Factors Affecting Depositors’ Behavior at ommercial Banks in Northern Vietnam45305

EDESUS Proceeding 2019 (156 of 1531) Factors Affecting Depositors’ Behavior at ommercial Banks in Northern Vietnam Le Trung Thanh(1)*, Vu Thi Phuong Thao(2)
 (1) VNU University of Economics and Business, Vietnam National University, Hanoi, Vietnam (2) Thuyloi University, Hanoi, Vietnam * Correspondence: ltthanh@vnu.edu.vn Abstract: This study evaluates the impact of factors affecting depositors' behavior at commercial banks in Northern Vietnam The research uses data by surveying questionnaires collected from 1000 depositors at branches of Vietnamese commercial banks in the North of Vietnam to find out factors affecting people's saving habits as well as their behaviors when they received information about the financial crisis The results show that age, sex, education, and marital status influence the behavior of depositors And after receiving unfavorable information about the financial market, the more the money sender trustthe official sources of information, the less they tend to withdraw their money Keywords: Behavior; depositors; commercial banks; financial crisis Introduction Mobilized capital has a decisive meaning and it is the source for the bank to carry out lending, investment, reserving, etc that bring profits for the bank In order to obtain this capital, the bank needs to conduct capital mobilization activities, in which capital mobilized from deposits accounts for a particularly important role In the world, the phenomenon of a bank run (a large number of people withdraw their money from a bank because they believe the bank may cease to function in the near future) is not rare and causes serious consequences Normally, these cases stem from the suspicion of people with bank liquidity This suspicion may stem from an accurate analysis of the economic and financial situation, but may also stem from the combination of rumors and herd psychology (Nagaoka and Takemura, 2009) Therefore, studying the behavior of depositors based on the theory of behavioral finance will help banks have appropriate policies to mobilize capital effectively and ensure liquidity for the whole system In the world, many types of research on the behavior of choosing a bank for transactions have been made The most representative study of the bank selection model is the model of five elements of Anderson et al (1976) They argued that the five main factors affecting the decision of choosing a bank include a recommendation from friends, the bank's reputation, bank credit, bank staffs’ attitude, and transaction fees Martenson (1985), Ta & Har (2000) showed that recommendations from friends and parents are extremely important EDESUS Proceeding 2019 (157 of 1531) factors in choosing a bank Later, Laroche et al (1986) and Ying & Chua (1989) presented the concept of banking services and identified the factors affecting depositors’ decision in choosing the banks Other studies also showed that other criteria such as convenience (including location, quality of service) are also important in selecting bank (Dupuy and Kehoe, 1976; Thwaites and Vere, 1995) Analyzing selection criteria of retail banking in the UK, through survey, Devlin (2002) thought that financial knowledge affected customers' choice of banks Specifically, customers who have limited financial knowledge tend to choose banks following their position or recommendation from friends and relatives while the group of people with better financial knowledge is interested in banking services, profit rate, and interest rate This conclusion is not in line with the study of Lee and Lou (1996) when they argued that factors outside the bank had more impact on the group of customers with higher financial literacy And family relationships are more important for financially literate groups because they tend to talk openly on such issues with family members Yada (2008), Yada et al (2010), Washio et al (2008) built a model of a bank operating during the financial crisis with three main causes (system errors, bank scandals, and natural disasters) The authors estimated the total amount of money that customers withdraw at a bank when the depositors suspect their bank's solvency, and they found the factors affecting the depositors' behavior include the position as well as the action of big depositors on that bank Takemura and Ukai (2008) modeled the decision-making process, in which depositors are determined whether or not to withdraw their deposits after receiving uncertain information about the financial market In particular, Takemura and Kozu (2009) conducted a survey covering 1500 depositors, who believe that depositors' behavior is influenced by magazine, Internet, and conversations with friends or colleagues Besides, depositors' behavior is also affected by personal characteristics of depositors such as their gender, education, and income Krisnanto (2011) studied the bank's customer selection factors including creditworthiness, credit quality, bank staffs’ attitude, interest rates, positions, and some secondary factors such as a friend's recommendation and advice from family members In Vietnam, the authors mainly use survey