Variable group
Variable name | Encoded measurement value | Source of documents | |
X7 | Current job position | 1-Business owner, 2-Manager, 3-Office staff/specialists, 4-Vocational trained workers, 5-Other | Marjo Hörkkö (2010), Truong D. Loc & Nguyen T. Tuyet (2011) |
X8 | Customer's financial capacity | 1-Under 10 million, 2-From 10 to under 40, 3-From 40 million to under 80, 4-From 80 million to under 120 million, 5-120 million or more | Marjo Hörkkö (2010), John M. C (1940) |
X9 | Housing conditions | 1-Owned, 2-Rented, 3-Living with parents, 4- Staying with others | Marjo Hörkkö (2010), Nguyen T. M Thao (2016) |
X10 | Professional competence | 1-Postgraduate, 2- Undergraduate, 3- College, 4- Intermediate, 5- Other | Marjo Hörkkö (2010), Nguyen T. M Thao (2016) |
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3.4. Data processing method
3.4.1. Descriptive statistics
Based on the collected data, the author uses descriptive statistics to describe the current situation of individuals who have borrowed capital at Vietinbank Ba Ria Vung Tau branch in terms of: demographic size; gender; education; number of dependents; occupation.....
3.4.2. Processing Binary logistic regression model
General form model
In multiple regression, the independent variable Xi and the dependent variable Y are continuous variables related through the equation:
𝑖=1
Y = B0 + ∑ 𝑛 𝐵𝑖𝑋𝑖 + u (1)
With Xi being the independent variable; Y being the dependent variable.
In Logistic regression, the dependent variable Y has only two states: 1 (Individual has credit risk) and 0 (Individual has no credit risk). To convert it to a continuous variable, we calculate the probability of these two states. If P is the probability that the event occurs (the possibility that the individual has credit risk), then 1-P is the probability that the event does not occur (Individual has no credit risk). The Logistic regression equation is stated:
( 𝑃(𝑌=1)
𝐿𝑛
) = 𝐵0 + 𝐵1𝑋1 + 𝐵2𝑋2 + ⋯ + 𝐵𝑖𝑋𝑖 (2)
𝑃(𝑌=0)
Where P(Y=1) = P 0 : Probability of event occurrence : Probability of individual having credit risk .
In which P(Y=0) =1 - P 0 : Probability of no event occurring : Probability of individual having no credit risk
Xi : independent variables.
Ln : Log of base e (e = 2.714)
The relationship between theory and research: An individual with credit risk (debt groups 2,3,4,5) is an expected value of the topic (called variable Y), and an individual without credit risk is the remaining value of the expected variable. Individual customers with credit risk are identified through a system of explanatory variables, which are variables measuring gender, age, marital status, family status, occupation, time
Time spent at current address, current job position, customer's financial ability, housing conditions, professional capacity.
Assessing the personal factors affecting the credit risk of individual customers, the model for assessing personal credit risk, or no personal credit risk is the Logit (Binary Logistics) model used for cases where the dependent variable has only 2 values, usually these two values are coded as "1" or "0". In which, each value represents a specific value of the dependent variable. Determining which object "1" or "0" belongs to, which value of the dependent variable does not affect the results of the model.
Odds
O 0 = 𝑃0 1−𝑃0
O 0 = 𝑃0 1−𝑃0
= 𝑃(return on investment)
𝑃(The price of the product is too high)
Substitute into (2) we get: Ln(Odds) = B0 + B1X1 + B2X2 + …+ BiXi (3)
This is a form of Logit function. From this we can deduce that the Ln function of the Odds coefficient is a linear regression function with independent variables Xi.
Binary Logistic regression forecast function form:
E( 𝑌 ) = 𝑃
= e B0 + B1X1 +B2X2 + …+ BiXi
𝑋𝑖 1−𝑃
E(Y/Xi) : Probability that Y = 1 occurs when the independent variable Xi has a specific value. e B0 + B1X1 + B2X2 + …+ BiXi
P =
1 + e B0 + B1X1 + B2X2 + …+ BiXi
Regression function form of the proposed research model in chapter 3:
Ln(Pi/1-Pi)= 0 + 1* X1 + 2* X2 + 3* X3+ 4* X4 + 5* X5 + 6* X6 + 7 *
8* X8 + 9* X9 + 10* X10 + u i
Including: gender (X1), age (X2), marital status (X3), family status (X4), occupation (X5), time living at current address (X6), current job position (X7), customer's financial capacity (X8), housing conditions (X9), professional capacity (X10).
3.4.3. Tests in Binary logistic regression model
Model fit testing
To test the general suitability of the logistic regression model, we use the 2LL (-2 Log Likelihood) index. This measure has the same meaning as SSE (Sum of squares of error), meaning that the smaller the index, the better. The smallest value of -2LL is 0 (meaning no error), then the model has a perfect fit (Hoang Trong and Chu Nguyen Mong Ngoc, 2008).
Testing the statistical significance of coefficients
In linear regression, we use the t-test to test the hypothesis H 0 . In Binary logistic regression, the Wald estimate is used to test the statistical significance level (sig.) of the overall regression coefficient. The sig. level for the Wald test is at the 5% significance level. If the sig. level < 5%, the independent variable has a significant impact on the dependent variable.
