Account.
 Provision of 1% for Off Balance Sheet Exposures.
Specific provision: All banks have to maintained amount as provision as below stated rate in
case of demand, continuous and fixed loans
 For Sub-standard Loan, provision will be 20%.
 For Doubtful loan, provision will be 50%.
 For Bad/Loss loan, provision will be 100%.
For Short-term Agricultural and Micro Credit, Provision has to be met according to below
stated rate
 For all categories expect Bad/Loss, provision will be maintained at 5%.
 For Bad/Loss, provision will be maintained at 100%.

Chapter- Four: Analysis of Non-performing
Loan
(Agrani Bank Limited)
4.00 Credit Quality of Agrani Bank Limited

 The main objective of Agrani Bank Limited credit program is helping the businesses,
trades and industries by their financing activity and effective delivery system.
 Agrani Bank Limited offers credit facilities to nearly all business sectors for competitive
reasons.
 The loan portfolio of the Bank encompasses a wide range of credit programs covering
about 150 items.
 Government has designated 15 sectors in which loans are provided. To grow frontier indu
stries at a lower interest rate
 Credit facilities shall be given to individuals, merchants, small and large companies, deal
ers,
producers, corporate bodies and so on.
 Loans shall be issued to rural people for agricultural and other off-farm activities.
 Loan pricing system is customer friendly.
 Prime customers enjoy prime lending rates and other amenities.
 Fast review, review, judgment and disbursement are guaranteed.
 Credit facilities shall be provided in compliance with Bangladesh Bank guidelines
4.01 Principals and guidelines regarding NPL followed By Agrani Bank
Limited
Credit risk may arise when a borrower fail to repay the required payments or the probability that
borrower is unable to meet its obligation as per agreed terms.
Banks are highly prone to credit risk as it hinders the core operations of the bank, i.e. loans to co
mpanies, SMEs, individuals, other banks / FIs or other countries. Credit risk management's main
aim is to reduce the negative effect by taking reasonable mitigations and reducing credit risk exp
osures within acceptable limits.
Table 4: Policies & Guidelines followed By Agrani Bank limited
Classification Types of Loans Classification Period for

SL Status classification
(past due)
a)(i) ABL
follows
Bangladesh
Bank’s
BRPD
Circular
No.14
Dated 23
September
2012 for
classificatio
n
of loans &
advances
1 Continuous
Loan SMA 2
Months
(Overdraft, Cash
credit-Hypo, SS
3M
Cash credit-
pledge etc)
SMA
SS
DF
BL
2 Months
3M
6M
9M
2 Demand Loan
SMA (2M)
(Forced Loan,
PAD, LIM, SS
3Months
FBP, IBP etc.)
SMA
SS
DF
BL
2 Months
3M
6M
9M
3 Fixed Term
Loan SMA
(2M)
(Which are
repayable under
a specific SS
3M Repayment
schedule.)
SMA
SS
DF
BL
2 Months
3M
6M
9M
4 Fixed Term
Loan SMA 2M
(loan amount
below Tk 0.10
crore)
SMA
SS
DF
BL
2 Months
6M
9M
12M
5 Short term
Agriculture &
Micro credit
SMA
SS
DF
BL
-
12M
36M
60M

(ii)
Provisionin
g
depending
on
the group:
Particulars Short
Term
Agricultur
e
& Micro
Credit
Consumer Financing SME
F
BHs
/
MBs
/SDs
All
other
Credi
t
Other
than
HF,L
P
HF LP
Unclassifie
d
Standar
d
5% 5% 2% 2% 0.25% 2% 1%
SMA - 5% 2% 2% 0.25% 2% 1%
Classified SS 5% 20% 20% 20% 20% 20% 20%
DF 5% 50% 50% 50% 50% 50% 50%
BL 100% 100% 100
%
100
%
100% 10% 100%
HF=Housing Finance, LP=Loans to professionals to setup business,
SMEF=Small & Medium Enterprise Financing, BHs= Loans to Brokerage
House, MBs= Loans to Merchant Bank, SDs = Loans to Stock Dealers.
Source: Annual reports of Agrani Bank Limited, web: www.Agranibank-bd.com
Table 1: Current scenario of NPLs of Agrani Bank Limited
Classification wise Loan- Advances &
Provisions
Summary Outstanding Provision kept
Standard 32582 808
SMA 6130.04 95.97
Sub Total= 38712.04 903.97
Classified Outstanding Provision
kept
Substandard 6993 2965

