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

1 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) 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 3 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 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 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 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 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 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 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 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) 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 Source: author's synthesis 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 Udell (2006) (+) Mason Stark (2004) (+) Uchida et al (2006) (+) Armstrong et al (2010) (+) Financial report Feldma (1997) (+) Mester (1997) (+) Nguyen Anh Hoang (2014) (+) Hard Business plan Petersen Rajan (2002) (+) information Business purposes Berry et al (1993) (+) Petersen,MA (2004) (-) Uchida et al (2006) (-) Products, services and Armstrong et al (2010) (-) potentials, risks Agarwal Hauswald (2010) (-) (business risks) Berry et al (1993) (-) Nguyen Anh Hoang (2014) (+) Berry et al (1993) (+) Uchida et al (2006) (+) Rand (2007) (-) Knowledge Coleman (2004a) (-) Le, Sundar, & Nguyễn (2006) (+) Nguyen Anh Hoang (2014) (-) Berry et al (1993), (+) 3rd party opinion Uchida et al (2006) (+) Nguyen Anh Hoang (2014) (-) Cole 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) (-) Irwin & Scott (2010) (+) Owner characteristics Nofsinger & Wang (2011) (+) Fatoki & Asah (2011) (+) Numerical order Influence factor 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 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 Udell (2006) (+) Nguyen Anh Hoang (2014) (+) Berger (1998) (+) Berger Udell (2002) (+) Petersen,MA (2004) (+) Xin 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 Udell, (1995) (+) Petersen Rajan, (1994, 1995) (+) Angelini, P et al, (1998) (+) Scott Dunkelberg, (1999) (+) Ongena Smith, (2000) (+) Uchida (2006) (+) Uchida, Hirofumi, Udell, Gregory F & Yamori, Nobuyoshi (2012) (+) Coleman 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 Construction of preliminary scales Scale assessment through in-depth interviews and preliminary survey Formal quantitative research Phân tích số liệu 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 Business plan Put into research model Asymmetric information theory Affect Adjust the name of factor 1: Applied theory in banking credit management Business purposes Information about the business Products, services and potentials, risks (business risks) Business size 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 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 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 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 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 11 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 main groups by the author: 12 Source: Author's research Loan decisions H2 Information serving loan decisions Soft information: Information about the capacity of the business owner Information about the business owner personality Information about social networking participation Information about the relationship with the bank H1 Hard information: Information about the business Financial information Information about collateral 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 14 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 15 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 16 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 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 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 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  ... (20 02) ; Ajagbe (20 13) Nguyen Anh Hoang (20 14) Khung et al (20 01); Ferrary (20 03); Berger (1998); Berger,Udell (20 02) ; Ajagbe (20 13) Nguyen Anh Hoang (20 14) Berry et al (1993) ; Uchida et al (20 06);... Rajan (20 02) (+) Uchida et al (20 06) (+) Khung et al (20 01) (+) Petersen (20 04) (+) Tran Trung Kien (20 15) (+) Nguyen Thi Minh Hue (20 12) (+) Nguyen Anh Hoang (20 14) (+) Uchida et al (20 06) (+)... Thanh (20 11) (+) Ricardo (20 04) (+) Ha Thi Thieu Dao (20 14) (+) Business size Do Thị Thanh Vinh (20 14) (+) Le (20 12) (+) Malesky & Taussig (20 09) (+) Nguyen & Ramachandran (20 06) (+) Rand (20 07)