General suitability test
Use the Chi-square test to check the overall goodness of fit of the binary regression model. Based on the significance level of the Chi-square coefficient in the Omnibus table, decide to reject or accept the hypothesis H0.
CHAPTER 3 SUMMARY
In Chapter 3, the author presents the research method, the research implementation process from the expert survey stage to the official survey sample selection process. At the same time, he presents the data analysis method used in the research, with the regression analysis method with binary variables, showing the probability of credit risk problems arising for customers.
CHAPTER 4: RESEARCH RESULTS
4.1. Introduction to Vietnam Joint Stock Commercial Bank for Industry and Trade - Ba Ria Vung Tau Branch
4.2. 1. Mission, vision
As a branch bank of Vietinbank, the mission and vision of Vietinbank is also the mission and vision of Vietinbank Ba Ria Vung Tau branch.
* Mission
Striving to make Vietinbank the number 1 bank in the Vietnamese banking system, providing modern, convenient, international standard financial and banking products and services.
* Vision
Making Vietinbank the bank with the largest total assets and leading operational efficiency in the Vietnamese banking industry. Aiming to become a modern banking and financial group according to international standards.
* Core values
- Customer-oriented: “VietinBank is committed to providing consistent products, services and service styles; a VietinBank that can best meet all the needs of all customers”.
- Honesty - integrity - transparency: "VietinBank's leadership team, officers and employees always think and act to ensure fairness, integrity, transparency and responsibility".
- Sustainable development and responsibility to the community and society: “Innovation and creativity are the driving force; growth, development, safety, efficiency, sustainability”.
4.2.1. Formation and development process
March 26, 1988: Vietnam Joint Stock Commercial Bank for Industry and Trade was established under Decree No. 53/HDBT of the Council of Ministers on the organization of the State Bank of Vietnam.
November 14, 1990: Vietnam Joint Stock Commercial Bank for Industry and Trade was transformed into Vietnam Bank for Industry and Trade (Decision No. 402/CT of the Council of Ministers).
The management work is innovated in the direction of: implementing the centralized management and operation role of the head office, while promoting the advantages and proactive role of the branches within the framework of decentralization and authorization of the Board of Directors.
March 27, 1993: According to Decision No. 67/QD-NH5 of the Governor of the State Bank of Vietnam, a State-owned enterprise named Vietnam Joint Stock Commercial Bank for Industry and Trade was established.
September 21, 1996: Re-establishment of the Vietnam Joint Stock Commercial Bank for Industry and Trade (Decision No. 285/QD-NH5 of the Governor of the State Bank of Vietnam).
Since 2001, we have continued to comprehensively innovate business operations, develop products and services, organize management, and modernize the bank according to the bank restructuring project approved by the Government.
In 2008, the Vietnam Joint Stock Commercial Bank for Industry and Trade changed its international transaction name in English and its English abbreviation according to Decision No. 196/QD-NHNN.
Figure 4.1: Image of Vietinbank Ba Ria Vung Tau branch
(Source: Vietinbank Ba Ria Vung Tau branch, 2019)
Main results achieved.
Vietnam Joint Stock Commercial Bank for Industry and Trade has developed a network in all provinces and cities nationwide and reached out internationally with 01 Transaction Center, 152 Branches (CN) including 149 domestic branches, 2 branches in Germany and 1 branch in Laos and over 1000 Transaction Offices/Savings Funds.
Founding member and joint venture partner of INDOVINA Bank.
Being the first bank in Vietnam to open a branch in Europe, marking a remarkable development of Vietnam's finance in the regional and world markets. Continuously researching, improving existing products and services and developing new products.
Over 30 years of establishment, construction and development, Vietnam Joint Stock Commercial Bank for Industry and Trade has marked the process of transforming the traditional business model into a new modern model including: retail, wholesale, professional business activities according to each customer group. Vietnam Joint Stock Commercial Bank for Industry and Trade has been and continues to affirm its position as a large, key, leading commercial bank in Vietnam, always effectively implementing the national monetary policy, contributing to promoting the socio-economic development of the country.
Vietnam Joint Stock Commercial Bank for Industry and Trade - Ba Ria Vung Tau Branch was established in 1991 after separating from the State Bank.
On July 1, 2009, Vietnam Joint Stock Commercial Bank for Industry and Trade - Ba Ria Vung Tau Branch changed its name to Vietnam Joint Stock Commercial Bank for Industry and Trade - Ba Ria Vung Tau Branch according to Decision 496/QD-HDQT NHCT1 of the Chairman of the Board of Directors of Vietnam Joint Stock Commercial Bank for Industry and Trade. After 30 years of establishment and development, Vietinbank Ba Ria Vung Tau Branch has affirmed its reputation and brand in the Vietinbank system as well as in the banking industry in Ba Ria Vung Tau province.
The total number of employees at Vietinbank Ba Ria Vung Tau branch as of August 31, 2016 is 165 workers, including 105 women and 60 men. Specifically: