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MINISTRY OF EDUCATION TRAINING STATE BANK OF VIET NAM BANKING UNIVERSITY HO CHI MINH CITY TRẦN THIÊN PHÚC ENABLING FINANCIAL INCLUSION THROUGH FINTECH GRADUATION THESIS MAJOR FINANCE – BANKING CODE 73[.]
MINISTRY OF EDUCATION TRAINING STATE BANK OF VIET NAM BANKING UNIVERSITY HO CHI MINH CITY TRẦN THIÊN PHÚC ENABLING FINANCIAL INCLUSION THROUGH FINTECH GRADUATION THESIS MAJOR: FINANCE – BANKING CODE: 7340201 HO CHI MINH CITY, 2021 Tai ngay!!! Ban co the xoa dong chu nay!!! MINISTRY OF EDUCATION TRAINING STATE BANK OF VIET NAM BANKING UNIVERSITY HO CHI MINH CITY TRẦN THIÊN PHÚC ENABLING FINANCIAL INCLUSION THROUGH FINTECH GRADUATION THESIS MAJOR: FINANCE – BANKING CODE: 7340201 SUPERVISOR HẠ THỊ THIỀU DAO Assoc Prof, PhD HO CHI MINH CITY, 2021 ABSTRACT Financial inclusion is an issue of global concern with the goal of developing a financial system that serves all society members, providing appropriate and convenient services at an affordable cost for all individuals and businesses, contributing to the country's sustainable development Indeed, Decision No 149/QD-TTg highlights the goal "at least 80% of adults will have bank accounts." dated on 22 January 2020 in Vietnam New financial technologies (fintech) are seen as key enablers of financial inclusion This study uses probit regression to examine the impact of fintech on financial inclusion by using the Global Findex database The study uncovers new evidence that fintech is a key to enable financial inclusion The main findings are fintech (proxy via mobile phone used to use of specific services, mobile phone used to pay utility bill, mobile phone used to receive the payment, mobile phone ownership) and other determinants such as the education and income, which have positive and statistically significant relationship with financial inclusion Overall, the study's results offer recommendations to policymakers in Vietnam i COMMITMENT This thesis is the author's study The research results are honest in that there is no previously published content or other content done by someone else except fully cited citations in the thesis Ho Chi Minh City, ………………………………… Author Trần Thiên Phúc ii ACKNOWLEDGEMENTS After four years of studying at the Banking University of Ho Chi Minh City, I achieved a lot of knowledge and experience from talented, devoted, and enthusiastic lecturers, who always support students and improve academic development Firstly, I would like to express my gratitude to my family, who always encourage and care for me My sister has been my wonderful caregiver since starting my project, and I want to thank her for all the supports she has given me Secondly, I cannot thank my supervisor, Hạ Thị Thiều Dao, Assoc Prof, Ph.D., enough for the efforts you have given me to support me to finish the project successfully Finally, last but by no means least, thank you to all my colleagues who has shared their valuable feedback to complete my publication iii TABLE OF CONTENTS ABSTRACT i COMMITMENT ii ACKNOWLEDGEMENTS iii CHAPTER INTRODUCTION 1.1 RESEARCH MOTIVATION 1.2 RESEARCH OBJECTIVE 1.2.1 Overall objective 1.2.2 Specific objectives 1.3 RESEARCH QUESTIONS 1.4 RESEARCH SUBJECT AND SCOPE 1.5 RESEARCH METHODOLOGY 1.5.1 Regression method 1.5.2 Data sources 1.6 RESEARCH CONTRIBUTION 1.7 RESEARCH STRUCTURE CHAPTER LITERATURE REVIEW 2.1 DEFINITIONS AND MEASUREMENT 2.1.1 Fintech definition 2.1.2 The measurement of fintech 10 2.1.3 Financial inclusion definition 14 2.1.4 The measurement of financial inclusion 15 2.2 REVIEW OF PREVIOUS STUDIES 17 iv 2.2.1 Fintech and financial inclusion 17 2.2.2 Financial inclusion and other determinants 20 CHAPTER METHODOLOGY 24 3.1 REGRESSION METHOD 24 3.1.1 Binary model 24 3.1.2 Estimation 25 3.2 TESTING 27 3.2.1 Wald test 27 3.2.2 The Lagrange multiplier or score test 28 3.3 RESEARCH DATA 29 3.4 RESEARCH MODEL 30 CHAPTER