Nghiên cứu nhân tố ảnh hưởng đến quyết định cho vay đối với khách hàng doanh nghiệp nhỏ và vừa tại các ngân hàng thương mại khu vực tây bắc việt nam tt 2

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CHAPTER 1:
GENERAL INTRODUCTION TO THE THESIS
1.1. The reason for choosing the topic
Theoretical gaps: bank's lending decision is affected by: hard and soft information.
Berger, Allan and Lamont Black (2011), commercial banks apply many lending
technologies, banks have their own advantages in hard or soft information, (small banks
with soft information collection advantages are called Qualitative information or nonfinancial information, large banks that have the advantage of gathering hard information are
known as quantitative information or information based on financial statements).
The role of soft information influences bank credit decisions: social capital
relationship, belief in competence and business ethics ..., especially soft information is
subjectively evaluated by Credit officers directly collect and process credit decisions. This is
a research gap that is very interesting and has important implications for the credit
management policy of a bank, official credit capital mobilization policy of corporate
customers.
Current situation gaps: In 2019, among 6,202 SMEs in the Northwest sub-region, over
30% of enterprises are seriously lacking in capital but cannot access bank credit because of the
reasons: Unaudited financial statements, weak enterprises in collateral, low financial efficiency,
declining profits in recent years according to the global trend ... means that SMEs cannot meet
the requirements of hard information that banks set. In addition to hard information, bank credit
officers consider soft information when making lending decisions such as: belief in the capacity
and ethics of business owners, participation in network relationships. Corporate society ... These
factors play an important role in credit decision-making but are not currently reflected in bank
and corporate credit policies.
Stemming from the theoretical gap and the current situation, the author has chosen the topic:
“Research on factors affecting lending decisions to small and medium-sized enterprise customers at
regional commercial banks. Northwest Vietnam” as my research topic.
1.2. Overview of research related to the topic
1.2.1. Concept and classification of hard and soft information
The concept of hard and soft information has been widely developed in
organizational economics literature (Degryse et al, 2013; Saengchote, Kanis, 2013; Qian et

al, 2010; Petersen, 2004).
Petersen (2004): hard information is quantitative information - Digital digital (in finance is
balance sheet data, profit, assets ...) soft information is qualitative, verbal (meaning opinions, ideas,
projects, opinions ...); hard information about outdated trends in the search direction (eg balance
sheet data), soft information about future forecasting trends (eg business plan). Hard information is
almost always recorded digitally. Soft information is qualitative information, non-financial
information, information outside financial statements; Hard information is quantitative information
and is information on financial statements (based on research by Berger, Allan and Lamont Black,
2011).

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1.2.2. The role of the two types of information in a commercial bank's lending
decision
Synthesis of studies in the review, there are two different assessment directions on the
importance of hard and soft information to a bank's lending decision:
First, hard information plays an important role in the lending decisions of commercial
banks
Second, soft information plays an important role in the lending decisions of
commercial banks
1.2.3. The role of the credit officer in the bank's lending decision
Evaluation of the role of customer information collection and processing staff (credit
officers) has two main research directions:
Credit officers play an important role in the bank's lending decisions.
However, there are also studies that ignore the importance of credit officers such as:
Gropp, Gruendl and Guettler (2012) show that using lender's decision power does not affect
the effectiveness of creditors. Bank loan section.
1.2.4. Research gap
- First, studies in the world on banks' lending decisions to SMEs have not yet agreed
on the roles of hard and soft information to lending decisions. Especially in the developing
economy, when asymmetric information is severe, this research is even more necessary.

- Secondly, research to supplement qualitative data from the subjective perception of
credit officers, to verify the role of information processing collectors to the probability of
getting SME bank loans or not.
- Third, research to clarify the role of Social Capital factors, Trust (in capacity,
prestige, entrepreneurship ethics), the position of the lender (the main bank in lending to
SMEs) to the loan decision of commercial banks.
- Fourth, in the Northwestern sub-region of Vietnam, SMEs also carry all the
characteristics of SMEs in general, but there are no studies to assess the ability to access
bank loans, or study the factors that influence. to decide on lending of commercial banks to
these SME customers.
On the basis of pointing out gaps in research on SME lending decisions of
commercial banks, the thesis shows the necessity of this study to fill the previous research
gaps, specifically the thesis needs:
- Determine the factors that significantly affect commercial banks' lending decisions
to SME customers in the Northwestern sub-region of Vietnam.
- Compare and confirm the role of the two types of hard and soft information to the
lending decisions of commercial banks with SMEs in the Northwest sub-region.
- Scientific examination of the influence of soft information factors: Social capital,
trust, Bank's position in lending on lending decisions of commercial banks.
- From there, proposing feasible solutions to help SMEs in the Northwest sub-region
easily access bank loans.


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1.3. Objectives of the study
The thesis has a general objective: to study the factors influencing the lending
decisions to SME customers at commercial banks in the Northwestern region of Vietnam.

