Improving the Management of Non-Performing Loans in Joint Stock Commercial Banks - The Case of the Bank for Investment and Development of Vietnam (BIDV)– Quang Trung Branch

 

MASTER’S THESIS
Improving the Management of Non-Performing Loans in Joint
Stock Commercial Banks - The Case of the Bank for Investment
and Development of Vietnam (BIDV)– Quang Trung Branch

Author:

Thanh, Nguyen Dinh

Student ID:

360685

Supervisor:

Pr. Dr. Rainer Stachuletz

Date:

15th March, 2014

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Acknowledgement
My most humble and sincere thanks to:
First and foremost, my supervisor, Professor Stachuletz Rainer for suggesting the topic of this
research and encouraging me to pursue it. I am grateful for his invaluable advice and
comments as well as for his dedication and constant support throughout the duration of this

project.
Mr. Le Quang Thanh, director of BIDV Quang Trung, and other Deputy Directos and
managers, as well as members of the staff at BIDV Quang Trung, for providing me with
insights, statistics, among other supporting documents for my research.
My wife and family for their love, patience and support throughout the writing process and
the duration of the MBA course.


TABLE OF CONTENT
LIST OF ABBREVIATIONS...................................................................................................i
LIST OF TABLES INDEX .....................................................................................................ii
EXCUTIVE SUMARY............................................................................................................iii
INTRODUCTION.....................................................................................................................1
1.1. Problem statement......................................................................................................... 1
1.2. Research objectives ....................................................................................................... 1
1.3. Research questions ........................................................................................................ 2
1.4. Research methodology .................................................................................................. 2
1.4.1. Methodology ............................................................................................................. 2
1.4.2. Data collection ......................................................................................................... 2
1.4.3. Selection ................................................................................................................... 2
1.4.4. Interview ................................................................................................................... 2
1.4.5. Methods of conducting interviews ............................................................................ 3
1.5. Research scope ............................................................................................................... 3
1.6. Research structure......................................................................................................... 3
I.1. CONCEPT ...................................................................................................................... 4
I.1.1. Definition of credit risk measured..........................................................................4
I.1.2. Indicators of credit risk .......................................................................................... 4
I.2. NPL IN COMMERCIAL BANK ................................................................................. 5
I.2.1. Definition of overdue loan ...................................................................................... 5
I.2.2. Definition of NPL .................................................................................................... 5

I.2.3. Classifying loans using quantitative and qualitative measures .......................... 5
I.2.4. The impact of NPL on the operation of commercial banks ................................ 6
I.3. THE THEORY OF NPL MANAGEMENT IN COMMERCIAL BANK ................ 7
I.3.1. Definition ................................................................................................................. 7
I.3.2. The objective of NPL management ....................................................................... 7
I.3.3. Basel principles on managing NPL ....................................................................... 7
CHAPTER II: CURRENT STATUS OF NPL MANAGEMENT AT BIDV QT...............9
II.1. INTRODUCTION TO BIDV QT ............................................................................... 9
II.1.1. Overview................................................................................................................. 9
II.1.2. BIDV QT’s organization structure ...................................................................... 9
II.1.3. BIDV QT’s activities from 2010-2013 ............................................................... 11


II.2. CURRENT STATUS OF NPL AT BIDV QT 2010-2013 ....................................... 13
II.2.1. NPL status and loan classification ..................................................................... 13
II.2.2. NPL structure ...................................................................................................... 15
II.2.3. NPL by industries ................................................................................................ 17
II.3. NPL MANAGEMENT AT BIDV QT DURING 2010 – 2013 ................................ 19
II.3.1. Mechanisms for credit management at BIDV QT ........................................... 19
II.3.2. The process of managing and handling NPL at BIDV QT.............................. 23
II.3.2.1. Establishment of loan handling at BIDV QT............................................... 23
II.3.2.2. Risk handling process at BIDV QT .............................................................. 24
II.3.3. The application of the measures......................................................................... 25
II.4 THE REASONS FOR THE INCREASE OF NPL DURING 2010-2013 ............... 26
II.4.1. The reasons from macroeconomic environment .............................................. 26
II.4.2. The reasons from the borrowers ........................................................................ 27
II.4.3. The reasons from the bank ................................................................................. 28
CHAPTER III: RECOMMENDATION TO IMPROVE THE MANAGEMENT OF
NPL AT BIDV QT..................................................................................................................31
III.1. MANAGEMENT’S PROSPECT ON THE FUTURE OF BIDV QT .................. 31

III.1.1. The objective of BIDV QT in coming years .................................................... 31
III.1.2. The future of managing NPL at BIDV QT...................................................... 31
III. 2. RECOMMENDATION TO IMPROVE THE MANAGEMENT OF NPL AT
BIDV QT ............................................................................................................................. 32
III.2.1. Building orientation for credit operations....................................................... 32
III.2.2. Enhance the quality of credit evaluation before granting credit, inspection
during and after granting the loan................................................................................ 32
III.2.3. Improving the structure of credit operations and credit risk management. 33
III.2.4. Devising a reward and discipline system for individuals and groups ........... 33
III.2.5. Training, developing and standardizing staff capacity related to credit
operations ........................................................................................................................ 34
III.2.6. Developing an effective information system .................................................... 35
III.2.7. Flexibility in handling NPL............................................................................... 35
III.2.7.1. Improving debt collection practices............................................................. 35
III.2.7.2.Debt restructuring......................................................................................... 35
III.2.7.3. Effective use of allowance to handle NPL .................................................. 36
III.2.7.4. Improving handling of collaterals............................................................... 36