RESULTS AND DISCUSSION 33 4.1 FINANCIAL INCLUSION AND FINTECH 33 4.1.1 Financial inclusion 33 4.1.2 Fintech 33 4.2 FINANCIAL INCLUSION AND OTHERS DETERMINANTS IN VIETNAM 34 4.2.1 Financial inclusion and gender 34 4.2.2 Financial inclusion and income 35 4.2.3 Financial inclusion and education 36 4.3 EMPIRICAL RESULTS 37 4.3.1 Statistics 37 4.3.2 Testing results 38 4.3.3 Discussion 38 CHAPTER CONCLUSIONS AND RECOMMENDATIONS 45 5.1 CONCLUSIONS 45 5.2 RECOMMENDATIONS 48 v 5.3 LIMITATIONS AND FUTURE RESEARCH 50 vi LIST OF ABBREVIATIONS AFI Alliance of Financial Inclusion AI Artificial Intelligence ASIC Australian Securities & Investments Commission ATM Automated Teller Machines eKYC electronic Know Your Customer EVN Electricity of Vietnam FI Financial Inclusion Fintech Financial technology GDP Gross Domestic Product GPFI The Global Partnership for Financial Inclusion GSMA Global System for Mobile Communications ICF Information & Communication Technologies IFI Index of Financial Inclusion IMF International Monetary Fund PCA Principal Component Analysis SBV State Bank of Vietnam SFA Singapore Fintech Association SME Small and Medium Enterprise SMS Short Message Services UK United Kingdom USA United States of America vii LIST OF FIGURES AND TABLES Table 2.1 Measurement of Fintech 11 Table 2.2 Fintech indicators 12 Table 2.3 The Summary table of literature review on the determinants of financial inclusion 21 Table 3.1 Definition and measurement of variables 30 Table 4.1 Adult with an account (%) 33 Table 4.2 Adults with mobile money account (%) 34 Table 4.3 Aldults with utility bill payments (%) 34 Table 4.4 The size of the gender gap in account ownership (%) 35 Table 4.5 Poorer adults are less likely than wealthier ones to have an account (%) 36 Table 4.6 Less-educated adults are less than well-educated ones to have an account (%) 36 Table 4.7 Summary statistics 37 Table 4.8 The determinants of financial inclusion in Vietnam 39 Table 5.1 Mobile cellar subscriptions and individuals using Internet in Vietnam 47 Figure 5.1 Adult having the formal account 46 Figure 5.2 Individual accounts 46 viii Hua, X., & Huang, Y (2020) Understanding China‘s fintech sector: development, impacts and risks The European Journal of Finance, 1-13 Huyền, P T (2019) Ứng dụng Fintech thúc đẩy tài tồn diện Việt Nam Tạp chí Khoa học & Đào tạo Ngân hàng, 209(10), 36-45 Jakhiya, M., Bishnoi, M M., & Purohit, H Emergence and Growth of Mobile Money in Modern India: A Study on the Effect of Mobile Money In 2020 Advances in Science and Engineering Technology International Conferences (ASET) (pp 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New financial technologies (fintech) are seen as key enablers of financial inclusion Before investigating the impact of fintech on financial inclusion, some definitions must clarify Financial inclusion definition According to the World Bank, Financial inclusion means that individuals and businesses can access useful financial products and services at reasonable prices, including remittance, payment, savings, credit, and insurance, provided responsibly and sustainably Accordingly, Financial inclusion is determined by the following three criteria: (i) Access to financial services; (ii) Use of financial services; (iii) Quality of products and services delivered Simultaneously, access to account transactions is the first step towards expanding financial inclusion, as a trading account allows all citizens to store money, send and receive payments Financial inclusions' definition is broader and more multidimensional, emphasizing the quality aspect of service Accordingly, Financial inclusion provides users with available financial services at an affordable cost, makes customers use financial services regularly, offers financial services to users' needs Financial inclusion is not limited to improving access to credit, improving citizens' financial