Bad and
doubtful
4842 2024
Sub Total= 11835 4989
Grand Total= 50547.04 5892.97
Source: Annual reports of Agrani Bank Limited, web: www.Agranibank-bd.com
Table 6: Trend of NPL and Provisions
Variable 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
NPLs 23740 21020 21488 53801 35801 39657 46395 68043 55698 69932
Provision 10560 8340 9420 3272 1685 1930 2245 3057 2750 2965
Figure 1: Trend of NPL and Provisions
2010 2011 2012 2013 2014 2015 2016 2017 2018
0
10000
20000
30000
40000
50000
60000
70000
80000
NPL
Provisions
Source: Drown from the data of above table
Variable 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
NPLs 23740 21020 21488 53801 35801 39657 46395 68043 55698 69932
Total 122245 163256 190496 212667 202973 235091 244797 265873 319121 395751

Loan
Percentage 19.42 12.88 11.28 25.30 17.64 16.87 18.95 25.59 17.45 17.67
Table 7: Comparison between Total Loans and NPL
Figure 2: Comparison between Total Loans and NPL
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
NPL
Total loans
Source: Drown from the data of above table
Table 8: Flow of Deposits and Loans
Variable 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Deposits 16628
0
206330 252210 292420 348683 38392
4
439982 494054 530348 621938
Total
loans
12224
5
163256 190496 212667 202973 23509
1
244797 265873 319121 395751

Figure 3: Flow of Deposits and Loans
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
0
100000
200000
300000
400000
500000
600000
700000
Deposits
Total loans
Table 9: Comparative recovery position of classified and overdue loans in 2017 and 2018
2018 2017
Category Cash
recove
ry
Regulariz
ation
Write-
off
Total
recove
ry
Incr
ease/
decr
ease
Cash
recovery
regula
rizatio
n
Write-
off
Total
recove
ry
Increase/
decrease
Classified 319.05 666.55 72.67 1058.2
7
(816.
33)
576.04 1278.8
0
10.76 1874.6
0
921.02
Overdue 224.86 427.12 0.00 651.98 369.3
3
239.87 42.78 0.00 282.65 (94.03)
Total 543.92 1093.67 72.67 1710.2
5
(447) 815.91 1330.5
8
10.76 2157.2
5
826.09
Table 10: Current Treand of NPLs (Agrani Bank Limited) (in millions)
Classified
loans
2013 2014 2015 2016 2017 2018
Substandard 8,608 3,511 6,813 3,749 14,663 17,745
Doubtful 3,338 5,096 7,725 1,759 8,905 10,049
Bad /Loss 26,047 44,607 53,504 40,895 33,443 39,178

Sub Total= 37,993 53,214 68,042 46,403 57,011 66,972
Source: Annual reports of Agrani Bank Limited, web: www.Agranibank-bd.com
Figure 4: NPLs of Agrani Bank Ltd. from 2013-2018
2013 20014 2015 2016 2017 2018
0
10,000
20,000
30,000
40,000
50,000
60,000
Chart Title
Axis Title
Source: Drown from the data of above table
The above figures and charts show that the status of non-performing loans of Agrani Bank
Limited follows an unusual trend from time to time. From figure 3 (NPLs of Agrani Bank
Limited from 2013-2018) it can be seen that the non-performing loans of Agrani Bank Limited is
increasing day by day from 2013 to 2018. In 2013 NPLs of Agrani bank Limited was 37,993
millions. On the other hand, in 2018 it was 66,972 millions. Agrani Bank Limited suffers huge
non-performing loans in 2015 and that was 68,042.

Chapter-Five: Impacts of Non-performing
loan of Agrani Bank Limited
5.01 Variables of Regression Analysis for Agrani Bank Limited
To conduct regression analysis for Agrani Bank Limited, it has to determine the dependent
variable and the independent variable. Here, Net interest Margin (NIM), Return On Assets(ROA)
and Return on Equity(ROE) are the dependent variable and Equity/Assets, NPL Ratio,
Loan/Assets and Macro-economic variables(Unemployment rate and inflation rate) are
independent variables.

