(Luận văn) credit risk management, case study of bidv

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECNOMICS HOCHIMINH CITY K - ng hi ep w n lo ad BÙI NGUYÊN NGỌC ju y th yi pl n ua al CREDIT RISK MANAGEMENT: CASE STUDY OF BIDV n va ll fu m oi MASTES’S THESIS In Banking Ology code: 60.31.12 at nh z z ht vb k jm Supervisor: Dr Nguyễn Văn Phúc om l.c gm n a Lu n va Ho Chi Minh City – 2010 y te re th ACKNOWLEDGMENT ng hi ep I owe a debt of gratitude to many people who helped me complete this thesis I w would like to acknowledge the help of all n lo ad First of all I would like to express my deepest acknowledgement to my supervisor, y th Doctor Phóc Nguyễn Văn, for his valuable advice and recommendations ju yi pl Then, I would like to thank my superiors and colleagues who agreed to be al ua interviewed and/or completed the survey questionnaires The information they n provided, especially from managers/vice managers, allowed me to get deeper va n understanding about credit risk management in BIDV and deriving the findings of ll fu this study oi m at nh Finally, I want to express my sincere thanks to every member of my family for their encouragement and support during the time I devoted to this dissertation z z ht vb k jm om l.c gm n a Lu n va y te re th Page i ABSTRACT ng hi Credit risk is one of the most popular risks in banks due to their intermediary ep functions: lending and borrowing An excessive level of credit risk may destroy not only banks’ profitability but also the stability of global banking system Therefore, it w n is necessary for banks to develop an effective credit risk management strategy not lo ad only to protect themselves but also to prevent banking crises ju y th In case of BIDV, BIDV is one of four State Banks established when Viet Nam yi pl banking system is at a very early stage of development For a long time, BIDV was al ua controlled in allocating loans by government Therefore, credit risk management has n been the main challenge facing the board of BIDV managers With the best try of va n this board, since 2008, BIDV has controlled credit risk that comply with fu ll international standard (non-performing-loan ratio was less than 3%) This is the m oi main reason that drove this study to describe credit risk management in BIDV, to in 2004 to 2.82% in 2009 at nh know why non-performing loan ratio in BIDV has been sharply reduced from 38.3% z z vb ht Both secondary data and primary data are needed for this study Collected data is jm analyzed by Statistical Package for Social Studies version 16.0 (SPSS) Cronbach k gm alpha is used to measure coefficient of reliability and t-test technique is used to test l.c the hypotheses about the four factors influence reduction of non-performing-loan n a Lu information that will answer the researcher’s questions om ratio in BIDV These techniques and tools help collected data transform into n va y te re th Page ii LIST OF FIGURES ng hi ep Figure 1.1: Structure of chapter Figure 1.2: Field of research problem w n Figure 1.3: Method of secondary data lo ad Figure 1.4: Population and sampling ju y th Figure 1.5: Quota sampling method Figure 1.6: Structure of the study 12 yi pl Figure 3.1: BIDV Organization Chart 40 al ua Figure 3.2: BIDV’s non-performing loans 45 n Figure 3.3: BIDV’s loan structure by collateral 46 va n Figure 3.4: BIDV’s loan structure by economic sector 47 fu ll Figure 4.1: Respondents’ position 57 m oi Figure 4.2: Respondents’ working years in BIDV 58 at nh z z ht vb k jm om l.c gm n a Lu n va y te re th Page iii LIST OF TABLES ng hi Table 2.1: Level of specific provision 20 ep Table 2.2: Example of a loan rating system and bond rating mapping 23 Table 2.3: Strategies for reducing and scoping with portfolio credit risk 26 w n Table 3.1: BIDV’s key performance indicators 41 lo ad Table 3.2: BIDV’s credit indicators 43 ju y th Table 3.3: Loan classification in BIDV 49 Table 3.4: Summarize four factors influencing NPL ratio in BIDV 52 yi pl Table 4.1: Four variables with different aspects 58 al ua Table 4.2: Level of agreement