1.4. Research question
With the research objectives as mentioned above, the thesis must answer the
following research questions:
- What kind of information does the Northwestern subregion commercial bank use
(information collected about enterprises) in its lending decision to SMEs?
- Which information plays a more important role in lending decisions to SMEs in the
Northwest?
- What should commercial banks, SMEs and related organizations do to help SMEs
in the Northwest easily access bank loans?
1.5. Object and scope of the study
Research object: Research on factors affecting SME lending decisions of commercial
banks in the Northwest region of Vietnam.
Research scope:
- Research credit decisions in lending operations (the bank administrator's
perspective).
- In this study, the author agreed to understand the term: soft information is
qualitative information, non-financial information, information outside financial statements;
Hard information is quantitative information and is information on financial statements
(based on research by Berger, Allan and Lamont Black, 2011).
- Hard and soft information in a commercial bank's lending or non-lending decision
(assessment information is collected from the bank credit officers' perspective survey)
- Study in 4 provinces in the Northwest sub-region according to Decision No. 1064 /
QD-TT, 08/7/2013 of the Prime Minister on "Approval of master plan for socio-economic
development in midland and the Northern mountainous region to 2020 ”, including Hoa
Binh; Son La; Dien Bien; Lai Chau.
- Target customers in lending decisions are small and medium enterprises.
- Secondary data collected during the period: 2013 - 2018
- Primary data collected during the period: March - December 20171.6. Phương pháp
và quy trình nghiên cứu
1.6.1. The research process of the thesis

1.6.2. Research Methods
- Qualitative research: General method and theoretical analysis; Modeling method;
Hypothesis method; Comparative method; Professional solution; Group discussion method.
- Quantitative research:
+ Data source and survey survey: secondary data on the current situation of SME
loans at commercial banks in the Northwest subregion. Primary data are surveyed by author
and research team of full-time credit officers at commercial banks in the Northwest in the
end of 2018.

+ Clean data.
+ Statistical analysis.
Regression analysis method.
1.7. The contributions of the thesis
1.7.1. New academic and theoretical contributions
(1) On the basis of asymmetric information theory (George Akerlof, 1970; Michael
Spence, 1973; Joseph Stiglitz, 1975); applied theories in banking credit management (Fed,
2004; Peavler, 2013; Kobil Ruziev, 2018;…). Along with qualitative research results, the
thesis has added soft information factors (the theory of judgment and perceptions in loan
decision making (Brown et al, 2012), the theory of social capital (Mayer). et al, 1995)), into
a research model of factors affecting commercial banks' lending decisions to SME
customers.
(2) The thesis assesses the importance of hard and soft information in a bank's
lending decision, especially in an emerging economy, where information asymmetry occurs.
(3) The thesis uses a new approach based on the point of view of bank credit
management. Meaning: the subjective opinion, the feeling of the credit officer has a
significant influence on the bank's lending decision.
1.7.2. New practical contributions
The research results of the thesis are similar to those of Berger and Udell (1995) that
in the emerging economy, the information asymmetry phenomenon occurs seriously, so
banks always find ways to Minimizing risk by setting collateral is the first choice. However,

other research results Iyer, Khwaja, Luttmer and Shue (2015) believe that soft information
has a decisive role in the ability of banks to get loans. The research results show that:
financial information, information about collateral, credit history, relationship with the
lending bank all have a significant impact on a bank's lending decision. Accordingly, the
factors of collateral have a decisive influence on the ability of customers to receive loans,
soft information factors play a complementary role to hard information. Meaning: SMEs
cannot borrow money from the bank without collateral. On the basis of research results, the
thesis recommends:
(1) Commercial banks at branch level: need to supplement and perfect credit policy
for small and medium enterprise customers to reduce dependence on collateral.
(2) Head office level commercial banks: the current situation of internal credit rating
with soft information indicator accounts for 50% - 70% of the total score. Contrary to the
survey situation: 100% of hard information requirements are very high, meaning that there
is a gap between policy and implementation, banks need to adjust the set of criteria and
credit score structure.
(3) On the side of small and medium enterprises: it is necessary to proactively grasp
the specific requirements of banks, supplement the response level of hard information
(additional collateral, transparency of asset information key) and strengthen soft information
advantage (relationship with banks).


(4) Regarding the relevant boundaries (State Bank, Association of Small and
Medium Enterprises): Renovating mechanisms and policies to support small and medium
enterprises in order to easily access bank loans (support for collateral, lending to businesses
along the value chain ... in order to reduce dependence on collateral, ...).
1.8. Thesis layout
Thesis layout includes 5 chapters
Chapter 1: Introduction about the thesis
Chapter 2: Theoretical basis of factors influencing SME lending decisions in
commercial banks

Chapter 3: Research Methodology
Chapter 4: Research results
Chapter 5: Discuss results and recommendations
CHAPTER 2: THEORETICAL BASIS OF FACTORS AFFECTING
DECISIONS ON LOANS TO SMALL AND MEDIUM BUSINESS CUSTOMERS IN
COMMERCIAL BANK
2.1. Theoretical basis for lending decisions to SME customers at commercial banks
2.1.1. Concept of small and medium business
2.1.2. Loans to SMEs in commercial banks
The SME loan classification of commercial banks can be classified into four basic
categories:
- Loan based on financial statements,
Loans based on collateral
Loans based on credit rating scores
=> These 3 categories are: credit distribution (Stiglitz and Weiss, 1981, J. Edwards, J.
Franks, C. Mayer and S. Schaefer, Stiglitz, J. and Weiss, A1986) or onlending (De Meza
and Webb, 1987, de Meza, 2002).
Relationship-based lending: Social theory advocates think that social capital, human capital,
and trust are variables that facilitate credit access for SMEs ( Granovetter, 1985; Ferrary,
2003)
2.1.3. Difficulties in accessing bank loans of SMEs
In global surveys, SMEs report that commercial banks provide 18.75% of total
financial needs, but the cost of access to finance is the biggest challenge for their
development.
2.1.4. Loan Process and Decision for SMEs
The steps of the loan process: Prepare loan application => Evaluation analysis =>
Credit decision => Disbursement => Loan monitoring, debt collection and liquidation.
Loan decision is the process of approving or rejecting a loan, requiring an assessment
of the risk system; have clear results, can quantify and measure results based on certain
professional methods (McNamara & Bromiley, 1997). Loan decisions are based on: the

components of the decision-making process; the lender's decision-making process; and the