This report will try to show the relationship between the dependent variables and independent
variables.
• Dependent Variables
• Net Interest Margin(NIM)
• Return on Assets(ROA)
• Return on Equity(ROE)
• Independent Variables
• Equity/Assets
• NPL Ratio
• Loan/Assets
• Macro-economic variables(Unemployment rate and inflation rate)
5.1.02 Variables Definition
The dependent variable measures the bank’s actual performance. For testing the robustness of the
results we use different variables.
1. Net profit margin=interest margin(IM)/ Total Assets,
2. ROA=Profit before tax/Total Assets
3. ROE=Profit before tax/Total Equity
The independent variables are the following:
 Equity/Total Assets: Higher equity-to-asset ratio is always expected because lower the
external funding higher will be the NIM and profit. When a bank is well-capitalized then
they have less cost burden and less risk for bankruptcy.
 Loans/Assets = Total debtors and equivalent/Total Assets. Banking activity is all about
the work of intermediary between lenders and borrowers. In banking business

profitability depends on the deposits, more the deposits for banks the more will be the
loanable funds available for the customers and the interest income also go up.. However,
if a bank needs to incur higher risk in order to have a higher loan-to-asset ratio, then
profits may decrease.
 NPL ratio: Non-performing loan to total loan, it measures the percentage of total loan
is in trouble, when the percentage is higher, then income from the loanable funds will
reduce.
 Unemployment rate (UR): It is one of the important macro-economical variables,
because it has great impact on the profitability of banking industry as a whole.
 Inflation rate (INF): When in an economy inflation rate is high then their cost of
capital will also high. So it also has some impacts on profitability.
5.1.03 Variable Calculation
 Profitability Ratios
 Return on Assets (ROA)
The Return on Assets Ratio indicates the dollars in income earned by the firm on its assets. It is
important to remember that these ratios are based on accounting book values and not on market
values.
Table 11: Return on Assets (ROA): Net Income after tax/ Total Assets
Return on
Assets (ROA)
Particulars (Figure in Millions) Result(%) Year
=1986/494870 .40 2014
=653/565351 .12 2015
= (6970)/ 623567 (1.12) 2016
= 6759/673922 1.00 2017

=1035/789153 .13 2018
Source: Annual reports of Agrani Bank Limited, web: www.Agranibank-bd.com
Figure 5: Return on Assets (ROA) of Agrani Bank Limited for 2014-2018
2014 2015 2016 2017 2018
0.004000000000
00001 0.001100000000
00001
-
0.011100000000
0001
0.01
0.0013
ROA
Source: Drawn from the above data
Agrani Bank’s return on assets was negative (-0.0111) in 2016 and increased in 2017. This
sudden huge change from 2015 to 2016 indicates inefficiency in the management and required
more supervision. But the supervisory body did not follow the banking laws for banking
functions. Therefore the results become untouched. However, is has become positive (0.01) in
2017. But Agrani bank had very low return on assets all over the years.
 Return on Equity (ROE)
Return on Equity Ratio indicates the dollars of income earned by the firm on its shareholders'
equity.
Table 12: Return on Equity (ROE): Net income after Tax/ Shareholders’ equity
Return on Particulars (Figure in Millions) Result(% Year

Equity (ROE) )
19866/39566= 5.02 2014
653/44675= 1.46 2015
(6970)/36576= (19.06) 2016
6759/40734= 16.59 2017
1035/42586= 2.49 2018
Source: Annual reports of Agrani Bank Limited, web: www.Agranibank-bd.com
Figure 6: Return on Equity (ROE) of Agrani Bank Limited for 2014-2018
2014 2015 2016 2017 2018
0.05
0.014
-0.19
0.16
0.024
ROE
Source: Drawn from the above data
The above figures shows that the return on equity of Agrani bank was positive (though very low)
(0.014) in 2015. But it has become negative (significantly low) in 2016. However, the bank has
recovered from that bad situation in 2017 but again fall in 2018.
5.1.04 Data Set
Table 13: Dependent & Independent Variables (in percentage)
Dependent Variables Independent Variables
Variables NIM ROE ROA Equity/ NPL Loan/ Unemploymen Inflation