in survey questionnaire 59 n Table 4.3: The overall score of Cronbach’s alpha 60 va n Table 4.4: The t-test result 61 fu ll Table 4.5: Summary of hypotheses testing results 64 oi m at nh z z ht vb k jm om l.c gm LIST OF APPENDICES Appendix A 74 a Lu Appendix B 75 n Appendix C 79 n va y te re th Page iv ng TABLE OF CONTENTS hi ep Acknowledgment i w Abstract ii n List of figures .iii lo ad List of tables iv y th List of appendices iv ju yi Table of contents v pl Chapter 1: Introduction al ua 1.1 Introduction n 1.2 Rationale of the study va n 1.3 Statement of the problem and the scope of the study fu ll 1.4 Research questions and objectives m oi 1.5 Methodology at nh 1.5.1 Research design 1.5.2 Data collection z z 1.5.3 Data analysis 10 vb ht 1.6 Significance of the study 12 jm 1.7 Structure of the study 12 k gm Chapter 2: Literature review 14 l.c 2.1 Introduction 14 om 2.2 Basic functions of banks 14 a Lu 2.3 Lending business 15 n 2.3.1 The board of directors’ written loan policy 15 va 2.3.2 Lending procedure 16 n 2.4.3 Loan loss provision 20 Page v th 2.4.2 Loan classification 19 y 2.4.1 Credit risk 17 te re 2.4 Credit risk in banks 17 2.4.4 Non-performing loan 21 2.5 Credit risk measurement 21 ng 2.5.1 Traditional approaches 21 hi ep 2.5.2 Modern approaches 24 2.6 External factors that affect the level of credit risk 27 w 2.6.1 Financial deregulation 28 n lo 2.6.2 Supervision and re-regulation 28 ad 2.6.3 Competition 29 y th ju 2.6.4 The recent financial crisis 30 yi 2.7 Internal factors that affect the level of credit risk 30 pl ua al 2.7.1 Credit information 30 2.7.2 Technology 32 n n va 2.7.3 Credit staffs 33 fu 2.7.4 Loan policy 34 ll 2.8 Summary 35 m oi Chapter 3: Case study of BIDV 37 nh at 3.1 Introduction 37 z 3.2 Overview of BIDV 37 z ht vb 3.2.1 Introduction 37 jm 3.2.2Organization structure 37 k 3.2.3 BIDV business performance 41 gm 3.3 Lending business 43 om l.c 3.3.1 Overview 43 3.3.2 Non-performing loans and loan loss provision 44 a Lu 3.3.3 Loan structure 45 n 3.4 Internal factors that influence non-performing-loan ratio in BIDV 47 va n 3.4.1 Credit information 47 Page vi th 3.4.4 Loan policy 51 y 3.4.3 Credit staff 50 te re 3.4.2 Technology 48 3.4.5 Suggesting hypotheses 52 3.5 Summary 55 ng Chapter 4: Data analysis and findings 56 hi ep 4.1 Introduction 56 4.2 Data collection results 56 w n 4.3 Data analysis 57 lo 4.3.1 Descriptive statistic 57 ad y th 4.3.2 Measures of reliability 58 ju 4.3.3 Statistical hypotheses testing (t-test) 60 yi 4.4 Comparison and discussion of findings 62 pl ua al 4.4.1 Credit information 62 4.4.2 Technology 62 n n va 4.4.3 Credit staffs 63 ll fu 4.4.4 Loan policy 63 m 4.5 Result of hypotheses testing 64 oi 4.6 Summary 64 nh at Chapter 5: Recommendation and Conclusion 66 z 5.1 Introduction 66 z ht vb 5.2 Reviewing research questions 66 jm 5.3 Recommendation for BIDV 66 k 5.3.1 Credit information 66 gm 5.3.2 Technology 67 om l.c 5.3.3 Credit staffs 67 5.3.4 Loan policy 68 a Lu 5.4 Recommendation for other banks 68 n 5.5 Limitation of the research 69 va n 5.6 Summarizing and concluding the dissertation 69 y te re References 70 th Page vii CHAPTER ONE ng INTRODUCTION hi ep w 1.1 Introduction: n lo This chapter provides a general introduction to the research study The purpose is to ad establish foundations for following chapters and the study as a whole, by providing y th a general picture of the study This chapter is structured into seven sections as ju yi presented by figure 1.1 pl Section 1.1 provides a general introduction to the chapter and section 1.2 examines al ua the research background where the research problem is identified Section 1.3 n defines the statement of the problem and scope of the study va n Section 1.4 which includes two subsections 1.4.1 and 1.4.2 defines the research fu ll questions and research objectives Subsection 1.4.1 addresses the research questions m oi that will be respectively answered in chapters of the study Subsection 1.4.2 presents problem defined at nh research objectives that the study covers in the process of solving the research z z Section 1.5 discusses the aspects of research methodology such as selecting from vb ht alternative types of research, research design and research techniques Section 1.6 jm points out the significance and scope of the study, and finally section 1.7 describes k om l.c gm overall structure of the thesis n a Lu n va y te re th Chapter 1: Introduction Page Section 1: Introduction ng hi Section 2: Rationale of the study ep w Section 3: Statement of the problem and n lo scope of the study ad y th Section 4: Research questions and objectives ju yi pl n ua al Section 5: Methodology va Section 6: Significance of the study n ll fu oi m Section 7: Structure of the study nh z 1.2 Rationale of the study: at Figure 1.1: Structure of chapter z ht vb In today’s world, in order to meet customers’ requirements, there is a need for banks jm to diversify their business including other activities such as payments, leasing, and k investments besides the two traditional functions of lending and borrowing gm However, lending still plays an important role in banks because banks’ revenue operating (about 70% in case of BIDV) om l.c primarily comes from lending revenue which contributes over a half of bank total a Lu The traditional way that banks make their profit is to take risk in exchange for an n acceptable return to not only cover the cost of funding but also maintain their va n profitability Thus, the main business of banks is not, as everyone might assume, Chapter 1: Introduction Page th 2006) y principle from the loans which is known as managing credit risk (Burton & Lombra te re taking deposits and making loans but minimizing the risk in collecting interest and APPENDIX A ng MINISTRY OF EDUCATION AND TRAINING hi ep UNIVERSITY OF ECONOMICS HOCHIMINH CITY w n lo ad ju y th yi pl n ua al Bïi Nguyªn Ngọc n va CREDIT RISK MANAGEMENT: fu ll CASE STUDY OF BIDV oi m MASTER S THESIS nh at In z z Banking vb ht Ology code: 603112 k jm om l.c Dr Nguyễn Văn Phúc gm Supervisor n a Lu Ho Chi Minh City - 2010 n va y te re th Page 74 APPENDIX B ng hi ep QUESTIONNAIRE w n Dear sir/ madam lo ad This questionnaire is one part of a research project to understand and improve the y th credit risk management in BIDV Your responses are important in enabling me to ju obtain a full understanding of this topical issue yi pl The questionnaire may take you about ten minutes to complete Please follow the ua al instruction to answer the questions If you wish to add further comments, please feel n free to so The information you provide will be treated in the strictest confidence va The finding from your questionnaire and others will be used as the main data set of n ll fu my dissertation for my master course in Ho Chi Minh City University of Economics oi m (HUE) nh I hope you will find completing the questionnaire enjoyable Please return the at completed questionnaire to the person who delivered it to you/ or just simply reply z z to this email address vb Thank you for your help ht k jm om l.c CREDIT RISK MANAGEMENT IN BIDV gm SURVEY OF a Lu SECTION 1: Back ground Instruction: for the following questions please tick your most favorite answer to n [ ] 5-10 years [ ] More than 10 years [ ] 3-5 years th [ ] 1-3 years y [ ] Less than year te re Question 1: How long have you worked in banking industry? n va each question Question 2: How long have you worked in BIDV? Page 75 [ ] Less than year [ ] 1-3 years [ ] 3-5 years [ ] 5-10 years [ ] More than 10 years ng Question 3: What is your current position in your department/bank? hi ep [ ] Manager [ ] Supervisor [ ] Staff Question 4: What best describes your background? w [ ] Economics n [ ] Banking [ ] Technical field lo ad y th SECTION 2: Credit risk management in BIDV ju (Factors influencing credit risk (non-performing-loan ratio in BIDV) yi pl Instruction: Each below question has five choices of answers which are arranged in ua al increasing of agreement level order (Number is Strongly disagree, number is n disagree, number is normal, number is agree, number is strongly agree) For