III.2.7.5. Selling of NPLs ............................................................................................ 36
III.2.8. Recommendations for government’s agencies ................................................ 36
CONCLUSION OF CHAPTER III.......................................................................................37
GENERAL CONCLUSIONS.................................................................................................38
REFERENCES..........................................................................................................................v
APPENDIX 1 - LIST OF INTERVIEWEES.......................................................................41
APPENDIX 2 – LIST OF QUESTIONNAIRE FOR THE IN-DEPTH INTERVIEW...42


LIST OF ABBREVIATIONS
Agribank

Vietnam Bank for Agriculture and Rural Development

BIDV

Joint Stock Bank for Investment and Development of Viet Nam

BIDV QT

Joint Stock Bank for Investment and Development of Vietnam – Quang Trung
Branch (BIDV Quang Trung)

BOD

Board of Director

BOM

Board of Manager

CEO

Chief Executive Officer

CIC

Credit Information Center

DGD

Deputy General Director

FED

Federal Reserve

GD

General Director

IAS

International Accounting Standards

IPO

Initial public offering

LGD

Loss given default

NPL (NPLs) Non-performing loan (Non-performing loans)
SBV

State Bank of Vietnam

SWIFT

Society for Worldwide Interbank Financial Telecommunication

UN

United Nations

VCB

Joint Stock Bank for Foreign Trade of Vietnam

Vietinbank

Vietnam Joint Stock Commercial Bank for Industry and Trade

VND

Vietnam Dong

VP

Vice President


LIST OF TABLES INDEX
Figure 2.0: BIDV QT’s organization
Table 2.1: Fund mobilization of BIDV QT from 2010 to 2013
Figure 2.2: Deposits from Customers and Total Asset of BIDV QT from 2010 to 2013
Table 2.3: NPL rate of BIDV against other banks
Table 2.4: 10 branches with the highest amount of NPL and NPL ratio as of 12/31/2013
Table 2.5: Financial result of BIDV QT from 2010 to 12/31/2013
Table 2.6: BIDV QT’s NPL from 2010 to 2013

Figure 2.7: NPL rate curve of BIDV QT from 2010 to 2013
Table 2.8: Loan classification of BIDV QT from 2010 to 2013
Table 2.9: Loan classification by time to maturity of BIDV QT from 2010 to 2013
Table 2.10: NPL classification by time to maturity of BIDV QT from 2010 to 2013
Table 2.11: Loan classification by business structure 2010 to 2013
Table 2.12: BIDV QT’s NPL classification by business structure 2010 to 2013
Table 2.13: BIDV QT’s loan classification by industries 2010 to 2013
Figure 2.14: System of documents governing credit activities at BIDV
Figure 2.15: Credit authorization at BIDV
Figure 2.16: Credit granting process at BIDV
Table 2.17: Proportion in using handling measures of BIDV QT from 2011 to 2013
Figure 2.18: Proportion in using handling measures of BIDV QT from 2011 to 2013


EXECUTIVE SUMMARY
For the last few decades BIDV has consistently remained one of the largest commercial banks
in Vietnam – placing itself among the key players in funding and supplying banking services
and also serving as an important intermediary for the State Bank’s fiscal and monetary
policies. Since its inception in April 2005, BIDV – Quang Trung Branch (hereby known as
BIDV QT for short) has become one of the largest and the most effective branches in the
BIDV system.
In the wake of the global economic downturn at the end of 2012, however, the banking sector
was hit hard since most if not all clients were affected to varying degrees. As businesses
downsized to stay alive and many individuals going bankrupt, problems started arising for
even the most bullet-proof of financial institutions, namely BIDV. Non-performing loans
(NPLs) skyrocketed, which had a dual effect: banks’ profits started to go down from writing
off bad debts and lending came to a halt, thus disrupting the flow of capital in the whole
economy. Owing to these factors, BIDV QT has been facing many challenges as its market
share shrinks, loyal customers either leave or go out of business. To make matters worse,
BIDV QT’s credit rating has been downgraded due to the sheer amount of NPL it carries.

As someone who is directly involved at BIDV QT’s operations, I decided on the topic of
“Improving the Management of Non-performing Loans in Joint Stock Commercial Banks –
The Case of the Bank for Investment and Development of Vietnam (BIDV) – Quang Trung
Branch” for the final project.


