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BỘ GIÁO DỤC VÀ ĐÀO TẠO NGÂN HÀNG NHÀ NƯỚC VIỆT NAM TRƯỜNG ĐẠI HỌC NGÂN HÀNG TP HỒ CHÍ MINH lu an va n V TH HƯNG B NH ie gh tn to U TỐ TÁC ĐỘNG Đ N N p CÁC w ẤU CỦA d oa nl CÁC NGÂN HÀNG THƯ NG MẠI TẠI oi lm ul nf va an lu VIỆT NAM z at nh KHÓA LUẬN TỐT NGHIỆP CHUYÊN NGÀNH: TÀI CHÍNH – NGÂN HÀNG z MÃ SỐ: 7340201 m co l gm @ an Lu n va TP HỒ CHÍ MINH, NĂM 2018 ac th si BỘ GIÁO DỤC VÀ ĐÀO TẠO NGÂN HÀNG NHÀ NƯỚC VIỆT NAM TRƯỜNG ĐẠI HỌC NGÂN HÀNG TP HỒ CHÍ MINH lu an va n V TH HƯNG B NH gh tn to U TỐ TÁC ĐỘNG Đ N N ẤU CỦA p ie CÁC nl w CÁC NGÂN HÀNG THƯ NG MẠI TẠI d oa VIỆT NAM va an lu ul nf KHÓA LUẬN TỐT NGHIỆP oi lm CHUYÊN NGÀNH: TÀI CHÍNH – NGÂN HÀNG z at nh MÃ SỐ: 7340201 z gm @ NGƯỜI HƯỚNG DẪN KHOA HỌC m co l TS NGU ỄN TRẦN PH C an Lu TP HỒ CHÍ MINH, NĂM 2018 n va ac th si TÓM TẮT KHÓA LUẬN Nghiên cứu đƣợc thực nh m x c đ nh nh ng y u t ảnh hƣởng đ n nợ xấu c c ngân hàng thƣơng mại Việt Nam Trong đó, bi n đo lƣờng nợ xấu NHTM tỷ lệ nợ xấu (NPL-Non performing loans) C c bi n thể y u t kinh t vĩ mô là: tăng trƣởng kinh t (GrGDP); tỷ lệ lạm ph t (INF); tỷ lệ thất nghiệp (UNE); lãi suất cho vay trung bình (AWPR) Ngồi việc phân t ch ảnh hƣởng môi trƣờng kinh t vĩ mô đ n nợ xấu ngân hàng, nghiên cứu c n bổ sung thêm m t s bi n vi mô, đại diện cho y u t n i b ngân hàng c ng góp phần thấy đƣợc nh ng t c đ ng ngân hàng đ n nợ xấu NHTM nhƣ: tỷ lệ chi ph thu nh p (OPE), suất lu an sinh lợi tài sản (ROA), tỷ lệ dƣ nợ t n dụng tổng tài sản (LA), dự ph ng rủi ro cho n va c c khoản nợ xấu (LLP), quy mô ngân hàng (lnSIZE), tỷ lệ nợ xấu năm trƣ c (NPLt-1) to ên cạnh đó, nghiên cứu c n đ nh gi thực trạng v nợ xấu ảnh hƣởng đ n n n kinh t gh tn Việt Nam giai đoạn 2008-2016 p ie Nghiên cứu sử dụng phƣơng ph p hồi quy GMM (Generalized method of moments) cho d liệu nghiên cứu bảng (Panel regression), bao gồm 29 NHTM Việt nl w Nam giai đoạn 2008-2016 d oa Nghiên cứu cung cấp hiểu bi t v m i quan hệ gi a môi trƣờng kinh t vi an lu mô l n vĩ mô đ i v i nợ xấu c c Ngân hàng Thƣơng mại Do đó, k t nghiên cứu va thực nghiệm lu n văn có ch cho c c Ngân hàng Thƣơng mại, c c nhà đầu tƣ ll oi m rủi ro xảy u nf việc đƣa c c ch nh s ch, quy t đ nh đầu tƣ để đem lại hiệu cao hạn ch z at nh z m co l gm @ an Lu i n va ac th si ABSTRACT In business activities of commercial banks, credit is the most important activity, accounting for the major proportion It directly affects the performance of a bank, which determines the development or failure of the organization, the economy of the country Besides, credit activities always face credit risks in general and nonperforming loans in particular Non-performing loans are one of the main factor influencing the sustainability of Vietnam’s financial system Therefore, this study aims to examine the determinants of Non-performing Loans in the Vietnam base on based on empirical studies of other countries with similar characteristics, which contribute as lu an experimental evidence it is essential to make policy recommendations to guide and va adjust the non-performing loans accordingly So the authors decided to implement the n Research has done the study of the theoretical foundations, definitions, the gh tn to research “ Factors effecting non-performing loans of commercial banks in Vietnam.” p ie empirical studies in other countries as well as the empirical researches in Vietnam to w indicate the research gap for thesis to steer towards implementation Besides, studying oa nl the author forms the analysis framework and research model for thesis topics