Year assets ratio Assets t
rate
rate
2009 1.91 12.09 .52 5.40 19.42 57.71 5.00 4.91
2010 6.25 22.38 1.33 5.94 12.88 61.64 3.38 9.37
2011 3.83 9.54 .72 7.44 11.07 55.64 3.72 11.46
2012 1.61 (259.94) (4.92) 2.89 25.30 56.15 4.05 6.23
2013 3.83 25.39 2.04 8.02 17.93 45.68 4.43 7.54
2014 3.90 5.02 .40 8.80 16.96 47.50 4.41 7.01
2015 3.34 1.46 .12 7.92 18.96 43.30 4.42 6.16
2016 3.24 (19.06) (1.12) 5.86 25.59 42.63 4.35 5.68
2017 .64 16.59 1.00 6.04 17.45 47.35 4.37 5.61
2018 1.13 2.49 .13 5.27 17.67 50.15 4.31 5.61
5.1.05 Regression Analysis
Regression analysis is a statistical method to estimate the relationships among variables. To
analyze several variables it uses many techniques. These techniques help to know the
relationship among dependent variable and one or more independent variables. Regression
analysis is widely used for prediction and forecasting, where its use has substantial overlap with
the field of machine learning. Regression analysis is also used to understand which among the
independent variables are related to the dependent variable, and to explore the forms of these
relationships. In restricted circumstances, regression analysis can be used to infer causal
relationships between the independent and dependent variables.
5.06 Constant Effective Model
Linear Regression Equation,
Y= b0+b1X1+b2X2+b3X3+b4X4+ b5X5
Where,
Y= Net Interest Margin (Dependent Variable)
Y= Return On Assets (Dependent Variable)

Y= Return On Equity (Dependent Variable)
b= the estimated regression coefficient that quantifies the association
between the potential confounder and the outcome.
X1= Equity-to-Assets Ratio (Independent Variable)
X2= Non-Performing Loan Ratio (Independent Variable)
X3= Loan-to- Assets Ratio (Independent Variable)
X4= Unemployment Rate (Independent Variable)
X5= Inflation Rate (Independent Variable)
5.1.07 Empirical Result
The core assumption in this model is that the coefficients are constant across time period and
taken from individual bank. The assumption is given as follows:
 (2009-2018) is the period which used in the study of Agrani Bank Limited”. The Fixed
Effect Model thus assumes that during this period of time the coefficients of the model
remain unchanged.
 Net interest Margin (NIM), Return On Assets(ROA) and Return on Equity(ROE),
Equity/Assets, NPL Ratio, Loan/Assets and Macro-economic variables(Unemployment
rate and inflation rate) these determinants of Agrani Bank used in our model and all the
variables performance are affected by economic ups and downs.
Table 2: Constant Effect Model Estimates
a. Dependent Variable: Net interest Margin (NIM), Return On Assets(ROA) and Return on
Equity(ROE)
b. Independent Variables: Equity/Assets, NPL Ratio, Loan/Assets and Macro-economic
variables(Unemployment rate and inflation rate)

Model Summary
1. Dependent Variable : Net Interest Margin
Model R R Square Adjusted R Square Std. Error of the Estimate
1 0.9398 0.8832 .7371 .8562
a. Predictors: (Constant), Equity/Assets, NPL Ratio, Loan/Assets and Macro-economic
variables(Unemployment rate and inflation rate)
In the model summery, R represents the coefficient of correlation where R Square for coefficient
of determination. R measures the capacity of the linear relationship between two variables. On
the other hand, coefficient of determination predicts the future results or hypotheses testing, on
the basis of other related information. R2 replicates by the model how well the observed results
are.
Here, R=0.9398 which says the positive of direct relationship between Net interest Margin
(NIM) and Equity/Assets, NPL Ratio, Loan/Assets and Macro-economic
variables(Unemployment rate and inflation rate). Net Interest Margin has some impacts when
independent variables increases/decreases. On the other hand, R square=0.8832 which also says
that there is a solid relationship between the dependent variable (NIM) with the independent
variables (Equity/Assets, NPL Ratio, Loan/Assets, Unemployment rate and inflation rate)
Table 14: ANOVA
Particulars SS Df MS F
Significanc
e
1 Regression 22.1674 5 4.4334 6.0473 0.05289
Residual 2.9326 4 0.7331

Total 25.0996 9
a. Dependent Variable: Net Interest Margin
b. Predictors: (Constant): Equity/Assets, NPL Ratio, Loan/Assets, Unemployment rate and
inflation rate.
Table 15: Statistical Result
Particulars Coefficients Standard
Error
t Stat P-
value
1 Equity-to-Assets Ratio 1.5768 0.4168 3.7828 0.0194
2 NPL Ratio 0.3618 0.1333 2.7138 0.0533
3 Loan-to-Assets 0.2659 0.0908 2.9265 0.0430
4 Unemployment Rate -3.5327 1.3519 -2.6131 0.0592
5 Inflation Rate -0.2539 0.3612 -0.7029 0.5208
a. Dependent Variables : Net Interest Margin
In this report, time series data were used and the Table shows that some of the independent
variables are statistically significant.
P-value of this table saying that Equity/Assets, NPL Ratio, Loan/Assets and Unemployment rate
are statistically significant because the value is less than 10%. And inflation rate is not
statistically significant.
Model Summary
2. Dependent Variable : Return On Equity
Model R R Square Adjusted R Square Std. Error of the Estimate
1 0.85
77 0.7357 .4053 66.1549