literacy, and protecting consumers Fintech definition According to Karakas & Stamegna (2017), fintech stands for financial technology, which is a broad term used mainly to refer to companies using technology- based systems in some way To provide services directly or to try to make the financial system more efficient Initially, this term referred to technology applied to support the operations of commercial and standards firms Today, the fintech interpretation has expanded to include any new financial sector changes, including new changes in financial education and training, retail banking, investment, or innovation Fintech operations progress and expression have also become synonyms for services finance that emerged in the 21st century Fintech encompasses a wide range of services and products in the foreground, such as payments using money, loans, business, consulting, fundraising, virtual money, and projects will expand further in the coming years According to World Bank (2017), Financial technology -Fintech- is creating new opportunities and challenges for the financial sector – from consumers to financial institutions and regulators Fintech offers many opportunities for governments, from making their financial systems more efficient and competitive to broadening access to financial services for the under-served populations However, it can also pose potential risks to consumers and investors and, more broadly, to financial stability and integrity After clarifying the definitions of fintech and financial inclusion, which leads to the question "How to measure the fintech and financial inclusion?" The fintech measurement Fintech measurement in Fintech measurement in Authors this study previous studies Mobile phone used to use Mobile money account Abayaa et al of specified services Ouma et al., (2020) (2020); Mobile phone used to pay Mobile for payment of the Asongu et al (2019) utility bill et al (2020); bill ;Nagpal Demir et al., (2020) Mobile phone used to Digital payment Nagpal et al (2020) receive payment Owning a mobile phone Mobile phone penetration Morawczynski & Kpodar (2012); Abor et al (2018) The financial inclusion measurement To suitable in the research context in Vietnam This study will calculate financial inclusion through account ownership because owning an account is an important first step toward financial inclusion (Word Bank, 2017) An account is a fundamental product to access financial markets, savings and credit are essential services to expand and improve financial inclusion However, having accounts and using accounts are two different things, and reality shows that the next step countries need to promote financial inclusion is how to increase account ownership Moreover, owning an account is an important first step toward financial inclusion (Word Bank, 2017) Furthermore, following Decision No 637/Q -NHNN, promoting financial inclusion, and enhancing individuals (age 15+) having an account at the financial institution, at least 70 percentages are financial inclusion in Vietnam Therefore, in line with Demirgüc Kunt & Klapper (2012) and Cámara & Tuesta (2014) having an account at the financial institution is financial inclusion in this study To evaluate the impact of technology on financial inclusion, the author uses the Binary Logistics regression model with the following general form to analyze the impact of fintech and other factors on financial inclusion in Vietnam This study's new point focuses on non-bank financial institutions' services, such as digital payments services and electronic banking services The following relationship captures this approach: Details: - Y is the dependent variable measuring financial inclusion, takes the value of if the individual has an account at a financial institution, and otherwise - X is a set of independent variables measuring the individual's characteristics - Fintech is a set of independent