va the following questions, please circle the most appropriate number to each question n ll fu Level of agreement Question Low oi m No disagree nh The quality of credit information has a great at Normal High agree 5 z z impact to the reduction of non-performingThe quality of credit information depends on k jm ht vb loan ratio in BIDV What is your viewpoint? gm the source that they are collected from? What 2 the information selecting and systemizing om The quality of credit information depends on l.c you think? If banks are willing to cooperate in sharing n te re credit information, the quality of credit va n a Lu progress of BIDV? What is your viewpoint? information will be improved significantly y th What is your opinion? Page 76 The quality of credit information depends on 5 5 5 gm 5 3 the information updating progress of BIDV? ng What you think? hi ep Effective technology operation has a great impact to BIDV’s level of credit risk Do you w agree with this statement? n lo The effectiveness of technology can be ad y th improved if BIDV staffs have enough to ju competence operate and explore yi technology facility’s functions Do you agree pl The ua al with this statement? effectiveness of BIDV technology n on the frequency of facility n va depends The effectiveness of technology can be oi m ll fu maintenance How is your view point? improved if the technology investment is nh at matching with the growth progress of BIDV z What you think? z The effectiveness of BIDV technology 11 Characteristic of credit officers play an k your viewpoint? jm depends on the frequency of update What is ht vb 10 om l.c important role in reducing NPL ratio in BIDV What you think? a Lu 12 If BIDV frequently provides comprehensive n va training courses, the skills of BIDV credit n staff can be improve significant Do you needed to prevent the ethic issues of credit Page 77 th 13 The strict and proper supervisor system is y te re agree? officers Do you agree? 14 Board of directors plays an important role in 5 5 5 ng reducing NPL ratio in BIDV What is your hi ep opinion? 15 Suitable reward policy plays an important w role in improving the quality of credit n lo officers What is your opinion? ad y th 16 Loan policy is a critical factor affect to the ju level of credit risk What you think? yi 17 A well-defined loan policy is important in pl ua al reducing the level of credit risk What you think? n well-communicated loan policy is n va 18 A oi m What is your opinion? ll fu important in reducing the level of credit risk 19 Loan policy must be frequently amended in adept internal and external at to nh order z environment What is your viewpoint? z ht vb jm SECTION 3: Suggestion for future k Instruction: please state your own idea to answer this question gm om l.c performing-loan ratio? What suggestions would you make to help BIDV continuously reducing non- n a Lu n va Thank you for your help and cooperation! y te re th Page 78 APPENDIX C ng hi Descriptive statistics ep Impact of credit information Frequency Percent Valid Percent w n lo ad Valid ju y th Strongly disagree Disagree Normal Agree Strongly agree Total Cumulative Percent yi pl 2 2 54 39 100 54 39 100 54 39 100 61 100 n ua al Source of credit information Frequency Percent Valid Percent n ll 72 14 100 oi m 72 14 100 14 86 100 at nh 72 14 100 fu Disagree Normal Agree Strongly agree Total va Valid Cumulative Percent z Credit information selecting and systemizing Frequency Percent Valid Percent Cumulative Percent z 17 60 22 100 18 78 100 k 66 100 y 3 60 34 100 te re 3 60 34 100 n 3 60 34 100 va Disagree Normal Agree Strongly agree Total n Valid Cumulative Percent a Lu Credit information sharing Frequency Percent Valid Percent om l.c gm 17 60 22 100 jm 17 60 22 100 ht Disagree Normal Agree Strongly agree Total vb Valid th Credit information checking Page 79 Impact of credit information Frequency Percent Valid Percent ng Valid hi ep w 17 63 17 100 Disagree Normal Agree Strongly agree Total 17 63 17 100 Cumulative Percent 17 63 17 100 20 83 100 n lo ad Technology operation