methods when they focus on the factors affecting the fluctuation of deposit Le (2012) studied depositors’ behavior through a survey of 904 customer questionnaires According to the author, there are factors that affect depositors behavior: customer care policies, employees and simple procedures Truong et al (2015) studied the impact of financial knowledge on the decision to send money from farmers in An Giang province The data used in this study were collected from a questionnaire with 398 people The probit estimation results show that farmers' financial knowledge is positively correlated with their decision to deposit money into local commercial banks with the control of elements of the characteristics of the family The results of this study imply that in order to increase capital mobilized from farmers, commercial banks should have programs to improve their financial knowledge Le and Tran EDESUS Proceeding 2019 (158 of 1531) (2016) studied the factors affecting the decision to choose a savings deposit bank in Tuy Hoa and Phu Yen cities, showing: Safety; Convenience; Service quality; Financial benefits; Promotion form; The influence of related people is positively related to the choice of bank Hoang (2017) studied the factors affecting the decision to choose the savings deposit bank of individual customers in Hue through survey data of 267 individual customers in Hue The results show that there are factors that positively affect the decision to choose a bank, which comprise brand reputation, financial benefits, the influence of relatives, marketing, employees and the facilities Nguyen et al (2018) studied the behavior of depositors in the Vietnamese banking system, including depositors’ saving habits, their understanding of deposit insurance and research model of depositors behavior in the Vietnamese banking system in the 2007-2013 period Since then, the authors propose many solutions to consolidate the trust of depositors to maintain stable deposit growth, contributing to the stability of the banking system Thus, research on depositors' behavior in the world as well as in Vietnam is quite common However, research on their behavior when receiving adverse information about the financial market in general and the banking system, in particular, is still small Therefore, the study focused on investigating factors affecting depositors' behavior as well as their behavior on their deposits when there is information about the financial crisis Methodology 2.1 Data processing Logical regression models are widely used to build decision-making models in the fields of psychology, society, economy and economic management In particular, the probability of occurrence is p, with logit distribution in logit form (p) = log (p / 1-p) In this study, the author uses a model that has been applied by Toshihiko Takemura and Takashi Kozu (2009) in “An empirical analysis using individual data collected through a Web-based survey” Independent variables In the model, the sender withdraws all deposits after receiving adverse financial market information and the bank they deposit represents the depositors' behavior The probability that the sender withdraws all deposits after receiving adverse information about the financial market and the bank they deposit is p The explanatory variables for this probability are concretized into gender, age, educational level, living area, marital status, average income, reliability of the information, frequency of access information of depositors; understanding of deposit insurance The relationship between the independent variable and the dependent variable through the formula: log (p / 1-p) = a + b_1 X_1 + b_2 X_2 + b_3 X_3 + b_4 X_4 + b_5 X_5 + b_6 X_6 + b_7 X_7 In which: p = if the sender withdraws all the money EDESUS Proceeding 2019 (159 of 1531) otherwise Dependent variable X1 variable – gender X1 = if the depositor is male, = otherwise X2 variable - age The depositors are divided into groups: the group under 30 years old (those who start working, not have many accumulated assets); groups from 30 to 60 years old (those who have worked for a while, jobs have been stable and have accumulated assets); group over 60 years old (those who are at retirement age, have accumulated assets but are no longer working so income reduced) To perform the evaluation of differences between groups, we add dummy variables X2A and X2B Inside: X2A = if the depositors are from 30 to 55 years old for women, to 60 years for men = otherwise X2B = if depositors are over 55 years old for women, over 60 years for men = otherwise X3 variable - education The education variable is divided into groups: the group with high school graduation or lower, the group graduating from university, the group graduating from graduate school To perform the evaluation of differences between groups, add dummy variables X3A and X3B Inside: X3A = if depositors belong to university graduates = otherwise X3B = if depositors belong to a graduate group = otherwise X4 variable - marriage status Marriage status expresses the different reaction between single and married depositors when they receive adverse information about the financial market and the bank where they deposit