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quality of the loan officer determines. Hirsch (1987), lending decisions can involve
quantitative information and subjective, qualitative assessments.
2.1.5. The commercial bank's internal credit rating prior to credit decision
Normally, commercial banks classify corporate customers into 10 grades with low to
high risk levels such as: AAA, AA, A, BBB, BB, B, CCC, CC, C, D.
2.1.6. Criteria for evaluating the results of the bank lending trade
Scale; Structure; Profit from the loan; Control risks in lending
2.2. Theories related to lending decisions of commercial banks
2.2.1. Theory of information asymmetry (Asymmetric Information)
Information asymmetry, sometimes called the failure information or imbalance of
information, means of economic transaction, one party has the advantage of holding more
information than the other, leading to the decision the economic inefficiency.
2.2.1.1. Adverse selection theory of credit markets (Adverse Selection)
In terms of information symmetry, meaning that one party in a transaction has more
information about business objects than the other party, who have the advantage of
information may provide information that is not honest about objects allocated poorly
translated to the advantages of information. As a result, less dominant parties agree on the
information to complete the transaction and get things not as they want.
2.2.1.2. Moral hazard in banking activity (Moral hazard)
Paul (2009) defines moral hazard as "cases where one party to make decisions related
to the acceptable level of risk, while the other party suffer losses if those decisions fail"
(Paul , 2009).
2.2.2. Theory of judgment and feeling in decision
In the study by Brown, M., Matthias Schaller, Simone Westerfeld, and Markus
Heusler (2012), managers in the world have acknowledged that the managers "within the
limits of reason," and so, management decisions are often unable to fully "rational".

2.2.3. Social capital theory
Crane, D., and Robert Eccles (1988), Hauswald, R., and Robert Marquez (2006)
Social capital includes social networks, trust in society, the ability to connect to do the job.
Or impact on the role of social capital in decisions of the enterprise funds: help enterprises
enhance the reputation and legitimacy.
2.2.4. Theory application in bank credit management
Kobil 7Cs Ruziev development model 'Good and 5Cs' Bad (Kobil Ruziev (2018)

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The soft information factor

Loan
decision /
denial

Social
capital
theory

The hard information factor

The
model of
factors
influenci
ng
lending
decisions

Theory of ethical risks in
banking operations

Applied theory in
credit management

Theory of unfavorable
choices of the market

Asymmetric
information theory

Factors that influence the collection process
and credit information processing

Theory of
judgment
and
perception
in decision
making

Credit
officer
Commercial bank credit process

Diagram 2.3: Theoretical framework of factors affecting lending decisions

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Source: author's synthesis

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2.3. Overview of factors influencing SME lending decisions
Factors affecting commercial banks' lending decisions are listed by the author as follows:
Table 2.9: Overview of factors influencing a bank's lending decision in previous
studies
Previous studies
Numerical
Influence factor
(+) Has an influence on the loan decision
order
(-) Does not affect the lending decision
Berger và Udell (2006) (+)
1
Mason và Stark (2004) (+)
Uchida et al (2006) (+)
Armstrong et al (2010) (+)
Financial report
Feldma (1997) (+)
Mester (1997) (+)
Nguyen Anh Hoang (2014) (+)
Hard
2
Business plan
Petersen và Rajan (2002) (+)
information Business purposes
Berry et al. (1993) (+)

3
Petersen,MA. (2004) (-)
4
Uchida et al. (2006) (-)
Products, services and
Armstrong et al. (2010) (-)
potentials, risks
Agarwal và Hauswald (2010) (-)
(business risks)
Berry et al. (1993) (-)
Nguyen Anh Hoang (2014) (+)
5
Berry et al. (1993) (+)
Uchida et al. (2006) (+)
Rand (2007) (-)
Knowledge
Coleman (2004a) (-)
Le, Sundar, & Nguyễn (2006) (+)
Nguyen Anh Hoang (2014) (-)
6
Berry et al. (1993), (+)
3rd party opinion
Uchida et al. (2006) (+)
Nguyen Anh Hoang (2014) (-)
7
Cole và Wolken (1995) (+)
Yildirim et al. (2013) (+)
Khalid (2014) (+)
Vo Tri Thanh (2011) (+)
Ricardo (2004) (+)

Ha Thi Thieu Dao (2014) (+)
Business size
Do Thị Thanh Vinh (2014) (+)
Le (2012) (+)
Malesky & Taussig (2009) (+)
Nguyen & Ramachandran (2006) (+)
Rand (2007) (+)
Nguyen Anh Hoang (2014) (-)
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Irwin & Scott (2010) (+)
Owner characteristics Nofsinger & Wang (2011) (+)
Fatoki & Asah (2011) (+)


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Numerical
order

Influence factor

9

Collateral

10
Credit history records
11
Trust (ability and
entrepreneurial
personality)

12

13
14
15

Soft
information

Participation in social
networks
Main lending bank
Time of relationships

Number of bank
products

10
Previous studies
(+) Has an influence on the loan decision
(-) Does not affect the lending decision
Coleman (2004b) (+)
Fatoki & Odeyemi (2010) (+)
Osei-Assibey, Bokpin, & Twerefou (2012) (+)
Ajagbe (2013) (+)
Nguyen Anh Hoang (2014) (-)
Tran Trung Kien (2015) (+)
Nguyen Thi Minh Hue (2012) (+)
Petersen và Rajan (2002) (+)