Frequency Percent Valid Percent y th ju yi Valid Strongly disagree Disagree Normal Agree Strongly agree Total Cumulative Percent pl n ua al 1 1 10 62 26 100 10 62 26 100 10 62 26 100 12 74 100 n va ll fu Credit staff competence and technology matching Frequency Percent Valid Percent Cumulative Percent 13 70 12 100 at z z 13 70 12 100 18 88 100 ht vb 13 70 12 100 nh Disagree Normal Agree Strongly agree Total oi m Valid jm k Frequency of facility maintenance Frequency Percent Valid Percent 20 86 100 n a Lu 18 66 14 100 om 18 66 14 100 l.c 18 66 14 100 Disagree Normal Agree Strongly agree Total gm Valid Cumulative Percent 11 69 19 11 69 19 12 81 100 Page 80 th 11 69 19 y Disagree Normal Agree Strongly agree te re Valid n va Technology investment & BIDV's growth progress matching Frequency Percent Valid Percent Cumulative Percent Impact of credit information 100 100 100 Total ng hi Modern technology Frequency Percent Valid Percent ep Valid w n lo ad 15 71 11 100 Disagree Normal Agree Strongly agree Total y th 15 71 11 100 18 89 100 Characteristic of credit staffs Frequency Percent Valid Percent ju yi pl Normal Agree Strongly agree Total 25 45 30 100 n ua al Valid 15 71 11 100 Cumulative Percent 25 45 30 100 25 70 100 n va 25 45 30 100 Cumulative Percent fu ll Comprehensive training course Frequency Percent Valid Percent oi m Cumulative Percent 26 50 22 100 z z 26 50 22 100 28 78 100 ht vb 26 50 22 100 at Disagree Normal Agree Strongly agree Total nh Valid jm k Proper supervision system Frequency Percent Valid Percent 18 80 100 n a Lu 16 62 20 100 om 16 62 20 100 l.c 16 62 20 100 Disagree Normal Agree Strongly agree Total gm Valid Cumulative Percent 21 48 29 23 71 100 Page 81 th 21 48 29 y 21 48 29 te re Unimportant Normal Important Very important Cumulative Percent n Valid va Important role of board of directors Frequency Percent Valid Percent Impact of credit information 100 100 100 Total ng hi Reward policy Frequency Percent Valid Percent ep Valid w n lo ad 11 57 32 100 Normal Agree Strongly agree Total y th 11 57 32 100 11 68 100 Impact of loan policy Frequency Percent Valid Percent ju yi Disagree Normal Agree Strongly agree Total 10 64 21 100 pl Valid 11 57 32 100 Cumulative Percent n ua al 10 64 21 100 15 79 100 n va 10 64 21 100 Cumulative Percent fu ll Well-defined loan policy Frequency Percent Valid Percent oi m Cumulative Percent 15 56 27 100 z z 15 56 27 100 17 73 100 ht vb 15 56 27 100 at Disagree Normal Agree Strongly agree Total nh Valid jm k Well-communicated loan policy Frequency Percent Valid Percent 19 72 100 n a Lu 16 53 28 100 om 16 53 28 100 l.c 16 53 28 100 Disagree Normal Agree Strongly agree Total gm Valid Cumulative Percent 15 67 16 17 84 100 Page 82 th 15 67 16 y 15 67 16 te re Disagree Normal Agree Strongly agree Cumulative Percent n Valid va Frequency of amendment Frequency Percent Valid Percent ng Impact of credit information 100 100 100 Total Case Processing Summary hi ep Cases N % 100 100.0 0 100 100.0 Valid w Excludeda n lo Total ad y th a Listwise deletion based on all variables in the procedure ju Reliability Statistics yi pl 703 ua al Cronbach's Alpha N of Items n va Item Statistics n Std Deviation fu ll Mean N 4.2700 m 76350 100 Source of credit information 3.9400 67898 100 Credit information selecting and systemizing 4.0300 at Credit information sharing 4.2500 65713 100 Credit information checking 3.9400 67898 100 oi Impact of credit information nh z 65836 100 z ht vb k jm Item-Total Statistics gm Cronbach's Alpha if Item Deleted om l.c Corrected Item-Total Correlation Scale Variance Scale Mean if if Item Item Deleted Deleted 16.1600 3.651 406 681 Source of credit information 16.4900 3.525 562 611 Credit information selecting and systemizing 16.4000 3.960 392 681 Credit information sharing 16.1800 3.745 488 643 Credit information checking 16.4900 3.747 461 654 n a Lu Impact of credit information n va y th Page 83 te re Case Processing Summary Impact of credit information N ng hi Cases % Valid ep 100 100.0 0 100 100.0 Exclude da w Total n lo a Listwise deletion based on