X4 = if the depositor is married = if the depositor is single X5 variable - average monthly income EDESUS Proceeding 2019 (160 of 1531) The monthly average income variable is divided into groups: the group with income below million, the group from million to 10 million, the group from 10 million to under 15 million, the group from 15 million to 20 million and the group from 20 million above In order to assess the differences between groups, we put the fake variable X5A, X5B, X5C, and X5D X5A = if depositors are in the group of million to 10 million = with other cases X5B = if depositors belong to groups of 10 million to under 15 million = with other cases X5C = if the depositors belong to the group from 15 million to 20 million = with other cases X5D = if depositors are in the group of 20 million or more = with other cases X6 variable - reliability of information source We assume sources of information such as television, newspaper, e-newspaper, Internet, email, phone from friends, information from neighbors, and information from people at work as the sources of information that depositors receive from their surroundings In particular, the X6A variable represents the source of information from television, newspaper, electronic newspaper, and is considered to have higher reliability And the X6B variable represents the source of information from email, phone friends, from neighbors, from the workplace, the Internet and is considered to have a lower level of confidence The reliability of the information is divided into levels: (1) I never trust the information source; (2) I not trust it; (3) Sometimes I trust, sometimes I not trust; (4) I trust it; and (5) I strongly trust it X7 variable - how often to update information Turning information updates regularly tells us the different responses between never-updated depositors and those with updated financial market information, about the banks they send when they receive the information Adverse news about the financial market and their bank deposits This variable receives a value of if the sender has updated and receives a value of if the depositor is not updated 2.2 Data collection Data source: The author collects data by directly surveying depositors through questionnaires at commercial banks in Northern Vietnam EDESUS Proceeding 2019 (161 of 1531) Survey content Survey contents need to study the following basic issues: - Factors affecting the behavior of depositors - The behavior of depositors to their deposits when there is information about the financial crisis Scope of the survey A sample size of the survey: 1,000 observations The number of survey samples is divided according to the locations of bank branches in the North of Vietnam Table Allocating the number of surveyors to depositors in the northern regions of Vietnam Scope of the survey Number of samples Ha Noi 100 West North 200 East North 300 Red river delta 400 Total 1.000 (Source: The authors’ calculations) Results Through surveys, most depositors can choose to send savings at 1-2 banks Specifically, 54.6% of respondents only send money at one bank, 29% choose to deposit money at banks The number of depositors deposit money at banks or more is only 2.4% Through the table below, it can be seen that single people tend to prefer to send at one bank and married people tend to send at more than banks more than single people Table 2: Statistics of the number of banks sending customers Number of banks currently sending money Single Marital status Married Total 154 55 62.3% 22.3% 8.9% 392 235 57 52.1% 31.2% 546 54.6% Total >5 247 5.3% 0.4% 0.8% 100,0% 34 13 22 753 7.6% 4.5% 1.7% 2.9% 100,0% 290 79 47 14 24 1000 29% 7.9% 4.7% 1.4% 2.4% 100,0% 22 13 (Source: The authors’ calculations) Being asked about the factors affecting the choice of depositors' saving forms, up to 51% of respondents selected safety as the leading factor they were interested in when choosing saving forms, followed by the profitability Therefore, the bank's prestige factor is also the first priority factor of depositors in choosing banks to deposit money (55%), followed by interest rates The bank's position or the bank's staff attitude is the next two factors However, when considering the two-way relationship between the factors of bank selection and the gender of the depositors in this survey sample, it can be seen that female EDESUS Proceeding 2019 (162 of 1531) depositors tend to prioritize the choice of reputable banks while male depositors tend to prefer attractive interest rates and closer to home Table 3: Statistics of priority depositors Factors affecting the choice of depositors Male Gend er Fema le Total Banks’ Attractive Positi The attitude of bank Othe prestige interest rate on staffs rs 384 158 63 51 58.0% 23.9% 9.5% 7.7% 0.9% 166 98 48 25 49.1% 29.0% 14.2% 7.4% 0.3% 550 256 111 76 55.0% 25.6% 11.1% 7.6% 0.7% Total 662 100.0 % 338 100.0 % 1000 100.0 % (Source: The authors’ calculations) Table 4: Description of model variables Y X1 X2A X2B X3A X3B X4 Mean 0.5989 0.4256 0.6783 0.0792 0.6389 0.1347 0.801 Median 1.0000 0.0000 1.0000 0.0000 1.0000 0.0000 1.0000 Maximum 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 Minimum 