Uchida et al. (2006) (+)
Khung et al. (2001) (+)
Petersen (2004) (+)
Tran Trung Kien (2015) (+)
Nguyen Thi Minh Hue (2012) (+)
Nguyen Anh Hoang (2014) (+)
Uchida et al. (2006) (+)
Berger và Udell (2006) (+)
Nguyen Anh Hoang (2014) (+)
Berger (1998) (+)
Berger và Udell (2002) (+)
Petersen,MA. (2004) (+)
Xin và Pearce (1996) (+)
Nguyen et al (2006) (+)
Nguyen Hong Ha (2013) (+)
Nguyen Anh Hoang (2014) (-)
Ferrary (2003) (+)
Harhoff, D. and Körting, T. (1998a,1998b) (+)
Nguyen Anh Hoang (2014) (-)
Berger và Udell, (1995) (+)
Petersen và Rajan, (1994, 1995) (+)
Angelini, P. et al, (1998) (+)
Scott và Dunkelberg, (1999) (+)
Ongena và Smith, (2000) (+)
Uchida (2006) (+)
Uchida, Hirofumi, Udell, Gregory F. &
Yamori, Nobuyoshi (2012) (+)
Coleman và Cohn, (2000) (+)
Khalid (2014) (+)
Vo Tri Thanh (2011) (+)

Ricardo (2004) (+)
Ha Thi Thieu Dao (2014) (+)
Do Thị Thanh Vinh (2014) (+)
Nguyen Anh Hoang (2014) (+)

Source: Authors' synthesis based on research review
2.4. Research model and hypothesis
Hypothesis H1: Commercial banks in the Northwestern subregion use both hard and
soft information in approving loan decisions.
Hypothesis H2: Soft information plays a more important role than hard information
in a bank's lending decision.
Hard information
- Financial report
- Business plan in the future
- Loan purpose
- Business risks
- The understanding of the business
owner
- Third party comments
- Business size
- Owner characteristics
- Collateral

H1

Soft information
- Faith (Competence, Ethics, Integrity)
Social network participation
- Major lending bank
- Time of relationship

- Number of banking products

Information H2
serving loan
decisions

Loan
decision

Control variables
Age, Gender, Education,
Position, Experience,
Marriage, Number of
SME contacts / month,
Loan application

Figure 2.6: Proposed model and research hypotheses
CHAPTER 3: RESEARCH METHODS
3.1. Research design
The research order of the thesis is as follows:
Table 3.1. Order of research
Steps
1. Construction of preliminary scales
2. Scale assessment through in-depth interviews and preliminary survey
3. Formal quantitative research
4. Phân tích số liệu
5. Results and solutions


Table 3.2: Results of qualitative research on factors that are filtered into the research model

Proposal of research model
Qualitative research results
Related theory
Expected
1 Business plan
Put into research model
Asymmetric information theory
Affect
Adjust the name of factor 1:
Applied theory in banking credit management
2 Business purposes
Information about the business
3 Products, services and
potentials, risks (business
risks)
4 Business size
5 Financial report
Put into research model
Asymmetric information theory
Affect
Adjust the name of factor 2:
Applied theory in banking credit management
Financial information
Theory of the negative choice of credit markets
6 Collateral
Put into research model
Asymmetric information theory
Affect
Adjust the name of factor 3:
Applied theory in banking credit management

Information about collateral
Theory of ethical risks in banking operations
7 Credit history records
Put into research model
Applied theory in banking credit management
Affect
Adjust the name of factor 4:
Information about credit history
Theory of judgment and perception in decision
Affect
8 Trust (ability and
Put into research model
entrepreneurial personality)
making
Adjust the name of factor 4:
Information about the capacity of Applied theory in banking credit management
9 Understanding of business
business owners
owners
10 Owner characteristics
Put into research model
Asymmetric information theory
Affect
Adjust the name of factor 5:
Applied theory in banking credit management
11 3rd party opinion
Information about the personality of
the business owner
Put into research model
Adjust the name of factor 5:

Information about the personality of
the business owner
12
Asymmetric information theory
Affect
Put into research model
Participation in social networks
Adjust the name of factor 6: Applied theory in banking credit management

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Source: Author's research
3.2. Qualitative research
3.2.1. Qualitative research objectives
Refine the factors influencing the SME lending decisions of commercial banks
collected by the author in the research overview and discover new factors associated with
the reality of the context of commercial banks and SMEs in the Northwest Vietnam.
3.2.2. Object and qualitative research methods
Semi-structured interviews of 20 people: 02 deputy directors of the bank, 08 credit
managers, 10 credit officers of the Bank ... In order to ensure the representativeness of
random interview sample selection, the author chooses evenly 4-5 person / province in the
Northwest region.
3.2.3. Qualitative research results
General conclusion: basically the thesis research model proposed is appropriate.
Firstly, 100% of credit officers said that only customers who satisfy the basic criteria
will be able to access bank loans. At the same time, those 15 guiding factors were developed
by the interviewees into 52 necessary information attributes based on the actual banking
operations, the perceptions and experiences of the subjects in the process of working
lending partners for SMEs.
Second, the qualitative research results of 10 managers and credit officers of

commercial banks in the Northwest sub-region have 100% of respondents appreciate the
role of hard information in collecting classified information. Credit ratings of customers,
40% of respondents mentioned the role of soft information and revealing the relationship
network to help SMEs more easily access bank loans.
These 52 information attributes are divided into 8 main groups by the author:

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Source: Author's research

Loan decisions
H2

Information
serving loan
decisions
Soft information:
5. Information about the capacity of the business owner
6. Information about the business owner personality
7. Information about social networking participation
8. Information about the relationship with the bank

H1

Hard information:
1. Information about the business
2. Financial information
3. Information about collateral
4. Information about credit history

Asymmetric information theory
Affect
Applied theory in banking credit management
Theory of the negative choice of credit markets
Social capital theory
Source: Author's research
Diagram 3.1: Model of factors influencing lending decisions to SME customers at commercial banks in the Northwest region of
Viet Nam
13 Main lending bank
14 Time of relationships
15 Number of bank products