Next, d the thesis has a system of basic definitions of credit risks and non-performing loans, an lu distributing debt group, objective and subjective reasons relate to non-performing u nf va loans as well as analysis of microeconomics and macroeconomic impact to nonperforming loans in Vietnam’s commercial banks The brief survey of previous ll oi m empirical studies in the world and in Vietnam also helps identify research model z at nh This study was conducted to determine the factors affecting non-performing loans of commercial banks in Vietnam The variables representing macroeconomic z factors are: GDP growth rate (GrGDP); Inflation rate (INF); Unemployment rate @ gm (UNE); Average Prime Lending Ratio (AWPR) The thesis also adds a number of l micro variables, which represent the internal factors of the bank, also contribute to the m co impact: Operating Expense to Income (OPE), Return on Assets (ROA), Loan to assets an Lu (LA), Loan loss Provisions (LLP), Bank Size (lnSIZE), Non Performing Loans of the n va ii ac th si previous year (NPLt-1) In addition, the study also assesses the current status of nonperforming loans affecting the economy in Vietnam in the period 2008-2016 In chapter 3, the thesis introduces research methods to the problem of factos impact of non-performing loans commercial banks in Vietnam in the period 20092016 by identifying the research hypothesis, data, models and variables in the modelstudy It also presentsthe research facility to continue in chapter which performs quantitative research, tests disabilities of the model and fix them Here, the author gives an overview of the data, the study variables used in the model The study uses the Generalized method of moments (GMM) regression for panel regression data, including 29 commercial banks in Vietnam for the period 2008-2016 The study lu an provided an insight into the relationship between micro and macroeconomic n va environments for NPLs in commercial banks Therefore, the results of empirical tn to research in the thesis are very useful for commercial banks, investors in making policies and investment decisions to bring high efficiency and reduce the risk when it gh p ie occurs Besides introducing the operational status of banking system Chapter is the oa nl w quantitive analysis steps Firstly, a quantitative analysis tool was used to analyze the impact of micro and macro factors on the NPLs of commercial banks with the d an lu dependent variable NPL ratio The regression models obtained from the REM and va FEM method have self-correlation and variance of variance and endogenous variables ll u nf in the model To overcome these defects, the author uses the GMM estimation method oi m to analyze the influence of factors The results show that GrGDP, ROA, LA, OPE, NPLt-1 have the opposite effect on bad debt ratios and CPI variables, UNE impacts in z at nh the same direction on NPL ratios The results also show that AWPR, LLP, lnSize have z no meaning in the model This is the basis to improve the efficiency of commercial @ banks in Vietnam gm l Although the issue of NPLs in Vietnam was quite sensitive due to some political m co problems, the research has got some significant empirical results implying the impact of bank management on its NPLs To get the targeted NPLs ratio, the Vietnamese an Lu commercial banks should consider adjusting their Loan-to-asset ratios, their types of n va iii ac th si ownerships, their previous-year-NPLs even with suspicious relationships, and the weak effect of the bank’s total asset The difficulties