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INTRODUCTION
1.1. Problem statement
In the banking sector, credit activities account for most of the bank’s total income. However,
these activities are inherently risky - especially emerging economies like Vietnam’s. Because
of many factors, namely a lack of transparency in the information system, underdeveloped
risk management processes, and low professionalism among bank officers – the need for a
working model of credit risk management is more urgent than ever.
P. Volker, former chairman of FED, once said: "If banks do not have NPLs, it is not
business." For all commercial banks, credit risk is a fact of life. Even the world’s leading
banking institutions cannot escape from NPLs, simply because there are many factors beyond
human control. What separates an effective risk management model from an ineffective one
is how much controllable risk it can reduce or eliminate altogether.
The biggest challenges commercial banks in Vietnam now face are a weak financial position
and an extremely high rate of NPLs per total outstanding loans. The problem here is not only
to collect NPLs from previous years quickly but also to prevent NPLs from increasing. Only
then can Vietnam’s commercial banks get back on their feet financially and remain
competitive.
Take an example from BIDV Quang Trung: from the year 2009 to 2012, our cumulative
credit growth rate was 35.09% (from 2,524 billion to 3,430 billion VND). At the same time,
our NPL ratio shot more than 3-fold, from 1.05% to 3.20%, 1.14 times maximum ratio of
2.8% set by BIDV Headquarter. Our credit activities became much less efficient amid a surge

in credit risk and liquidity risk. The aftermath was not just financial – our credit rating was
demoted and our brand name suffered.
Therefore, one of our top priorities at BIDV Quang Trung is to standardize risk management
practices in the shortest time frame. Managing NPLs in compliance with current international
standards will enable commercial banks to provide better products and services at a lower
price by allowing a quicker capital turnover rate and of course, a smaller allowance for bad
debts, which cuts directly into net profit.
1.2. Research objectives
The core objective of the final project is to find answers for the following research questions:
1. Is management NPL a major factor causing this increase?
2. What can management at BIDV QT do to deal with the current NPL and reduce future
NPL?
In an effort to clarify the matters, I used both primary and secondary data from in-depth
interview, reports system from internal credit rating and other sources. The research
methodology applied during the research is the combination of quantitative and qualitative
methods.
After thorough analysis to answer these questions, I have some recommendations to improve
the managing NPL at BIDV QT, helping the bank reduce the NPL rate in the coming years.
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1.3. Research questions
The above content can be further broken down into the following problems that need an
answer to:
1. What are the current policies on managing credit & NPL at BIDV Quang Trung?
2. What caused the surge in NPLs at BIDV Quang Trung?
3. How can BIDV Quang Trung effectively manage its NPL?
4. What are the recommendations for improving managing NPL at BIDV Quang Trung?
1.4. Research methodology
1.4.1. Methodology

The final project uses the Basel Accords as a standard to rate the financial position and income
predictability of a bank as well as its credit risk over time. The final project also uses
qualitative and quantitative methods to measure and evaluate the related data. The qualitative
method is suitable for complex research with intention to provide a deeper understanding and
analyze the overall picture. The quantitative techniques are mostly way of measuring the
statistic selections to get the results more standardized in comparison with qualitative method.
1.4.2. Data collection
Both primary and secondary data is used for analysis. As the author found out secondary data,
even though quite abundant in quantity, was not sufficient for the scope of the research,
primary data is also utilized. Primary data is collected through in-depth interviews and
discussions with high-ranked bankers. Secondary data included banks’ annual reports,
financial statements, websites, television, newspapers, government publication, finance
journals, banking statistics, books, surveys and industry reports.
1.4.3. Selection
Qualitative interviews do not require a certain way selecting interviewees. However, the main
principle is that the selection should be made in the interest of the researcher’s aim (Rolf
Johansson, 2003). The author sought out people with experience on NPLs and asset
management who were willing to provide with sometimes sensitive information. Those
include directors, managers of corporate customer department, loan managers, compliance
control and inspection managers, officers with many years of experience with handling NPLs
(detail listed in Annex I).
1.4.4. Interview
The author chose to conduct an in-depth interview which is a crossed method between
structured and unstructured interview. It contains both the strict schedule from the structured
interview as well as the flexibility and conversation-like discussion from the unstructured
interview. The objective of an in-depth interview is to understand thoroughly the reasons
causing increasing NPL at BIDV QT. The author followed certain objective but still leave
room for other information of interest. The questionnaires which include 12 questions for
directors, managers and 11 questions for staff who work at BIDV QT were formulated and
constructed in order to avoid asking indistinct formulations, difficult designed questions.

There were 20 interviewees which included 1 director, 2 deputy directors, 3 managers, 3
deputy managers, 1 supervisor, 10 officers in the departments of BIDV QT(with the detail
listed in Annex II).
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1.4.5. Methods of conducting interviews
In order to make the primary data representative, the author found it necessary to audio record
the interviews. However, being aware of that taping an interview can affect the interviewee as
it might make him/her feel uncomfortable (Crane, 2004), the author made it clear that the
recording was to be used for academic purpose only. Notes were also taken during the time of
interview. Each interview was carefully transcript to prevent information loss through human
errors.
1.5. Research scope
The study of this research would enable the researcher to have better understanding of the
management of NPL at BIDV QT. In the scope of the final project with limited time and
resources, the research focuses only on the credit activities of BIDV QT from 2010 to 2013.
1.6. Research structure
The final project includes three chapters:
Chapter I “Theoretical Framework” review the relevant theories on managing NPL, giving
main ideas and some evaluation.
Chapter II “Current status of NPLs management at BIDV QT from” provides an overview
as well as analysis on managing NPL at BIDV QT.
Chapter III “Recommendations to improve the management of NPLs at BIDV QT” brings
some suggestions to reduce NPL rate and thus increases credit quality.