Qualitative research results
Information about the social network
participation of the business
Put into research model
Adjust the name of factor 7:
Information about the relationship
with the bank
Proposal of research model

13

Related theory
Social capital theory

Expected

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Specifically, 52 properties have been considered, synthesized and developed by the
author as follows:
Table 3.3: Attributes in hard information
Symbol
Properties
Source
Information about the business
DN1
Scale of SMEs
Mason,Stark (2004);
DN2
Enterprise brand recognitio
Petersen,MA.(2004;
DN3
Information about enterprise resources
Petersen,Rajan(200);
Management principles and system (strategy, structure, Berry et al. (1993);
Uchida et al. (2006);
DN4
culture, policy)
Cole,Wolken(1995).
DN5
Business outlook (products and markets)
Nguyen Anh Hoang
DN6
Business plan
(2014)
DN7
Information about customers, markets, suppliers
Financial information

TC1
Clear and professional accounting system and reporting
TC2
Revenue and profit of SMEs
TC3
Assets and capital resources of SMEs
Mason,Stark (2004);
TC4
Cash solvency ratio
Uchida et al (2006).
Nguyen Anh Hoang
TC5
Capital structure ratio
(2014)
TC6
Rate of return
TC7
Operating ratio
TC8
Statements of cash flows
Information about collateral
TSTC1
Personal assets of business owners in SMEs
Uchida et al. (2006);
TSTC2
SMEs' ability to mortgage real estate
Petersen,MA.(2004).
SMEs' ability to pledge other tangible collateral (different Nguyen Anh Hoang
(2014)
TSTC3

from real estate)
Information about credit history
LSTD1
Positive credit information in transactions with banks
LSTD2
The type and value of the mortgage for a loan in the past
LSTD3
Negative credit information in transactions with banks
Uchida et al. (2006);
LSTD4
The owner was once bankrupt
Berger,Udell (2006).
Nguyen Anh Hoang
LSTD5
Earnings and other personal financial information of the owner
(2014)
LSTD6
Utility billing record
LSTD7
Court rulings related to the business
LSTD8
Credit requests from other lenders.
Table 3.4: Properties in soft information
Symbol
Properties
Source
Information about the capacity of business owners
NLCSH1 Business owners have an educational background
Berry et al. (1993) ;
NLCSH2 Business owners have experience in the business sector

Uchida et al. (2006);
NLCSH3 Business owners have experience in management
Ravina(2008);
Petersen,MA.(2004);
NLCSH4 Business owners have the ability to make plans
Petersen,Rajan(2002);
Business owners use modern technology in business
NLCSH5
Khung et al. (2001);
management
Ferrary (2003);
NLCSH6 A business owner is good at selecting and managing


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Symbol

Properties
necessary resources
Business owners are good at understanding market
NLCSH7
changes
Business owners make a positive impression on the bank
NLCSH8
by demonstrating their knowledge and skills.
Information about the personality of the business owner
Business owners show a positive reception of banking
TSCSH1
procedures
Business owners are introduced as integrity (from a third

TSCSH2
party)
Business owners voluntarily share honest and sensitive
TSCSH3
information with the bank
Business owners have good experience working with
TSCSH4
banks
Business owners adapt their interests with those of
TSCSH5
commercial partners
TSCSH6
Business owners pay attention to the needs of employees.
Business owners are completely honest in the negotiation
TSCSH7
process with trading partners
Business owners are consistent with their actions and
TSCSH8
decisions.
Information about your business's social network participation
Business owners have a solid personal network with
MLXH1
banks and other financial institutions
Business owners have a solid personal network with
MLXH2
government officials
Business owners have a solid network with other entrepreneurs
MLXH3
in other businesses
MLXH4

Relationship with customers
MLXH5
Relationship with supplier
Information about the relationship with the bank
Number of years the business owner has a relationship
MQHNH1
with the bank
MQHNH2 The owner / business used to borrow from your bank
The owner / enterprise has the same outstanding balance at
MQHNH3
another bank
MQHNH4 Your bank is the primary bank of the SME
MQHNH5 The amount of products the entrepreneur uses at your bank

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Source
Berger (1998);
Berger,Udell (2002);
Ajagbe (2013)
Nguyen Anh Hoang
(2014)

Khung et al. (2001);
Ferrary (2003);
Berger (1998);
Berger,Udell (2002);
Ajagbe (2013)
Nguyen Anh Hoang
(2014)

Berry et al. (1993) ;
Uchida et al. (2006);
Petersen(2004);
Ferrary (2003);
Berger, Udell (2002);
Petersen,MA. (2004).
Nguyen Anh Hoang
(2014)

Uchida et al. (2006)
Nguyen Anh Hoang
(2014)

Source: Author's research
3.3. Quantitative research
3.3.1. Quantitative research objectives
- Verifying the reliability of the scale through Cronbach’alpha coefficient> 0.3 and
EFA analysis in preliminary survey, proposing the official questionnaire.
- Descriptive statistics on factors included in the research model affecting a bank's
lending decision.
- Test the reliable EFA of the official scale
- Identify factors influencing the bank's lending decision to SMEs in the Northwest
region.
- Using regression model to quantify the relationship of hard and soft information
factors that affect a bank's lending decision.
3.3.2. Design of quantitative research
Selection of quantitative research methods: survey methods.
Building scale: Level of Likert scale with 5 levels (Nguyen Anh Hoang, 2014)
Survey Table: Part A is the questions about the characteristics of the surveyed object,
Part B is the questions related to the objective of testing research hypotheses.