variables measuring financial technology such as financial services payment through mobile phone Data sources: The author uses survey data from the World Bank's Global Findex 2017, published in April 2018 This data is collected through surveys of more than 150,000 adults over 15 in more than 140 countries by Gallup, Inc It includes individuals' characteristics and modernized details of the manner respondents access financial services From 2011 to 2017, once each three years, about 1000 respondents are chosen to interview randomly 1002 respondents representing about 81 percent of the population (excluding 11 provinces: Nghe An, Thanh Hoa, Kien Giang, GiaLai, Dak Lak, Ha Giang, Ha Tinh, Kien Giang, Kon Tum, Quang Binh, An Giang, and Dien Bien with the target "population is the civilian, non-institutionalized population 15 years and above." The mobile money account is not explored in the 2011 database, so the panel data is non-necessary to examine the tendency of financial inclusion Due to two respondents did not meet the information requirements Therefore, in line with the previous study, the author focus on the variable account ownership as a key financial inclusion indicator with 1000 respondents in Vietnam Findings of the study is providing an overview of the trends of fintech, financial inclusion and other determinants in Vietnam: Fintech indicates including mobile phone used to use of specific services, mobile used to pay utility bill, mobile phone used to receive the payment, owning a mobile phone have a statistical significance and positive coefficient Financial inclusion is influenced by an individuals‘ characteristics Education and income are indicators playing a key role in enabling financial inclusion Other factors, including age, age2 also have statistical significance to financial inclusion The decision to participate in the financial system first step of individuals is not affected by gender in Vietnam despite some research all over the world whose have significant Recommendations are offered from the finding of this study: On the one hand, State Bank and government must have sustainable cooperation in researching and proposing solutions to explain new models and technologies, such as (i) Implementation of using mobile money accounts for small value goods and services (ii) Completing the application for the formulation of a Decree on a controlled trial management mechanism for Fintech activities in the banking sector; (iii) Researching to supplement appropriate legal regulations for products, models, services, payment means associated with the industrial revolution 4.0 such as digital banking, electronic know your customer (eKYC), researching blockchain technology in the payment sector; applying Big Data, Artificial Intelligence (AI) technology to many banking areas Currently, many domestic banks have applied advanced technology and new solutions to payment activities to increase payment speed, enhancing service safety and security, increasing customer experience and satisfaction such as biometric verification (fingerprint, face); payment on Quick response (QR code); Tokenization; contactless payment; Payment on mobile point of sale (mPOS) On the other hand, the vulnerable group like the less-educated and poverty adults who are lack of instruments to access financial inclusion So it is necessary to strengthen the education community Besides, good policies may be issued by community educators and policymakers to improve financial literacy so as to promote the living standard Instruments such as microfinance or social banking should be developed for low-income adults to access Moreover, easing financial institutions‘ requirements may create more chances for them to access financial products APPENDICES Probit regression results Iteration 0: Iteration 1: Iteration 2: Iteration 3: Iteration 4: Iteration 5: log likelihood = -632.75321 log