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CHAPTER I: THEORETICAL FRAMEWORK FOR NPL MANAGEMENT IN

COMMERCIAL BANKS
I.1. CONCEPT
I.1.1. Definition of credit risk
Credit risk is the risk of property loss resulting from borrowers who are not able to perform
part or all of the commitments signed with the bank.
According to the Basel Committee’s literature, "Credit risk is the change of net income and
the value of capital derived from the loan which is not paid or paid late."
In Vietnam, in accordance with decision No. 493/QD-NHNN dated 22 April 2005 issued by
the SBV, "Credit risk is the possibility of losses resulting from the borrower failing to perform
its obligations under the commitment."
Credit risk is a major concern for commercial banks because it is associated with their main
revenue-generating activity, which is granting credit. Banks are required by laws to accurately
analyze borrowers’ financial position in order to ensure the loans’ collectability.
Credit risk is usually associated with providing credits, which is the largest and most important
operation in a commercial bank. In a perfect world, when banks lend out money, they must try
to collect and analyze all information related to the borrower, following the standard
regulations to ensure the collectability of the loans. However, there are many factors affecting
the customers’ solvency that neither banks nor anyone else can foresee – the economy, for
example. Bank staffs can definitely make human mistakes in judging a project’s feasibility.
Sometimes, staffs even collude with customers to create false financial analyses. As a rule of
thumb, expecting the unexpected is the way of the banking industry. For the scope of this
project, we mainly focus on the risks that can be measured.
I.1.2. Indicators of credit risk
- The indicators:
Banks are required to minimize financial losses should the event of a default occur. Credit
risk can be assessed based on the following main criteria:
• Overdue loans as a percentage of total outstanding loans;
• NPL and NPL rate on total outstanding loans;
• The diversification of outstanding loans
• The collaterals;

• The relationship between the customers and the bank;
• Business environment of the customers’ industry.
Banks are recommended to collect as much information as possible regarding the above
aspects to ensure the loan’s safety.
- The measures of credit risk:
Credit risk measures are devised to quantify the risk of losses due to counterparty default.
Credit risk is generally broken down into three components:
• Default risk: is the possibility that a borrower fails pay off all or part of his
obligations. There are several criteria as to when a default occurs, such as: missing
payment for more than 90 days, filling for bankruptcy, breaking a covenant (which
triggers a cross-default for all lenders.) Default risk depends on many factors, both
qualitative and quantitative. Borrowers in a weak financial situation, high debt
burden, low and/or unstable income have a higher risk of default.

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• Qualitative factors such as the state of relevant industries and management quality
can also help banks determine the risk level for each customer. Markets with more
competition and harsher economic conditions are more likely to result in businesses
defaulting. Another factor would be the financial backing that a customer may have
access to. A subsidiary that is not doing well financially can receive support from its
parent company and therefore less likely to default.
• Exposure risk: Exposure risk measures the amount at risk when lending to
counterparty. The level of exposure risk varies with the types of transactions. For the
amortized loans, principal is paid off over time, therefore exposure risk is reduced.
For lines of credit, however, the exposure risk is consistent during the life of the
contract. For project financing transactions, exposure risk tends to rise from the
beginning of the contract, reaching its highest level at the middle stage of project
development and declines afterwards. For transactions involving derivatives,

exposure risk varies during the life of the contract as market indicators change.
Exposure risk is particularly high with these transactions because, as it is well
known, derivatives can oftentimes be extremely volatile.
• Loss risk: The loss risk determines the loss as a fraction of the exposure in the case
of default. In the Basel II, this parameter is known as the loss given default which is
the amount of funds that is lost by a bank or other financial institution when a
borrower defaults on a loan. Academics suggest that there are several methods for
calculating the loss given default, but the most frequently used method compares
actual total losses to the total potential exposure at the time of default. Of course,
most banks don't simply calculate the LGD for one loan. Instead, they review their
entire portfolio and determine LGD based on cumulative losses and exposure.
I.2. NPL IN COMMERCIAL BANK
I.2.1. Definition of overdue loan
Overdue loans are loans that customers fail to repay in full on the maturity date of the loan
contract. According to Decision No. 493/2005/QD-NHNN dated 22/4/2005 issued by the
SBV, overdue loan is understood as "a loan of which a part or all of the principal and/or
interest has not been paid." In commercial banks, the level of overdue loans reflects the level
of credit risk.
I.2.2. Definition of NPL
According to international standards
According to the NPL Statistics Division – United Nations, " a loan is considered NPL if
interest and/or the principal are overdue more than 90 days; or unpaid interest from more
than 90 days was added to the principal, or the payments are overdue less than 90 days, but it
is reasonable to suspect the possibility that the loan will be fully paid." Thus, NPL is
determined by two factors: (i) expired more than 90 days and (ii) solvency in doubt. This is
also the working definition of NPL in the International Accounting Standards (IAS).
According to Vietnamese standards
Decision No. 493/QD-NHNN dated 22 April 2005 and Decision No. 18/2007 by the SBV
dated 25 April 2007 defined NPL very similarly to international standards.
I.2.3. Classifying loans using quantitative and qualitative measures