facing the process of the empirical model have implied several problems with regard to the data availability and consistency Although it is easy to collect the data from the annual report of commercial banks in Vietnam, the number of NPLs given to the public might not be precise Comparing the NPLs ratio of Vietnam published by international institutions and the SBV, the result showed an extremely different situation In addition, the public annual report of commercial banks might also contain inaccurate numbers such as the numbers in the balance sheet, the cash flow and so on Although the model result gave us quite a good number of all variables, however, the R-sq of it was relatively small lu an As a result, the study was able to conclude that even though bank-level factors had real n va influences on the changes in NPLs, the relationship was quite weak This requires the Through this paper, the author provides empirical evidence on the relationship gh tn to regulation of data transparency and consistency from the State Bank of Vietnam p ie between bad debt and the factors affecting bad debt in the Vietnam banking system In terms of science, research contributes to the completion of studies on the impact of oa nl w micro and macroeconomic environment on bad debts of commercial banks Topics provide empirical evidence to test and supplement the results for previous studies In d an lu practice, research results are a reference for bank managers Research has shown the va influence of macroeconomic factors as well as the internal factors that banks can ll u nf control impact on the bad debt ratio of banks This contributes to improve the oi m performance of each bank in particular and the whole banking system in general in the context of Vietnam integration and the impact of the global economy today z at nh The author would like to propose the next research to improve the idea of the z topic First of all, the paper will expand the size of the sample that is specifically @ increasing the number of years selected for research in subsequent years Next, the gm l topic will observe more banks or foreign bank branches, as the involvement of foreign m co elements in the banking system of Vietnam is further deepened, the classification of property studies (banks, private banks and foreign banks) to see the impact of this an Lu factor on the increase of bad debt is necessary Finally, the dissertation is limited to the n va iv ac th si study of quantitative factors, without considering qualitative factors, such as employee productivity, credit procedures, How does each bank's source of credit affect bad debt? The research will continue to focus on the elements mentioned above Further research can provide more specific guidance for managers to come up with the most appropriate strategies for managing bad debt and sustainability lu an n va p ie gh tn to d oa nl w ll u nf va an lu oi m z at nh z m co l gm @ an Lu n va v ac th si LỜI CAM ĐOAN Tôi V Th Hƣng ình, sinh viên l p HQ02 – GE01 thu c khoa Tài ch nh – Ngân hàng trƣờng Đại học Ngân hàng TP.HCM Tơi xin cam đoan khóa lu n cơng trình nghiên cứu riêng tơi, k t nghiên cứu trung thực, khơng có c c n i dung đƣợc cơng b trƣ c n i dung ngƣời khác thực ngoại trừ trích d n đƣợc d n nguồn đầy đủ khóa lu n Tp Hồ Ch Minh, ngày th ng năm 2018 T c giả lu an n va tn to p ie gh V Th Hƣng ình d oa nl w ll u nf va an lu oi m z at nh z m co l gm @ an Lu n va vi ac th si LỜI CẢM N Tôi xin chân thành cảm ơn TS Nguy n Trần Ph c t n tình hƣ ng d n cho thời gian thực lu n văn Mặc dù qu trình thực