all variables in the procedure ad Reliability Statistics y th Cronbach's Alpha N of Items ju yi 817 pl Item Statistics al n ua Std Deviati on n va Mean nh facility 100 oi of 3.8900 66507 m 3.9200 63054 100 at Frequency maintenance 100 ll Credit staff competence and technology matching 4.1100 69479 fu Technology operation N z 3.9000 61134 ht Modern technology 100 vb 4.0600 58292 z Technology investment & BIDV's growth progress matching gm Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted om l.c Scale Mean if Item Deleted Scale Variance if Item Deleted k jm Item-Total Statistics 100 15.7700 3.815 585 Credit staff competence and technology matching 15.9900 3.707 678 Frequency of maintenance 15.9600 3.978 600 784 15.8200 4.068 628 777 760 n va y te re Page 84 th Technology investment & BIDV's growth progress matching n facility 790 a Lu Technology operation Impact of credit information ng Modern technology RELIABILITY 15.9800 4.121 560 795 hi ep /VARIABLES=CS1 CS2 CS3 CS4 CS5 /SCALE('ALL VARIABLES') ALL w /MODEL=ALPHA n lo /STATISTICS=DESCRIPTIVE SCALE ad ju y th /SUMMARY=TOTAL Case Processing Summary yi N Valid pl Cases 100 100.0 0 100 100.0 n ua al Excludeda % va Total n a Listwise deletion based on all variables in the procedure ll fu oi m Reliability Statistics nh Cronbach's Alpha z 819 at N of Items z ht N k jm Mean Std Deviation vb Item Statistics 744 100 Comprehensive training course 3.92 748 100 Proper system 4.00 667 100 Important role of board of directors 4.04 764 100 Reward policy 4.21 624 100 om l.c n a Lu supervision 4.05 gm Characteristic of credit staffs n va te re y Item-Total Statistics th Page 85 Case Processing Summary N ng hi Cases Valid % 100 100.0 0 100 100.0 ep Excludeda Total w n Scale Scale Mean if Variance if Item Deleted Item Deleted lo ad y th Characteristic of credit staffs Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted 4.728 638 776 Comprehensive training course 16.30 4.838 592 790 Proper system 16.22 5.103 597 788 16.18 4.715 616 783 ju 16.17 yi pl al n ua supervision va n Important role of board of directors RELIABILITY ll fu oi m /VARIABLES=LP1 LP2 LP3 LP4 nh /SCALE('ALL VARIABLES') ALL at z /MODEL=ALPHA z ht vb /STATISTICS=DESCRIPTIVE SCALE k jm /SUMMARY=TOTAL Case Processing Summary 0 100 100.0 n y te re N of Items th 851 va Reliability Statistics Cronbach's Alpha n a Listwise deletion based on all variables in the procedure a Lu Total 100.0 om Excludeda 100 l.c Valid % Cases gm N Page 86 Case Processing Summary N ng hi Cases Valid % 100 100.0 0 100 100.0 ep Excludeda Total w n Item Statistics lo Std Deviation ad Mean y th Impact of loan policy ju yi Well-defined policy loan N 718 100 4.08 706 100 4.06 750 100 627 100 pl 4.01 of va 3.97 n Frequency amendment n ua al Well-communicated loan policy fu ll Item-Total Statistics m Corrected Item-Total Correlation oi Scale Scale Mean if Variance if Item Deleted Item Deleted at nh 12.11 3.149 Well-defined policy 12.04 3.109 12.06 3.107 12.15 3.482 808 736 791 670 821 ht vb 669 821 om l.c n a Lu /SCALE('ALL VARIABLES') ALL gm /VARIABLES=CI TECH CS LP k of jm Well-communicated loan policy Frequency amendment RELIABILITY 697 z loan z Impact of loan policy Cronbach's Alpha if Item Deleted n te re /STATISTICS=DESCRIPTIVE SCALE va /MODEL=ALPHA y /SUMMARY=TOTAL Case Processing Summary th Page 87 N Cases Valid % ng 100 100.0 0 100 100.0 hi Excludeda ep Total a Listwise deletion based on all variables in the procedure w n Reliability Statistics lo ad Cronbach's Alpha y th N of Items ju 787 yi Item Statistics pl Std Deviation ua al Mean 4.0860 Technology 3.9760 Credit staff 4.0440 Loan policy 4.0300 n Credit information N n va ll fu oi m 46559 100 48516 100 54204 100 58310 100 nh at Item-Total Statistics z Corrected ItemTotal Correlation z 12.0500 1.692 Technology 12.1600 1.726 Credit staff 12.0920 1.557 Loan policy 12.1060 1.408 651 Cronbach's Alpha if Item Deleted 611 730 k jm Credit information gm ht vb Scale Mean if Scale Variance if Item Deleted Item Deleted 761 590 737 l.c 539 705 om n a Lu n va y te re th Page 88