Banks can classify loans on either a quantitative or qualitative basis. Both methods result in a
5-group classification:
- Group 1: standard loans
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- Group 2: loans that require attention
- Group 3: sub-standard loans
- Group 4: loans in doubt
- Group 5: loans at a high risk of being defaulted
Corresponding to each group, the State bank mandates a fixed amount of allowance: 0%, 5%,
20%, 50% and 100%, respectively.
Decision No. 493/QD-NHNN dated 22 April 2005 issued by the SBV regulates: "NPL are
loans which are classified in group 3 to 5.” The criteria for classifying loans are as followed
(Quotes Article 6, Article 7 of Decision 493/2005/QD-NHNN):
Classification of debt by quantitative methods:
• Group 3 (Sub-standard loans) includes loans that are overdue from 91 to 180 days;
first-time restructured loans (except for ones already classified into Group 2; loans
whose principal and/or interest have been partially waived; and other obligations that
are classified in Group 3.
• Group 4 (Loans in doubt) includes loans that are overdue from 181 days to 360 days;
first-time restructured loans that are overdue by less than 90 days from the date of
restructuring; loans that have been restructured for the second time; and other
obligations that are classified into Group 4.
• Group 5 (Loans at a high risk of being defaulted) includes loans that are overdue by
over 360 days; first-time restructured loans that are overdue by more than 90 days
from the date of restructuring; overdue loans that have been restructured for the
second time; loans that have been restructured more than two times; classified loans,
and other obligations that are classified in Group 5.
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Classification of debt by qualitative methods:
• Group 3 (Sub-standard loans) include loans of which the possibility of collecting all of
principal and interest when they mature is unlikely.

• Group 4 (Loans in doubt) includes loans at a higher risk of default than Group 3.
• Group 5 (Loss debt) includes loans that are very likely to be defaulted.
Under both international and Vietnamese standards, NPL is considered to be loans which are
overdue for more than 90 days and/or judged to be wholly or partly unrecoverable.
I.2.4. The impact of NPL on the operation of commercial banks
NPL is part of being in the banking business. The trick is how to keep NPL in control and
predictable. A higher than expected NPL rate may cause have serious consequences,
affecting the banks, the customers, and sometimes in extremely bad cases, the economy:
NPL reduces profitability
Even if an NPL is eventually paid off, this incurs loss for the bank because of the time value
of money. Moreover, when NPL incurred, banks must set aside an allowance for bad debts,
depending on how long the loans have been overdue. This allowance is taken directly out of
net earnings. Handling of NPL can be very expensive too. And in the worse case when an
NPL is written off and collaterals sold, very rarely do we see a bank recovering the full
amount.
NPL hurts the bank's reputation
Reputation is everything in the banking business. A lowered reputation will surely result in
lower deposit and consequently, lower lending. Big customers will steer away from banks
without a strong reputation because the fact is, interest rates among the state-owned banks do
6


not differ in any conceivable way, and there are four of them to choose from. Maintaining a
good image is one of the top priorities at BIDV, as it is at any other place.
NPL can cause insolvency

Banks, as any other type of business, can go out of business if sustaining losses for too long.
However, unlike other businesses, banks build its foundation on customer’s trust. Once a
bank is seen as “weak”, customers may choose to put their money elsewhere, and things can
only start going down from there. We have seen examples of hundred years old banks going
out of business in a week after the public finds out they had made a bad investment and
suffered a big loss. This is because banks keep only around 10% of deposits as reserve – the
rest is lent out. Once the public decides their money is not secured, they can rush to withdraw
their deposit – effectively making the bank insolvent.
I.3. THE THEORY OF NPL MANAGEMENT IN COMMERCIAL BANK
I.3.1. Definition
Management NPL is not only how to handle NPL when it incurred but also includes
developing and implementing the strategies and policies of credit management in banking
business in order to achieve safety objectives, efficient and sustainable development.
Additionally, it is highly focused on the strengthening of measures to prevent and minimize
NPL incurred; along with the handling these incurred NPL in order to match with the goal in
each stage of the bank.
I.3.2. The objective of NPL management
The objective of managing NPL in each stage of banking business is different. However, in a
general way, the objective of managing NPL in any circumstance for the bank is that it must
develop and implement a regulation, policy to classify customers in accordance with each
period to restrict the lowest level of risk from the loans without affecting the target profit of
the bank.
I.3.3. Basel principles on managing NPL
The Basel Committee issued 17 guidelines on managing NPL, the majority of which deal
with ensuring safety and efficiency in credit activities. The principles can be summarized
into the following points:
Develop a system for credit monitor and management (3 principles): in this
context, the Basel Committee urges BODs to perform periodical credit risk assessments and
to continually develop new strategies and policies as soon as new information emerges. The
General Director would then be in charge of enforcing the aforementioned strategies and

policies in order to maintain control of NPLs at all levels of the bank’s portfolio.
Granting “healthy” credits (4 principles): as commercial banks usually serve an
extremely broad range of customers, they offer many different products tailored to fit the
needs of everyone and everything from individuals to international conglomerates. For each
of those products, banks must clearly define at least the following criteria: eligibility, amount,
duration, other terms and conditions. After that, customers need to go through a filtering
process under the form of an internal credit rating system, which, based on each customer’s
creditworthiness, determines if one is eligible for a loan, and if yes, how much. The
procedures should be unified and unambiguous. Aside from the obvious factor of financial
position, the role of the credit officer cannot be overlooked.
Utilizing information system for credit risk analysis and management (10
principles): Banks must have a system by which customers files are continually collected and
kept up-to-date. The complexity of this system will depend on each bank’s scale of operation.
At a minimum, this system should be able to keep up with clients’ financial information and
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compliance status to quickly detect NPL. The next step can be assigned to either the debt
handling department or the marketing department or sometimes, both, depending on the loan
itself. The Basel Committee also recommends that banks build a rating system or its assets at
risk.