likelihood = -501.58816 log likelihood = -496.14174 log likelihood = -496.03661 log likelihood = -496.03636 log likelihood = -496.03636 Probit regression Number of obs LR chi2(13) Prob > chi2 Pseudo R2 Log likelihood = -496.03636 account_fin P>|z 5974684 303716 1.97 0.049 002196 1.192741 mobilephoneowner 4004222 1633762 2.45 0.014 0802107 7206337 payment_received 1.416739 6086807 2.33 0.020 2237468 2.609731 utilitybill_payment 1.94355 68411 2.84 0.004 6027193 3.284381 0560296 0189179 2.96 0.003 0189513 0931079 age2 -.0007557 0002173 -3.48 0.001 -.0011817 -.0003297 age Std Err 1,000 273.43 0.0000 0.2161 z account_mob Coef = = = = [95% Conf Interval] female 0349455 0931072 0.38 0.707 -.1475413 2174323 education_pri 7094495 1159402 6.12 0.000 4822109 9366882 education_ter 1.54188 1587634 9.71 0.000 1.23071 1.853051 income_2nd 053093 1643573 0.32 0.747 -.2690414 3752275 income_3rd 0658578 1631756 0.40 0.687 -.2539605 385676 income_4th 2017211 1563421 1.29 0.197 -.1047038 5081461 income_5th 3060414 1533873 2.00 0.046 6066749 _cons -2.522899 4225476 -5.97 0.000 -3.351077 -1.694721 0054079 Wald test [account_fin]account_mob = [account_fin]mobilephoneowner = [account_fin]payment_received = [account_fin]utilitybill_payment [account_fin]age = [account_fin]age2 = [account_fin]female = [account_fin]education_sec = [account_fin]education_ter = [account_fin]income_2nd = [account_fin]income_3rd = [account_fin]income_4th = [account_fin]income_5th = chi2( 13) = 183.03 Prob > chi2 = 0.0000 The lagrange multiplier test [account_fin]c.xbhat#c.account_mob = [account_fin]c.xbhat#c.mobilephoneowner = [account_fin]c.xbhat#c.utilitybill_payment = [account_fin]c.xbhat#c.payment_received = [account_fin]c.xbhat#c.age = [account_fin]c.xbhat#c.age2 = [account_fin]c.xbhat#c.female = [account_fin]c.xbhat#c.education_sec = [account_fin]c.xbhat#c.education_ter = [account_fin]c.xbhat#c.income_2nd = [account_fin]c.xbhat#c.income_3rd = [account_fin]c.xbhat#c.income_4th = [account_fin]c.xbhat#c.income_5th = chi2( 13) = 3.21 Prob > chi2 = 0.9971 Correlation account _fin acccount_ fin account_ mob mobileph oneowner uitilitybill _payment payment_ receive age age2 female income_2 nd income_3 rd income_4 th income_5 th education _sec education _ter account _mob mobilep honeow ner utilitybil Payment l_payme _reveive nt age age2 1.0000 0.1863 0.0000 0.2064 0.0000 0.1718 0.0000 0.1718 0.0000 -0.2461 0.0000 -0.2530 0.0000 -0.0227 0.4732 -0.0446 0.1590 -0.0438 0.1660 0.0198 0.5314 0.1808 0.0000 0.0782 0.0134 0.3505 0.0000 1.0000 0.0502 0.1123 0.2314 0.0000 0.4875 0.0000 -0.1247 0.0001 -0.1141 0.0003 0.0166 0.6009 -0.0304 0.3361 -0.0046 0.8846 0.0262 0.4077 0.0839 0.0079 0.0202 0.5235 0.1116 0.0004 1.0000 0.0565 0.0739 0.0352 0.2659 -0.2587 0.0000 -0.3002 0.0000 -0.1084 0.0006 -0.0281 0.3744 -0.0211 0.5044 0.0302 0.3400 0.1512 0.0000 0.1476 0.0000 0.1371 0.0000 1.0000 0.1622 0.0000 -0.0659 0.0371 -0.0617 0.0510 -0.0275 0.3850 -0.0213 0.5002 0.0167 0.5987 -0.0293 0.3551 0.0678 0.0321 -0.0400 0.2063 0.1444 0.0000 1.0000 0.0931 0.0032 -0.0819 0.0096 0.0038 0.9048 -0.0213 0.5002 -0.0032 0.9190 0.0279 0.3781 0.0499 0.1150 -0.0245 0.4386 0.1444 0.0000 1.0000 0.9812 0.0000 0.0513 0.1053 -0.0347 0.2736 0.0383 0.2257 -0.0163 0.6071 -0.1109 0.0004 -0.2130 0.0000 -0.1918 0.0000 1.0000 0.0515 0.1038 -0.0358 0.2586 0.0341 0.2813 -0.0260 0.4119 -0.1078 0.0006 -0.2148 0.0000 -0.1800 0.0000 female female income_2 nd income_3 rd income_4 th income_5 th education _sec education _ter 1.0000 0.0404 0.2015 -0.0300 0.3440 0.0030 0.9238 -0.0532 0.0929 -0.1046 0.0009 -0.0038 0.9050 income_ income_ income_ income_ educatio educatio 2nd 2nd 2nd 2nd n_sec n_ter 1.0000 -0.2240 0.0000 -0.2401 0.0000 -0.2691 0.0000 0.0838 0.0080 -0.0810 0.0104 1.0000 -0.2450 0.0000 -0.2745 0.0000 0.0415 0.1900 -0.0789 0.0125 1.0000 -0.2943 0.0000 -0.0002 0.9950 0.0003 0.9915 1.0000 0.0174 0.5823 0.2196 0.0000 1.0000 -0.4143 0.0000 1.0000