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 Std, Dev, 0.5271 0.6342 0.5168 0.2974 0.4276 0.3645 0.4086 Skewness -0.5983 0.7032 -0.5874 3.0236 -0.7424 2.3788 -1.296 Kurtosis 1.4985 1.5052 1.345 9.2986 1.4327 6.621 2.8160 Jarque-Bera 169.45 176.07 173.5 3207.4 171.04 1502.8 288.44 Probability 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 Sum 646.00 335.00 638.0000 89.000 634.00 115.00 769.00 Sum Sq, Dev 229.15 219.53 230.750 80.4 229.09 103.06 175.52 Observations 996 1000 997 997 998 998 1000 (Source: The authors’ calculations) Y X5A X5B X5C X5D X6A X6B X7 Mean 0.7248 0.397 0.2411 0.0897 0.0945 3.2501 2.9906 0.8115 Median 1.0000 0.0000 0.0000 0.0000 0.0000 3.0000 3.0000 1.0000 Maximum 1.0000 1.0000 1.0000 1.0000 1.0000 5.0000 5.0000 1.0000 Minimum 0.0000 0.0000 0.0000 0.0000 0.0000 1.0000 1.0000 0.0000 Std, Dev, 0.3775 0.5062 0.4232 0.2952 0.2943 0.8768 0.7638 0.3985 Skewness -0.6350 0.2524 1.4047 2.6253 2.8634 -0.2260 -0.1611 -1.7223 Kurtosis 1.4118 1.1655 2.8476 8.5186 8.7352 3.5387 4.5018 3.593 Jarque-Bera 173.46 167.64 341.30 2508.3 2589.1 19.205 90.769 467.32 EDESUS Proceeding 2019 (163 of 1531) Probability 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 Sum 645.00 435.00 221.00 98.000 96.000 3245.0 2902.0 817.00 Sum Sq, Dev 225.17 246.03 170.2 88.124 86.075 771.2 597.86 149.97 Observations 998 998 1000 1000 998 998 997 1000 (Source: The authors’ calculations) Table 5: Logit regression results Variable Coefficient Std Error z-Statistic Prob X1 0.258045 0.160325 1.609512 0.1178 X2A -0.423455 0.206855 -2.047110 0.0403 X2B -0.691812 0.320430 -2.159011 0.0256 X3A 0.345823 0.179022 1.931735 0.0709 X3B 0.305564 0.259855 1.175902 0.2555 X4 0.365886 0.196683 1.860283 0.0800 X5A 0.159422 0.243492 0.654732 0.4723 X5B -0.220641 0.248420 -0.888177 0.3955 X5C -0.238262 0.308744 -0.771713 0.4382 X5D 0.062249 0.305418 0.203815 0.8187 X6A 0.199899 0.100146 1.996076 0.0281 X6B 0.115302 0.103553 1.113454 0.2655 X7 1.141707 0.186764 6.113100 0.0000 C -1.968148 0.431341 -4.562864 0.0000 Observation 1000 Log-likelihood -569.4626 LR statistic 136.9728 McFadden R2 0.097683 (Source: The authors’ calculations) Significant variables: X2A X2B X6A X7 at 5% significance level The variables not make sense: X1 X3A X3B X4 X5A X5B X5C X5D X6B at 5% significance level However, X3A and X4 variables are significant at the 10% level The coefficient McFadden R-squared is 0.097683, meaning that the variables in the model explain 9.77% of the variation of the dependent variable The p-value of the coefficient LR equal to indicates that the general model is statistically significant The coefficients in the model not mean that the marginal contribution of that variable is negligible The coefficients in the model are significant, the marginal contribution of that variable is explained as follows: - The X2A variable has an estimated coefficient of -0.42 = which means that depositors from the age group 30 to 55 for women, to 60 years for men tend to withdraw more money than the group under 30 years old More specifically, with other variables constant, the proportion of depositors in the age group from 30 to 55 for women, to 60 for EDESUS Proceeding 2019 (164 of 1531) men compared to other groups is exp (0.42) = 1,284 That means the ability of women to withdraw money from the age of 30 to 55 for women to 60 for men is 28.4% higher than for other groups - X2B variable with an estimated coefficient of -0.69 means that depositors over 55 years of age for women, over 60 years for men tend to withdraw more money than those under 30 when receiving adverse information about Financial markets and banks they deposit money - The X6A variable has an estimated coefficient of 0.19 meaning that when receiving unfavorable information about financial markets and depositors' banks, depositors are more confident of official sources of information (television, paper newspapers, electronic newspapers), the tendency to withdraw less money - The X3A variable has an estimated coefficient of 0.35, meaning that depositors of college graduates tend to withdraw less money - The variable X4 has an estimated coefficient of 0.36, meaning that the depositors of the married group tend to withdraw less money More specifically, with the condition that other variables remain unchanged, the proportion of depositors in married groups compared to unmarried groups is exp (0.36) = 1,233 That means the ability of the married group to withdraw money is less than 23.3% Conclusions First, the model uses the factors including gender, age, educational level, marital status, average income, reliability of the information, frequency of access to information of depositors, which are able to explain the behavior of depositors Second, the depositors’ behavior is measured by the response of depositors who will withdraw all deposits after receiving adverse information about the financial market and the bank or not Third, the results from the model have shown the important factors of depositor behavior From these findings, relevant parties can provide appropriate policies to protect depositors and stabilize the amount of money mobilized from the population Fourth, with 5% significant level, the factors affecting