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CHAPTER II: CURRENT STATUS OF NPL MANAGEMENT AT BIDV QT
II.1. INTRODUCTION TO BIDV QT
II.1.1. Overview
BIDV QT was established in 2005 after being spun-off from BIDV SGD I. From a humble
start with only 700 billion VND in total outstanding loans and a relatively small customer

base, the branch has grown exponentially over the years, with outstanding loans shooting
almost 10-fold after 8 years. BIDV QT prides itself on having the smallest workforce in
relation to net income in the BIDV system. Normally a branch of comparable size and
profitability has around 400 employees. At BIDV QT we make do with just over 200, around
80 of whom are directly involved in credit activities.
Over the years BIDV QT has built trust and close relationships with many big partners in
various industries. Most of the high-profile companies in real estate and construction are
BIDV QT’s loyal customers. EVN – the biggest state-owned electricity company; VNPT –
telecom giant – and Vingroup are all BIDV QT’s customers. We also handle cash and
provide lines of credit for hundreds of small and medium-sized companies.
For the last few years BIDV QT has consistently placed itself among the top 5 of the biggest
branches in BIDV system.
II.1.2. BIDV QT’s organization structure
Currently, BIDV QT has 12 specialist departments in headquarters and 7 business
offices with a total of 210 employees, 90% of whom hold a bachelor’s degree or better.
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Wholesale banking:
• Department of corporate customers relations: serves as a focal point of maintain and
develop relationships with clients on all aspects of operations. The banking business
greatly values trust, therefore a good relationship with customers can sometimes mean
the difference between a long-term partnership or no business at all. The department
performs general customer evaluation and business analysis, which then will be
forwarded to upper management under the form of a report and a proposal.

-

Retail banking:
• Department of retail customers relations: same as the wholesale department, the retail
department builds relationship, albeit with individuals. A large portion of our total

deposit comes from the general public. Currently about one fifth of BIDV’s total
outstanding loans are loans made to individuals. They are an important source of
capital and income for any commercial bank. The department also markets and
develops specific products for personal use such as personal banking, credit card, debit
card, wire transfer, currency exchange, among other things.

-

Supporting departments:
• Department of credit management: the final step in the credit approval process, this
department double-checks for the validity of customers’ files, business plans contracts,
terms and conditions before cash disbursement. They also archive those files and input
them to BIDV QT’s database.
• Accounting department: recording banking transactions compliance with accounting
principles and regulations, and reporting to BOM, SBV and BIDV headquarter.
9


Figure 2.0: BIDV QT’s organization
• General planning department: fulfilling synthesize, analysis and business plans
development; trading interbank with headquarter, exercising foreign currency with
customers; managing and controlling foreign exchange, interest rate to ensure stability
in liquidity demand and optimize its fund utilization
• Information technology department: managing and maintaining information
technology systems related to banking business activities.
• Risk management department: testing, monitoring, auditing the compliance with
procedures, accounting, foreign exchange, treasury, trade finance, credit, retail service
10

banking to reduce risk, fraud, error in the key positions as well as activities of the
bank.
• Human resource department: Recruiting, evaluating, managing and training staff;
developing; incentive policies; fulfilling administrative activities of the bank.
II.1.3. BIDV QT’s activities from 2010-2013
-

Fund mobilization:

As of 12/31/2013, the total deposit from customers reached more than 9,277 VND billion, up
12.37% compared to 2012. This is considered as the highest increase since the string of
positive deposit growth from 2010 to present. This can be attributed to BIDV’s good
performance in recent years. The table 2.1 below summarizes the fund mobilization of BIDV
QT in the past few years.
Unit: VND Billion
2011

2012

2013

Target

% against
2012

% against
targets

Deposits from

customers

7,120 7,385

8,256

9,277

9,200

112.37%

100.83%

Total liabilities
and equity

7,530 7,740

9,156

10,274

10,200

112.21%

100.73%

Item

2010

(Source: BIDV QT’s Financial Statements from 2010 to 2013)
Table 2.1: Fund mobilization of BIDV QT from 2010 to 2013
From the start of 2013, the BOD of BIDV drastically assigned the fund mobilization target to
all branches and BIDV QT was assigned to reach the target at 9,200 VND billion in fund
mobilization in 2013. As of 12/31/2013, this goal has been achieved, exceeding target by
0.83% (Figure 2.2). BIDV QT's market share has been rising, and total assets reach the
highest since 2010.