lu n văn có nh ng khó khăn nhƣng nh ng Thầy hƣ ng d n, bảo gi p cho tìm đƣợc c ch giải quy t có thêm kinh nghiệm thời gian thực đ tài Mặc dù tổng hợp, nghiên cứu tài liệu v n dụng lý thuy t vào tình hu ng cụ thể, nhƣng trình đ thời gian có hạn nên khơng tr nh khỏi nh ng sai sót K nh mong q Thầy Cơ h i đồng Thầy Nguy n Trần Ph c đƣa góp ý lu để hồn thiện nghiên cứu, c ng nhƣ nâng cao kỹ nghiên cứu thời an Xin chân thành cảm ơn! n va gian t i tn to gh Tp Hồ Ch Minh, ngày th ng năm 2018 p ie T c giả d oa nl w lu ll u nf va an V Th Hƣng ình oi m z at nh z m co l gm @ an Lu n va vii ac th si MỤC LỤC T M T T KH A LU N i ABSTRACT ii LỜI CAM ĐOAN vi LỜI CẢM ƠN vii M C L C viii lu DANH M C TỪ VIẾT T T xi an n va DANH M C SƠ ĐỒ xii tn to DANH M C IỂU ĐỒ xii ie gh DANH M C ẢNG IỂU xii p CHƯ NG GIỚI THIỆU Đ TÀI NGHI N CỨU oa nl w 1.1 Lý chọn đ tài d 1.2 Mục tiêu nghiên cứu lu va an 1.3 Phƣơng ph p d liệu nghiên cứu cục khóa lu n ll 1.5 u nf 1.4 Ý nghĩa nghiên cứu oi m T VÀ CÁC NGHI N CỨU TRƯỚC z at nh CHƯ NG TỔNG QUAN L THU 2.1 KH I QU T V R I RO T N D NG V N XẤU C A NG N H NG THƢƠNG M I z @ gm 2.1.1 Rủi ro t n dụng c c tiêu phản nh rủi ro t n dụng m co l 2.1.2 Nợ xấu c c NHTM 2.2 C C YẾU T ẢNH HƢỞNG ĐẾN N XẤU 15 an Lu 2.2.1 Khái quát 15 n va viii ac th si Chase, K., Greenidge, K., Moore W., and Worrell, D (2005), "Quantitative Assessment of a Financial System – Barbados", IMF Working Paper, 5(76), pp.1-21 Collins, N J and Wanju, K (2011), "The effects of interest rate spread on the level of non-performing assets: A case of commercial banks in Kenya", Intenational Journal of Business and Public Management, 1(1), pp.58-65 Das, A and S Ghosh (2007), "Determinants of credit risk in Indian State-Owned banks: An empirical investigation", Economic Issues-Stoke on Trent, 12(2), pp 27-46 lu an commercial bank: An econometric study", Middle Eastern Finance and n va Dash, M., and Kabra, G (2010), "The determinants of non-performing assets in Indian ie gh tn to Economics, 7, pp.94-106 p Drukker (2003), "Testing for serial correlation in linear panel-data models", The Stata nl w Journal, (3)2, pp.168-177 d oa Ekanayake, E.M.N.N and Azeez, A.A (2015), "Determinants of Non-performing an lu loans in licensed commercial banks: Evidence from Srilanka", Asian Economic and Financial Review, 5(6), pp.868-882 u nf va Ernst & Young (2004), "Global Nonperforming Loan Report 2004, Asia Pacific ll m Financial Solutions" t ể Có tạ download oi man_execsummary.pdf z at nh http://info.worldbank.org/etools/docs/library/156232/restructuring2004/pdf/rod z gm @ Espinoza, R and Prasad, A (2010), "Non-performing loans in the GCC Banking system and their macroeconomic effects", IMF Working paper, pp.10/224 m co l Farhan, M., Sattar, A., Chaudhry, A H and Khalil, F (2012), "Economic an Lu determinants of non-performing loans: Perception of Pakistani Bankers", European Journal of Business and Management, 19(4), pp.87-99 n va 65 ac th si Fawad Ahmad and Taquadus Bashir (2013), "Explanatory Power of Bank Specific Variables as Determinants of Non-Performing Loans: Evidence form Pakistan Banking Sector", World Applied Sciences Journal, 22(9), pp.1220-1231 Fofack, H (2005), "Non-performing loans in Sub-Saharan Africa: Causal analysis and macroeconomic implications", World Bank Policy Research Working Paper, 3769 Francis Galton (1880), Statistics of mental imagery, Mind, (19), pp.301-318 Godlewski, C.J (2004), "Bank capital and credit risk taking in emerging market lu economies”, Journal of Banking Regulation, 6(2), pp.128-145 an va Green, S., B (1991), "How