a. Predictors: (Constant), Equity/Assets, NPL Ratio, Loan/Assets and Macro-economic
variables(Unemployment rate and inflation rate)
Here, R=0. 8577 which says the positive of direct relationship between Return On Equity(ROA)
and Equity/Assets, NPL Ratio, Loan/Assets and Macro-economic variables(Unemployment rate
and inflation rate). On the other hand, R square=0.7357 which says about relationship between
the dependent variable with the independent variables. Here, Std. Error of the Estimate is quite
high.
Table 16: ANOVA
Particulars SS Df MS F
Significanc
e
1 Regression 248730.53 5 9746.109 2.2269 0.2290
Residual 17505.93 4 4376.482
Total 66236.47 9
a. Dependent Variable: Return On Equity
b. Predictors: (Constant): Equity/Assets, NPL Ratio, Loan/Assets, Unemployment rate and
inflation rate.
Table 17: Statistical Result
Particulars Coefficients Standard
Error
t Stat P-value
1 Equity-to-Assets
Ratio 15.8472 32.2055 0.4921 0.6485

2 NPL Ratio -16.4964 10.3009 -1.6015 0.1845
3 Loan-to-Assets -2.4895 7.0197 -0.3547 0.7408
4 Unemployment
Rate 12.8008 104.4516 0.1226 0.9083
5 Inflation Rate -18.9806 27.9089 -
0.6800
0.5338
b. Dependent Variables : Return On Equity
Here, all the results are statistically insignificant. It happens because of lack of data.
Model Summary
3. Dependent Variable : Return On Assets (ROA)
Model R R Square Adjusted R Square Std. Error of the Estimate
1 0.88
60 0.7850 .5162 1.3392
a. Predictors: (Constant), Equity/Assets, NPL Ratio, Loan/Assets and Macro-economic
variables(Unemployment rate and inflation rate)
Here, R=0. 8860 which says the positive of direct relationship between Return On Assets (ROA)
and Equity/Assets, NPL Ratio, Loan/Assets and Macro-economic variables(Unemployment rate
and inflation rate). On the other hand, R square=0.7850which says about relationship between
the Return On Assets (ROA) with the independent variables (Equity/Assets, NPL Ratio,
Loan/Assets, Unemployment rate and inflation rate)
Table 18: ANOVA
Particulars SS Df MS F
Significanc
e
1 Regression 26.1921 5 5.2384 2.9206 0.1605

Residual 7.1744 4 1.7936
Total 33.36656
9
a. Dependent Variable: Return On Assets (ROA)
b. Predictors: (Constant): Equity/Assets, NPL Ratio, Loan/Assets, Unemployment rate and
inflation rate.
Table 19: Statistical Result
Particulars Coefficients Standard
Error
t Stat P-
value
1 Equity-to-Assets Ratio 0.342314 0.651976 0.525041 0.62731
2 NPL Ratio -0.38385 0.208534 -1.8407 0.139485
3 Loan-to-Assets -0.03485 0.142109 -0.24522 0.818352
4 Unemployment Rate 0.444222 2.114541 0.21008 0.843872
5 Inflation Rate -0.34207 0.564993 -0.60544 0.577559
a. Dependent Variables : Return On Assets (ROA)
Here, the result is statistically insignificant, because the p-value is more than 10%. But here
the NPL ratio is very close to 10%.
5.02 Measuring Default Probability
 Altman Z-score : 1.2X1+1.4X2+3.3X3+0.6X4+1.0X5

X1= Working Capital / Total Assets
X2= Retained Earnings / Total Assets
X3= Earnings before Amortization and Tax(EBAT) / Total Assets
X4= Market value of Equity /Total Liabilities
X5= Interest Income/ Total Assets
 Calculation of Z-score
X1= Working Capital / Total Assets
Working Capital= Total Current Assets – Total Current Liabilities
=718431-645456
=72975
T1= 72975/ 789153 =0.0925
X2= Retained Earnings / Total Assets
= (683) / 789153
X2 = (0.00086)
X3= Earnings before Amortization and Tax(EBAT) / Total Assets
= 8321 / 789153
X3= 0.0105
X4= Market value of Equity /Total Liabilities
=41586 / 32315
X4 =1.2869
X5= Interest Income & Revenue/Total Assets
=32315/789153
=0.0409

 Altman Z-score : 1.2X1+1.4X2+3.3X3+0.6X4+1.0X5
= 1.2*0.0925+ 1.4*(0.00086) + 3.3*0.0105+ 0.6*1.2869+1.0*0.0409
= 0.9598
With a Z-score less than 1.81, then the company is in high risk region.