Figure 2.2: Deposits from customers and Total Asset of BIDV QT 2010-2013
11


-

Credit activities:

From early in 2013, the BOD assigned the target of NPL ratio in the whole system at less
than 2%. However, by 09/30/2013, NPL ratio of the whole system was 1.8%, dangerously
close to target.
Unit: %
2011
NPL rate
2.57%
0.75%
2.10%
6.00%
0.85%

3.70%

Credit Institution
BIDV
Vietinbank
VCB
Agribank
Other Joint stock Banks
Banking system

2012
NPL rate
2.77%
1.35%
2.25%
5.8%
1.04%
4.08%

2013
NPL rate
1.80%
0.82%
3.76%
6.32%
0.62%
3.79%
(Source: Financial Reports)

Table 2.3: NPL rate of BIDV against other banks

From 2011 to 2013, BIDV did not fare the best in terms of NPL management among the
largest state-owned banks and other Join stock Banks as a whole. However, by 2013, its
NPL rate has dropped well below its level in 2012, showing BIDV’s effort in reducing NPL.
Branch
BIDV Headquarter
BIDV Hoan Kiem
BIDV SGD I
BIDV South
Saigon
BIDV Tay Ho
BIDV QT
BIDV SGD III
BIDV Bac Ninh
BIDV North
Hanoi
BIDV SGD II

Unit: VND Billion
NPL
NPL rate
238
3.1%
201
3.8%
198
2.3%
205
142
239
280

100

3.3%
5.2%
3.6%
3.7%
4.0%

170
245

3.2%
2.7%

(Source: NPL report in 2013)
Table 2.4: 10 branches with highest amount of NPL and NPL ratio as of 12/31/2013
Throughout the year 2013, BIDV achieved a lower NPL rate than 2012. However, a few
branches saw their NPL rate drastically increase. Among those branches, BIDV QT had
among the highest amount of NPL, accounting for 3.6% of BIDV's total NPL (NPL report in
BIDV system).
-

Financial results:

12


As of 12/31/2013, the branch's profit before provision increased to 174 VND billion, while
profit after provision was 124 VND billion, up 9.7% compared to 31/12/12. However, in
2013, BIDV QT only set aside 50 VND million for provision and allowance. Details of BIDV

QT’s financial statements are described in Table 2.5.
2010
2011
Amount Amount

Item
Profit before tax
before provisions
Provisions and
allowance for
credit risks
expense
Profit before tax
after provisions

Unit: VND Billion
2012
2013
Amount Amount

124

136

153

174

(5)

(40)

40

50

129

176

113

124

(Source: Financial Statements of BIDV QT from 2010 to 2013)
Table 2.5: Financial result of BIDV QT from 2010 to 2013
It can be said that the higher NPL will seriously affect the competitiveness in the banking
business. High NPL ratio not only reduces the solvency of banks, decreases efficiency in
allocation of asset and liability as well as the liquidity of capital, but also increases the
feasible of losing capital as result reducing the profitability of banks, increases level of risk
as well as loss of customers’ belief for banks. Therefore, managing and reducing NPL ratio
can be considered as the most important duties of BIDV QT in this period.
II.2. CURRENT STATUS OF NPL AT BIDV QT 2010-2013
II.2.1. NPL status and loan classification
NPL status:
As of 12/31/2013, total loans of BIDV QT were 6,646 VND billion, up 15.6% compared to
2012. Meanwhile, NPL was 239 VND billion, up 30.0% compared to 2012 and significantly
exceeded the goal of 1.80% assigned by the BOD. Detailed figures are provided in Table 2.6
and Figure 2.4.

Item

Unit: VND Billion
+/- %
+/+/- %
2013
against 2013
against against
Target
Target
2012
2012

2010

2011

2012

2013

Loans 3,590

4,329

5,749

6,646

897

115.60%

6,700

99.19%

87

184

239

55

130.00%

120

199.17%

3.60%

0.4%

NPL

54,4

NPL

1.51% 2.00% 3.20%
rate

112.50% 1.80%

200%

(Source: Financial Statements of BIDV QT from 2010 to 2013)
Table 2.6: BIDV QT’s NPL from 2010 to 2013
13


This high record figure reflected the increase in BIDV QT’s market share and its higher
liquidity and credit risk. Therefore, the important duty of BIDV QT is to reduce the NPL
ratio to get the target. This figure also showed a part of the weakness in the credit risk
management, in the quality of disbursement monitoring as well as in the NPL management
of BIDV QT.

Figure 2.7: NPL rate curve of BIDV QT from 2010 to 2013
Loan classification:
BIDV QT implemented loan classification and provisioning risk under Article 6 (for
individuals) and Article 7 (for businesses) of Decision No.493/2005/QD-NHNN issued by
the SBV since 2006. The internal credit ratings system has been built to ensure a streamlined
quality management process from the stage of evaluation, approval to the stage of cash
disbursement as well as collateral management. The internal credit rating policy also help the
manager control the loan classification, provisioning and use of allowances to handle risk.
This set of regulations also helped determine the rights and responsibilities of departments as
well as individuals involved in the process. The following Table 2.8 is loan classification
results over the years from 2010 to 2013.
Unit: VND Billion

2010
2011
2012
2013
Item
Amount % Amount % Amount
%
Amount
%
Group 1 –
3,177 88.49% 3,593 83% 4,933 85.80% 5,802 87.30%
Current debt
Group 2 –
359
10%
649
15%
632
11.00%
605
9.10%
Special
mentioned debt
Group 3 - Sub30
0.84%
50
1.15%
70
2.28%
140

2.11%
standard debt
Group 4 –
20
0.56%
30
0.69%
30
0.72%
79
1.19%
Doubtful debt
Group 5 – Loss
4
0.11%
7
0.16%
6
0.20%
20
0.30%
debt
Total Loans
3,590 100% 4,329 100% 5,749 100.00% 6,646 100.00%
(Source: Financial Statements of BIDV QT from 2010 to 2013)
Table 2.8: Loan classification of BIDV QT from 2010 to 2013
14