the withdrawal of depositors are explained as follows: - Depositors aged from 30 to 55 for women, and from 30 to 60 for men tend to withdraw more money than depositors under 30 years old Specifically, provided that other factors remain unchanged, when they receive adverse information about the financial market and the banks, the proportion of depositors aged from 30 to 55 for women, and from 30 years to 60 years of age for men who are able to withdraw money higher than those under 30 years old by 28.4% EDESUS Proceeding 2019 (165 of 1531) - Women over 55 years and menover 60 tend to withdraw more money than the group under 30 when receiving adverse information about the financial market and their bank - Depositors with a bachelor degree tend to withdraw less money than new depositors with high school diploma or below - Depositors from married groups tend to withdraw less money than unmarried depositors Specifically, provided that other factors remain unchanged, when receiving adverse financial market information and their bank, the proportion of married depositors is likely to withdraw less than the unmarried group by 23.3% - When receiving adverse information about the financial market and their banks, the more the money sender believes in the official sources of information (television, newspaper, electronic newspaper), the less chance they tend to withdraw their money - The remaining factors such as gender, the average income of depositors not affect the withdrawal and deposit of depositors References Anderson Jr., W.T., Cox III, E.P and Fulcher, D.H (1976) Bank selection decisions and market segmentation Marketing, 40(1), 40–45 Devlin, J.F (2002) Customer knowledge and choice criteria in retail banking Strategic Marketing, 10(4), 273–290 Dupuy, G.M., Kehoe, W.S (1976) Comments on bank selection decisions and marketing segmentation Marketing, 40(4), 89–91 Hoang, T.A.T (2017) Researching the factors affecting the decision to choose the savings deposit bank of individual customers in Hue Science and Technology, 20, 96 Krisnanto (2011) The Customers’ Determinant Factors of the Bank selection International Research Journal of Business Studies 4(1), 59 Laroche, M., Rosenblatt, J.A and Manning, T (1986) Services used and factors considered important in selecting a bank: an investigation across diverse demographic segments The International Journal of Bank Marketing, 4(1), 35–55 Le, T.K.A., Tran, D.K.N (2016) Study the factors affecting the decision to choose a savings bank in Tuy Hoa city - Phu Yen province Economic & Development 228, 76-84 Le, T.T.H (2011) Bank savings deposit behavior of individual customers Psychology, 7, 84 Lee, M., Lou, Y.C (1996) Consumer reliance on intrinsic and extrinsic cues in product evaluations: a conjoint approach Applied Business Research 12(1), 21–8 Martenson, R (1985) Customer choice criteria in retail bank selection The International Journal of Bank Marketing, 3(2), 64–75 EDESUS Proceeding 2019 (166 of 1531) Nagaoka, H., Takemura, T (2009) Case Studies of Bank Run in Financial Institutions: Suggestion from Viewpoint of Risk Management The proceeding of the 2nd International Conference on Social Sciences 3, 27-42 Nguyen, V.T (2016) Depositors 'behavior and factors affecting depositors' behavior in the Vietnamese banking system Ministry-level research topics Ta, H.P., Har, K.Y (2000) A study of bank selection decisions in Singapore using the analytical hierarchy process The International Journal of Bank Marketing, 18(4), 170–180 Takemura, T., Kozu, T (2009) Statistical analysis on an Individual's depositwithdrawal behavior: an empirical analysis using individual data collected through a Webbased survey The proceeding of 2009 Hawaii International Conference on Social Sciences, 811-829 Takemura, T., Ukai, Y (2008) A Note on Financial Behavior Modeling from a Webbased Survey The Proceeding of International Conference of Socionetwork Strategies and Policy Grid Computing 2008, 163-165 Thwaites, D., Vere, L (1995) Bank selection criteria – a student perspective Marketing Management, 11, 133–149 Truong, D.L., Vo, V.D., Pham, T.Y.N (2015) The relationship between financial knowledge and money transfer decisions of farmers in An Giang province The role of banks and public science applications technology in agricultural and rural development, 246-253 Yada, K., Washio, T., Ukai, Y and Nagaoka, H (2009) Modeling bank runs in financial crises The Review of Socionetwork Strategies, 3(1), 19–31 Ying, L.C., Chua, A (1989) Customer bank selection: bank marketing implication Malaysian Management Review, 24(3), 55–67  ... behavior when receiving adverse information about the financial market in general and the banking system, in particular, is still small Therefore, the study focused on investigating factors affecting. .. to update information Turning information updates regularly tells us the different responses between never-updated depositors and those with updated financial market information, about the banks. .. Proceeding 2019 (157 of 1531) factors in choosing a bank Later, Laroche et al (1986) and Ying & Chua (1989) presented the concept of banking services and identified the factors affecting depositors’