Table 3.5: Summary of 08 groups of factors after qualitative research
Biến
Chỉ báo
Information about the business
DN1, DN2, DN3, DN4, DN5, DN6, DN7
Financial information
TC1, TC2, TC3, TC4, TC5, TC6, TC7, TC8
Hard
Information about collateral
TSTC1, TSTC2, TSTC3
information
LSTD1, LSTD2, LSTD3, LSTD4, LSTD5,
Information about credit history
LSTD6, LSTD7, LSTD8
Information about the capacity of NLCSH1, NLCSH2, NLCSH3, NLCSH4,
business owners
NLCSH5, NLCSH6, NLCSH7, NLCSH8
Information about the personality TCCSH1, TCCSH2, TCCSH3, TCCSH4,
of the business owner
TCCSH5, TCCSH6, TCCSH7, TCCSH8
Soft
Information about your
information
business's social network
MLXH1, MLXH2, MLXH3, MLXH4, MLXH5
participation
Information about the
MQHNH1, MQHNH2, MQHNH3, MQHNH4,
relationship with the bank
MQHNH5

Table 3.6: Factors affecting, coding the question and choosing suitable scales
Selection
Factor
Survey question
Encode
scale
Scale of SMEs
DN1
Enterprise brand recognitio
DN2
DN3
Information Information about enterprise resources
Likert
about the
Management principles and system
DN4
1-5
business
Business outlook
DN5
Business plan
DN6
Information about customers, markets, suppliers
DN7


17
Factor

Financial

information

Information
about
collateral

Information
about credit
history

Information
about the
capacity of
business
owners

Information
about the
personality
of the
business
owner

18

Survey question

Encode

Clear and professional accounting system and reporting

Revenue and profit of SMEs
Assets and capital resources of SMEs
Cash solvency ratio
Capital structure ratio
Rate of return
Operating ratio
Statements of cash flows
Personal assets of business owners in SMEs
SMEs' ability to mortgage real estate
SMEs' ability to pledge other tangible collateral
Positive credit information in transactions with banks
The type and value of the mortgage for a loan in the past
Negative credit information in transactions with banks
The owner was once bankrupt
Earnings and other personal financial information of the
owner
Utility billing record
Court rulings related to the business
Credit requests from other lenders.
Business owners have an educational background
Business owners have experience in the business sector
Business owners have experience in management
Business owners have the ability to make plans
Business owners use modern technology in business
management
A business owner is good at selecting and managing
necessary resources
Business owners are good at understanding market
changes
Business owners make a positive impression on the bank

by demonstrating their knowledge and skills.
Business owners show a positive reception of banking
procedures
Business owners are introduced as integrity (from a third
party)
Business owners voluntarily share honest and sensitive
information with the bank
Business owners have good experience working with
banks
Business owners adapt their interests with those of
commercial partners
Business owners pay attention to the needs of
employees.

TC1
TC2
TC3
TC4
TC5
TC6
TC7
TC8
TSTC1
TSTC2
TSTC3
LSTD1
LSTD2
LSTD3
LSTD4
LSTD5

Selection
scale

Likert
1-5

Likert
1-5

Likert
1-5

LSTD6
LSTD7
LSTD8
NLCSH1
NLCSH2
NLCSH3
NLCSH4
NLCSH5
NLCSH6

Likert
1-5

NLCSH7
NLCSH8
TSCSH1
TSCSH2

TSCSH3
TSCSH4
TSCSH5
TSCSH6

Likert
1-5

Factor

Survey question

Encode

Selection
scale

Business owners are completely honest in the
TSCSH7
negotiation process with trading partners
Business owners are consistent with their actions and
TSCSH8
decisions.
Business owners have a solid personal network with
MLXH1
Information banks and other financial institutions
Business owners have a solid personal network with
about your
MLXH2
government officials

Likert
business's
1-5
Business owners have a solid network with other entrepreneurs
social
MLXH3
in other businesses
network
participation Relationship with customers
MLXH4
Relationship with supplier
MLXH5
Number of years the business owner has a relationship
MQHNH1
Information with the bank
The owner / business used to borrow from your bank
MQHNH2
about the
Likert
relationship The owner / enterprise has the same outstanding balance at
MQHNH3 1-5
another bank
with the
bank
Your bank is the primary bank of the SME
MQHNH4
The amount of products the entrepreneur uses at your bank
MQHNH5
3.3.3. Formal quantitative research
3.3.3.1. Select a formal quantitative research sample

The author believes that the simple random sampling is the most suitable for this
study.
Bollen (1989), with 52 observations in the questionnaire corresponding to the
minimum sample of 260, for research to ensure reliability and science, the survey sample
should be from 300-350 votes. Based on the response rate of the 100 preliminary survey
received / 100 votes received (100% response rate), however, the preliminary sample based
on the existing relationship has a very high response rate. In fact, surveys with social
surveys have response rates below 80%, usually between 50% and 60% (Cooper and
Schindler, 2006), so the author chooses the sample size to issue survey questionnaires.
Officially, 570 votes> 350 * 1.6 are used to eliminate the risks of low response rates or
interference votes, error votes.
The current situation of commercial banks with the policy of rotating staff from
departments and branches to limit ethical risks, it is difficult to determine the exact number
of officials who have examined loan applications. Based on the current status of the number
of credit officers allocated based on the size of SME customers, the study determines the
distribution rate of the questionnaire corresponding to the proportion of SMEs operating in
Hoa Binh, Son la, and Dien. Bien, Lai Chau.
Table 3.7: Distribution of the official survey
Hoa Binh
Son La
Dien Bien
Lai Chau
Total


19
SMEs (%)

38

26

20
20

16

100

Number of survey
215
150
115
90
570
Number of responses
125
95
72
63
355
The author uses the relationships available through family, colleagues and especially
the students of K20 in Finance - Banking class 2011 - 2013 at Northwestern University, (the
trainees are School and currently holding managerial positions in commercial banks) to
distribute questionnaires to 50 credit officers and ask these people to pass questionnaires to
570 credit officers at commercial banks in 4 provinces of the Northwest region. The survey
was conducted from May 2017 to September 2017 and resulted in 355 good responses
reaching 62.2% of the generated samples. According to Cooper and Schindler (2006), the
rate of recall of the questionnaire from 30% to 50% is typical for investigative studies, the
response rate of 80% or more will indicate that the respondents are very interested in the

research topic. Researchers and researchers cannot expect to receive 100% response rates.
Therefore, the response rate of 62.2% (lower than the response rate of the preliminary
survey 100%) of the study is relatively good and acceptable. Furthermore, 355
questionnaires have good data, no error sheets, blanks, omissions, or extreme selective
positive (error sheets = 0), demonstrating the quality of the questionnaire and the very
method of data collection effective with investigative research.
3.3.3.2. Methods of data analysis
CHAPTER 4: RESEARCH RESULTS
4.1. The current status of loans of commercial banks to small and medium enterprises
in the Northwest sub-region
4.1.1. Criteria for classifying SMEs in commercial banks in the Northwest region Bắc
Research situation at commercial banks in the Northwestern sub-region of Vietnam has a
very clear and specific classification of SMEs according to each criterion and field of activity.
4.1.2. Loan process and credit limit for SMEs at commercial banks in the Northwest
subregion of Vietnam
4.1.3. Process of credit scoring for SME customers in the Northwest region
Table 2.3: Role of hard information - soft information in credit decision
Audited financial
Non-audited financial
statements
statements
Bank
Targets
DN
DN
DN tư
DN tư
DNNN
DNNN
nhân ĐTNN

nhân ĐTNN
Agribank
Financial indicators (%)
25
35
45
35
45
55
ABBank
Non-financial
75
65
55
65
55
45
indicators (%)
Vietcombank Financial indicators (%)
40
36
50
60
55
60
LienViet
Non-financial
60
65
50

40
45
40
Post Bank
indicators (%)
BIDV
Financial indicators (%)
25
30
45
35
45
50
Non-financial
75
70
55
65
55
50

MBbank
Vietinbank

indicators (%)
Financial indicators (%)
Non-financial
indicators (%)

25

75

30
70

Source: Synthesized author's bank credit handbook
4.1.4. Commercial banks' banking services for SMEs in the Northwest sub-region
4.1.3. Size of commercial bank lending to SMEs in the Northwest sub-region
Of the four provinces in the Northwest sub-region, 38% of SMEs operate in Hoa Binh
province, however Son La province still plays a key role in lending to SMEs.
4.1.4. Credit structure of SMEs in the Northwest sub-region
According to the type of business
According to economic sector
Over the term
4.1.5. Lending profits for SMEs in the Northwest region
In the period of 2013 - 2018, the average proportion of profit from SME lending / Profit
from credit activities was about 24.25%.
4.1.6. Credit quality for SMEs in the Northwest region
The total value of collateral for SMEs loans in the Northwest tends to increase rapidly
over the years in both absolute and relative terms.
4.1.7. SME credit rating at commercial banks in the Northwest region
Most of the SMEs in the Northwest are at low risk, corresponding to the
disbursement of loans only about 80% of the total capital needs. However, 2% - 4% of
SMEs are being converted to bad debt.
4.2. Descriptive statistics of the object of the survey
4.2.1. Statistics of surveyed object characteristics
4.2.2. The statistics describe information that influences commercial banks'
lending decisions
Information on collateral was the most important source of information for
commercial banks' lending decisions and was scored by respondents as the highest among

the information groups.
4.3. Verify the reliability of the scale
4.3.1. Verifying the conformity of the scale
The Cronbach alpha analysis results were all high, the highest reliability index was
the collateral group (0.926), only the group of variables about the financial situation was
0.67 but still acceptable. However, there are observed variables with total variable
correlation coefficients <0.3 and give higher Cronbach alpha level if we exclude the
variable, it shows that the information components are not correlated with the total variable,
so it should be removed. Therefore, 17 variables are observed: DN1, DN2, DN7, TC1, TC2,
TC3,TC8, NLCSH1, NLCSH4, NLCSH8, TCCSH3, TCCSH5, TCCSH6, MLXH2,


21
MQHNH5, LSTD2, LSTD6, LSTD7 Removed to ensure reliability with Cronbach's alpha's
highest.
4.3.2. Discovery factor analysis
The results of the discovery factor study have 5 factors that are identified and renamed, and
encoded variables based on the mean value as follows:
Table 4.22: Group of factors determined after EFA test
Variable group name
New variable
Observed variables
set again
encoding
NLCSH2, NLCSH3, NLCSH5,
NLCSH6, NLCSH7
Factor 1 TCCSH1, TCCSH2, TCCSH4,
Social Capital Information
VXH_TB
TCCSH7, TCCSH8

MLXH1, MLXH3, MLXH4, MLXH5
TC4, TC5, TC6, TC7
Business information and
Factor 2
TCDN_TB
DN3, DN4, DN5, DN6
financial situation
Factor 3 LSTD1, LSTD3, LSTD4, LSTD5, LSTD8 Credit history information
LSTD_TB
MQHNH1, MQHNH2, MQHNH3,
Relationship information
Factor 4
MQHNH_TB
MQHNH4
with the bank
Factor 5 TSTC1, TSTC2, TSTC3
Collateral Information
TSTC_TB
4.3.3. The results analyze the importance of information used in loan appraisal
The survey data sheet shows that 05 groups of independent variables do not have
similar correlation with each other, the model does not have multi-collinearity phenomenon.
Coefficients Sig. of the dependent variable of guaranteed loan decision <0.05,
proving that 04 groups of variables have an impact on the lending decision of commercial
banks, the coefficient Sig of Social Capital factor is .783> 0.05, representing multiplication
factors have no influence on the lending decisions of commercial banks
4.4. The regression of multiple factors influencing the lending decisions of
commercial banks
4.4.1. Regression of multiple factors influencing
The second correlated regression model has a fairly accurate interpretation of a
bank's lending decision. The model predicted a loan approval rate with an accuracy of

93.6%, while the interpretation of the decision not to lend had a lower rate of 82.1%,
however the rate This is still quite high, in aggregate, the model can accurately explain
90.1% of the respondents' loan decisions, so the model is appropriate.
4.4.2. Summary of regression coefficient for lending decisions
After the second Binary Logistic test guarantees the coefficients Sig. < 0,05
The regression equation is written as follows:
Y = -19,975 + 2,386 * Collateral + 1,739 * Relationship with the bank + 1,521 *
Credit history + 1,010 * Financial situation

22
Explain Y = loge [

]with the values 1 when choosing with loan and 0 when

choosing not to loan.
Regression test results confirm that hard information (collateral) plays an important
role in the lending decisions of commercial banks.
CHAPTER 5: DISCUSSION OF RESULTS AND RECOMMENDATIONS
5.1. Discuss research results
5.1.1. Results answer the first research hypothesis
Commercial banks in the Northwestern subregion use both hard and soft information
collected from customers to serve their lending decisions. Including 04 groups of hard and
soft information as follows: Financial situation; Credit history information; Information
on collateral; Relationship with the bank.
These 04 information groups forecast about 90.1% of commercial banks' lending
decisions.
Table 5.1: Research results
Factor
Expected
Research results

Information about the business
Hard
information

Financial information
Information about collateral
Information about credit history

There is an
influence
There is an
influence
There is an
influence
There is an
influence
There is an
influence
There is an
influence
There is an
influence
There is an
influence

There is an influence
There is an influence
There is an influence
There is an influence

Not affected
Information about the capacity of
business owners
Not affected
Information about the personality of the
Soft
business owner
Not affected
Information about your business's social
information
network participation
There is an influence
Information about the relationship
with the bank
The research results of the thesis are concur and also different from the results of
previous studies that in the credit approval process, credit institutions evaluate both hard
information and information. Soft is collected from customers.
5.1.2. The results answer the second research hypothesis
In the hard and soft information collected to serve the loan decision, the information
about: Financial situation, Credit history, Collateral, Relationship with the lending bank are
all meaningful. Explain lending decisions of commercial banks.
In which: Hard information is the most important in the loan decision
(collateral), when the collateral increases by 1 unit, the ability of banks to approve loans
for SMEs increases by 10,874 times. => The survey results contradict the author's


23

24

hypothesis that soft information (Competence, participation in social networks;
personality of the business owner) plays an important role in the SME lending decision of
commercial banks.

Third, SMEs in the Northwest region need to proactively define business plans and
business prospects based on timely grasping of government support policies, maintaining
safe financial indicators ( solvency ratio, operating ratio, capital structure ratio, rate of
return) to meet the requirements of commercial banks and use loans most effectively.
Fourth, SMEs need to strengthen linkages with lenders.
Fifth, SMEs have a plan to minimize dependence on collateral by understanding the
benefits of buying hedging insurance in business.
Sixth, SMEs in the Northwest region need to link production - consumption along the
value chain to minimize dependence on collateral.
5.2.4. Recommended to relevant organizations
The bank of Viet Nam
Association of SMEs in the Northwest sub-region of Vietnam
5.4. Limitations of the thesis and the next research direction
First: There are a number of factors that can influence a loan decision but have not
been studied and included. Therefore, in the next study, these factors should be added to the
study to have higher practical results.
Second: The study only mentioned the role of hard information more important than
soft information, going against the internal credit granting process at commercial banks in
the Northwest, but there is no in-depth analysis of the price of the role of each type of
information as well as the basis for building the internal credit rating set of commercial
banks.

Hypothesis

Result

H1: Commercial banks use both soft and hard information at the same time in
the process of making loan decisions.

Accept

H2: Soft information plays a more important role than hard information in
commercial banks' lending decisions.

Rejected

Interpretation of the dissertation's research results: Commercial banks in the Northwestern
subregion believe that hard information is the number one priority when approving loans for SMEs.
5.2. Some recommendations
5.2.1. Recommendation to commercial banks - Head office
First, the credit policies should be perfected towards equality for SMEs.
Second, the head office commercial banks need to improve internal credit policy
associated with reality in order to limit credit risks and promptly respond to loans for SME
customers.
Thirdly, head office commercial banks need to study and supplement the missing
criteria in the set of criteria for credit rating of corporate customers.
5.2.2. Recommendation to commercial banks - Branches in the Northwest sub-region
First, commercial banks need to design specific products that are suitable for SME
customers in the Northwest region.
Second, commercial banks in the Northwest subregion need to strengthen
coordination with local management levels
Third, commercial banks in the Northwest subregion need to catch up with the global
trend that is focusing on developing the economic sector in the value chain to reduce the
pressure on collateral for businesses.
Fourth, commercial banks in the Northwest sub-region need to have a flexible
measure of collateral (receiving assets outside real estate ...).

Fifth, commercial banks in the Northwest sub-region need to build a mechanism to
share information of stakeholders.
Sixthly, commercial banks need to train credit institutions with ability and skills to
collect and process hard information - reliable soft information, in order to minimize the
problem of asymmetric information in the current financial market.
5.2.3. Recommended for SMEs in the Northwest
Firstly, SMEs in the Northwest need to make financial information transparent.
Second, SMEs in the Northwest need to take advantage of the support policies of the
State and local governments.