As shown in Table 2.8, in 2011, Group 2 debt reached 15% while NPL accounted for 2% of

total loans. In 2012, Group 2 debt decreased to 11% while NPLs reached 3,2% of total loans.
As of 12/31/2013, Group 3, 4 and 5 both increased, amounting to the 3.6% NPL rate. Thus,
only in four years from 2010 to 12/31/2013, the branch's NPL increased significantly, from
1.51% to 3.6%. With current economic situation which is getting more and more difficult,
Group 2’s ratio of 9.10% might be a potential risk, which will raise NPL ratio and affect
asset quality of the bank when this group change to low credit rating groups.
II.2.2. NPL structure
To better understand the loan structure, as well as the proportion of NPL in each type of
loans we further analyzed the types of loan structure in the BIDV QT as below:
Loans by time to maturity
When it comes to time to maturity, loans are divided into three categories: short term,
medium term and long term. The data were summarized in Table 2.9. In Table 2.9, from
2010 to 2013, the proportion of short-term loan on total loan of BIDV QT increased, while
medium term and long term has a downward trend. Specifically, as of 12/31/2013, short term
loans accounted for 46.49% and medium and long term loans accounted for 53.51%.
Unit: VND Billion
2010
2011
2012
2013
Item
Amount
%
Amount
%
Amount
%
Amount
%
1,508

42.01%
1,820
42.04%
2,950
51.31%
3,090
46.49%
Short term
Medium to
long term

2,082

57.99%

2,509 57.96%

2,799 48.69%

3,556 53.51%

Total

3,590

42.01%

4,329 42.04%

2,950 51.31%

6,646 46.49%

(Source: Financial Statements of BIDV QT from 2010 to 2013)
Table 2.9: Loan classification by time to maturity of BIDV QT from 2010 to 2013
However, at that time the interest rates which had maturity from 1 month, 3 months, 6
months or 12 months were the same as 14%. Especially, there was some stress time that the
short term interest rate of deposit was higher than the long term interest rate, and the
customers tended to deposit in short-term reflecting the illiquidity in banking industry
(Interest rate report of SBV). This problem will cause the unbalance in managing assets and
liabilities of the bank, increase liquidity gap and liquidity risk, credit risk for BIDV QT.
NPL classified as repayment period is described in the Table 2.10.
Unit: %
Item

2010

2011

2012

12/31/2013

% NPL Short term

47.42%

87.43%

59.20%

68.98%

% NPL Medium term

52.58%

12.57%

7.05%

10.94%

0%

0%

33.76%

20.07%

% NPL Long term

(Source: Financial Statements of BIDV QT from 2010 to 2013)
Table 2.10: NPL classification by time to maturity of BIDV QT from 2010 to 2013
15


As shown in Table 2.10, NPL of BIDV QT from 2010 to 2011 was mainly short and medium
term. Since 2012 to 2013, short and medium term NPL fell while long term NPL

skyrocketed. As of 12/31/13, BIDV QT’s NPL short-term was 68.98%, medium-term was
10.94% and long term was 20.07%. Considering the current economy, the increase in the
proportion of long term NPLs reflects a big problem in long term financial capacity. The
weakness and inefficiency of cash flow management of the customers, as the result, will
affect the credit quality of the bank.
Loan classification by business structures:
When it comes to types of business, loans are divided into five categories of asset such as
loans for State owned companies, Limited companies, Joint stock and private companies,
Foreign invested enterprises, and for Individuals.
Unit: VND Billion
2010
2011
2012
2013
Item
Amount %
Amount
%
Amount
%
Amount
%
State owned
215.4
6%
216.45
5%
287.45
5%
265.84

4%
enterprises
359
10%
519.48
12%
632.39
11%
664.6
10%
Limited companies
Joint stock and
private companies
Foreign companies
Individuals
Total Loans

2,405.3

67% 2,943.72

68% 3,794.34

0

0%

0

0%

0

610.3

17%

649.35

15%

1034.82

3,590

100%

4,329

100%

5,749

66% 4,585.74
0%

69%

0

0%

18% 1,129.82

17%

100%

6,646

100%

(Source: Financial Statements of BIDV QT from 2010 to 2013)
Table 2.11: Loan classification by business structure from 2010 to 2013
As in Table 2.11, in 2013, most loans came from three groups of companies which were
limited companies accounting for 10%, Joint stock and private companies accounting for
69%, and Individuals accounting for 17%. State owned enterprises accounted for only 4%
while Foreign companies remained at 0%. NPL rate of JSCs was the highest, accounting for
96% of total loans in 2013, followed by Individuals contributing to 2% as described in Table
2.12.
Unit: %
Item
2010
2011
2012
2013
0.0%
0.0%
2.0%
2.0%

% NPL State owned companies
0.0%

0.0%

0.0%

0.0%

99.0%

99.0%

96.3%

96.0%

% NPL Foreign invested enterprises

0.0%

0.0%

0.0%

0.0%

% NPL Individuals

1.0%

1.0%

1.7%

2.0%

% NPL Limited companies
% NPL Joint stock and private companies

(Source: Financial Statements of BIDV QT from 2010 to 2013)
16