Chapter-Six: Findings, Recommendations
& Conclusion
6.00 Findings
6.01 Regression Analysis
The above discussion on NPLs in Bangladesh reveals that Bangladesh's banking sector has yet to escape
its NPL mess. While significant improvement have recently been noted regarding the implementation of
the loan classification and provisioning system from Bangladesh bank. We are following the international
standard in a large extent, but we are also far behind with regard to managing the NPLs.

In regression analysis the dependent variables are NIM(net interest margin), ROA(return on assets),
ROE(return on equity). These three determinants are the key indicator of profitability and the topic of our
study is NPL and its impacts on profitability. In this study we take some factors that have crucial impacts
on the profitability indicators those are loan to assets ratio, equity to assets ratio, npl ratio. And there is
some macro-economic variables which have some direct impacts on profitability variables are
Unemployment rate and inflation rate.
In the regression analysis the variables are in percentage form. Some the result of regression analysis is
significant and some of them are insignificant. This happens because of lack of data although we know
that the independent variables we selected in the study all have impacts on the profitability indicators.
For dependent variable NIM the ANOVA table p-value result is 0.0528, for ROE the result is .2290 and
for ROA that is .1605. P-value for Dependent variable NIM is significant
6.02 Z- score (Default Probability).
Z-score result shows the result of default probability for banks. This report tries the show the condition of
Agrani bank limited. They are in very bad position. The result of Z- score is 0.9598, which is below
1.81. An organization’s satisfactory position is if their Altman Z-score is more than 1.81. So ABL should
improve their performance to go to the safe zone.
This report shows that the percentage of the bad loans is very high, every year this percentage is going
higher compare to the private commercial banks. And their NPL to loan ratio is also very high.
6.03 Recommendation
 Strict rules and regulations have to be followed in due diligence for sanctioning loans.
Keeping in mind "prevention is better than cure."Agrani Bank Limited should maintain
high collateral because their default probability is very high. So, if a borrower fails to pay
the required amount then bank can sell the collateral to back the loan.

 Valuing the property properly is must, because at the end of day any problem arises
regarding the loan the only way to take back the loan amount by selling the collateral.
The security or collateral received have to be valued by proper agency
 To recover the potential NPLs bank should take action plans. The management of Agrani
Bank Limited should take step to collect the NPLs.
 Loan portfolio should be largely diversified to reduce the concentration risk. The main
reasons for increasing NPL amount every year is that bank’s don’t maintain the single
borrower exposure limits.
 Identification of highly risk sensitive borrowers in the credit portfolio. ABL should take
information about the clients before giving loans. It could go Bangladesh Bank to collect
the information and verify the financial statement carefully from reliable sources(CIB) to
identify the risky borrowers.
 Identification of geographical area-wise risk sensitivity. ABL should identify the clients
according area wise that is mean in Bangladesh, there is some places where growth rate is
low or rate of repay rate is low.
 Evaluate every customer’s character and sincerity of purpose
 Evaluate the customer’s credit reports and financial records properly.
 Customer services should be complied with the loan agreement.
 Trouble loans should be reviewed frequently.
 If the Economy or industry experiences problems then loan review schedule should
accelerate.
 Bank should careful about the warning signs of customer, like change in accounting
methods, adverse change in capital structure and unexpected change in price of stock.
 ABL should give their employees the proper training to recover the default loan.
 A robust risk management culture, with a ‘well articulated’ risk management policy can
help the institutions to avoid such loan default.
 Government should come forward to reduce the corruption in ABL, and the loans should
be provided to them who are eligible for loans nor the politically powerful people.
 They have to carefully manage their business operations because their Z-score showing
that they are not in a safe zone.

6.03 Conclusion
Banking sector of Bangladesh is characterized by low profitability and inadequate capital base
because lacking of adequate controlling and there are many banks in Bangladesh. Banks revenue
comes from spread (Lending rate – borrowing rate).However, there is huge competition among
banks. The crux of the problem lies in the accumulation of high percentage of non-performing
loans over a long period. The problem is most severe for SCBs, DFIs, PCBs and FCBs.