many subjects does it take to a regression analysis?", n gh tn to Multivariate behavioral research, 26(3), pp.499-510 p ie Greene (2000), Econometric analysis,International edition Greenidge, K and Grosvenor, T (2009), "Forecasting non-performing loans in w oa nl Barbados", Annual Review Seminar Research Department Central Bank of d Barbados, pp.1-33 an lu va Hồ Thanh Xuân (2013), "Xử lý nợ xấu NHTM - 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An Empirical Analysis", ECB n va Working Paper to gh tn Salas, V and Saurina, J., (2002), "Credit Risk in Two Institutional Regimes: Spanish Commercial and Savings Banks", Journal of Financial Services ie p Research, 22(3), pp.203-224 w oa nl Sinkey, F and M.B Greenwalt (1991), "Loan-loss experience and risk-taking d behaviour at large commercial banks", Journal of Financial Services lu va an Research, 5(1), pp.43-59 ul nf Skarica, B (2013), "Determinants of non-peforming loans in Central and Eastern oi lm European countries", Working paper, pp.13-17 z at nh Vogiazas, S D and Nikolaidou, D E (2011), "Credit risk determinants in the ulgarian banking system and the Greek twin cries”, MIBES 2011 - Oral, z pp.177-189 gm @ Thủ tƣ ng Ch nh phủ (2014), "Quy t đ nh phê duyệt đ m co l tổ chức t n dụng giai đoạn 2011-2015" n cấu lại hệ th ng c c an Lu n va ac th si 70 DANH MỤC PHỤ LỤC Phụ lục 1: Th ng kê mô tả lu an n va p ie gh tn to d oa nl w oi lm ul nf va an lu z at nh z m co l gm @ an Lu n va ac th si 71 Phụ lục 2: Ma tr n tƣơng quan lu an n va p ie gh tn to d oa nl w va an lu oi lm ul nf Phụ lục 3: Kiểm đ nh nhân tử phóng đại phƣơng sai z at nh z m co l gm @ an Lu n va ac th si 72 Phụ lục 4: Kiểm đ nh FEM v i REM lu an n va p ie gh tn to nl w d oa Phụ lục 5: Kiểm đ nh phƣơng sai thay đổi oi lm ul nf va an lu z at nh z m co l gm @ Phụ lục 6: Kiểm đ nh tự tƣơng quan an Lu n va ac th si 73 Phụ lục 7: K t hồi quy Mơ hình Pooled OLS lu an n va p ie gh tn to d oa nl w va an lu oi lm ul nf Kiểm đ nh phƣơng sai thay đổi cho Pooled OLS hettest z at nh z Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of NPL 9.80 0.0017 m co l = = gm @ chi2(1) Prob > chi2 an Lu n va ac th si 74 Mơ hình FEM lu an n va p ie gh tn to d oa nl w oi lm ul nf va an lu z at nh z m co l gm @ an Lu n va ac th si 75 Mơ hình REM lu an n va p ie gh tn to d oa nl w oi lm ul nf va an lu z at nh z m co l gm @ an Lu n va ac th si 76 Mô hình GMM lu an n va p ie gh tn to d oa nl w oi lm ul nf va an lu z at nh z m co l gm @ an Lu n va ac th si 77 Phụ lục 8: Danh s ch 29 Ngân hàng thƣơng mại d liệu nghiên cứu STT lu an TÊN GIAO D CH Á Châu ACB An Bình ABBANK Bản Việt VietCapitalBank Cơng thƣơng Việt Nam Vietinbank, CTG Đầu tƣ Ph t triển Việt Nam BIDV, BID Đông DAF Đông Nam SeAbank Hàng Hải Việt Nam Maritime Bank, MSB Kiên Long KienLongBank n va TÊN NGÂN HÀNG Kỹ Thƣơng Techcombank 11 Nam Á w Nam A Bank 12 Ngoại thƣơng Việt Nam 13 Phát triển Thành ph Hồ Chí Minh HDBank 14 Phƣơng Đông OCB 15 Quân đ i 16 Qu c t 17 Qu c dân 18 Sài Gịn 19 Sài G n Cơng Thƣơng 20 Sài G n Thƣơng T n 21 Việt Á 22 Việt Nam Th nh Vƣợng VPBank 23 Xăng dầu Petrolimex PGB oa nl p ie gh tn to 10 d VCB nf va an lu oi lm ul MBB VIB z at nh NCB SCB z SGB gm @ Sacombank, STB m co l VietABank, VAB an Lu n va ac th si 78 24 25 26 27 28 29 Xuất nh p Việt Nam Tiên Phong ƣu Điện Liên Việt Đại Ch ng Việt Nam Sài G n-Hà N i Việt Nam Thƣơng T n Eximbank, EIB TPB LPB Pvcombank SHB Vietbank lu an n va p ie gh tn to d oa nl w oi lm ul nf va an lu z at nh z m co l gm @ an Lu n va ac th si 79
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