Introduction
Introduction
This chapter offers a comprehensive introduction to the research study, establishing foundational context for the subsequent chapters and the overall research It aims to provide readers with a clear overview of the study’s purpose, scope, and significance Structured into seven sections as illustrated in figure 1.1, this chapter sets the stage for detailed exploration in the following parts, ensuring a cohesive understanding of the research objectives and framework.
Section 1.1 provides a general introduction to the chapter and section 1.2 examines the research background where the research problem is identified Section 1.3 defines the statement of the problem and scope of the study
Section 1.4 which includes two subsections 1.4.1 and 1.4.2 defines the research questions and research objectives Subsection 1.4.1 addresses the research questions that will be respectively answered in chapters of the study Subsection 1.4.2 presents research objectives that the study covers in the process of solving the research problem defined
Section 1.5 discusses the aspects of research methodology such as selecting from alternative types of research, research design and research techniques Section 1.6 points out the significance and scope of the study, and finally section 1.7 describes overall structure of the thesis
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Section 3: Statement of the problem and scope of the study
Section 2: Rationale of the study
Section 4: Research questions and objectives
Section 7: Structure of the study Section 6: Significance of the study
Rationale of the study
To meet evolving customer demands, banks must diversify their service offerings beyond traditional lending and borrowing Incorporating activities such as payments, leasing, and investments enables banks to enhance their competitiveness and better serve their clients in today’s dynamic financial landscape.
Lending remains a crucial component of banking operations, as it generates the majority of banks' revenue In particular, lending activities contribute over 50% of total bank income, with some institutions like BIDV deriving approximately 70% of their revenue from lending This highlights the essential role of lending in the bank's overall financial performance and profitability.
Banks primarily generate profit by managing credit risk, which involves minimizing the risk associated with collecting interest and principal from loans Their main business focus is not just taking deposits and issuing loans but balancing risk to ensure acceptable returns that cover funding costs and sustain profitability Effective credit risk management is essential for bank profitability and stability.
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Credit risk is primarily linked to banks due to their intermediary role in channeling funds from individuals with surplus capital to those with investment needs This essential function exposes banks to potential losses if borrowers fail to repay their loans, making credit risk a critical concern in banking operations (Mishkin & Eakins, 2006) Effective management of credit risk is vital for maintaining financial stability and fostering trustworthy lending practices within the banking sector.
Historically, financial crises are usually derived from the failure of banks to manage credit risk from poor quality loans or high probability of customers’ default (Yarbrough & Yarbrough 2006)
BIDV is one of the four State Banks established during Vietnam's early banking system development, with a history of government control over loan allocations Credit risk management has historically been a major challenge for BIDV's management board Since 2008, BIDV has successfully aligned its credit risk practices with international standards, reducing its non-performing loan ratio to below 3% This significant improvement prompted a detailed study to understand BIDV's effective credit risk management strategies and the reasons behind the rapid decrease in its non-performing loan ratio from 38.3%.
1.3 Statement of the problem and scope of the study
This study conducts with particular emphasis on why non-performing-loan ratio in BIDV has been rapidly reduced from 38.3% in 2004 to 2.82% in 2009
This research focuses on two main areas: the background of credit risk management and a case study of BIDV’s efforts to reduce non-performing loans The first section provides essential knowledge on credit risk, including its measurement, management strategies, and influencing factors The second section analyzes BIDV’s success in lowering its non-performing loan ratio, examining an overview of BIDV, credit activity analyses, and the application of credit risk management theories to practical operations It also considers four key factors—credit information, technology, credit staff, and loan policies—during 2004–2009 and proposes hypotheses based on these analyses Ultimately, the study demonstrates that effective credit risk management has been a significant achievement for BIDV.
2009, BIDV has controlled credit risk under international standard (non-performing-
Chapter 1: Introduction Page 3 nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg loan ratio was less than 3%) Maybe there are many reasons leading the success of BIDV In scope of this study, four factors including credit information, technology, credit staff, and loan policy will be examined as the main positive factors that influence credit risk management of BIDV
This study explores four key factors influencing credit risk management, supported by a comprehensive review of relevant literature and credit risk management theories It analyzes BIDV’s credit business practices to demonstrate how these factors effectively reduce the non-performing loan (NPL) ratio Additionally, survey findings through questionnaires validate the relationships between these factors and improved credit risk performance, providing practical insights into effective credit risk reduction strategies.
Figure 1.2: Fields of the research problem
1.4 Research Questions and Research Objectives:
Research questions involve the research translation of “problem” into the need for inquiry (Zikmund, 1997, p.88) The research problem defined above leads to the following research questions:
• What are factors that influence non-performing-loan ratio in BIDV?
• How has BIDV applied credit risk management theory to practice?
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This study is conducted with the purpose of:
• To know the main factors leading to BIDV success in reducing non-performing loan ratio,
• To consider whether BIDV applies theory to manage its credit risk or not
This study investigates the impact of four key factors—credit information, technology, credit staff, and loan policy—on reducing the non-performing loan (NPL) ratio at BIDV The researcher formulates hypotheses to assess how each element contributes to improving loan performance and minimizing credit risks By analyzing these factors, the study aims to identify effective strategies for enhancing credit management and promoting financial stability within the bank.
H 1 : Credit information variable influences non-performing-loan ratio in BIDV
H 2 : Technology variable influences non-performing-loan ratio in BIDV
H 3 : Credit staffs variable influences non-performing-loan ratio in BIDV
H 4 : Loan policy variable influences non-performing-loan ratio in BIDV
The research methodology includes research design, data collection and data analysis
1.5.1 Research design: provide a road map of the whole research,
This study employs both qualitative and quantitative research methods to comprehensively analyze BIDV's performance Quantitative data, including performance indicators, business lending figures, and factors influencing the non-performing loan ratio, provide measurable insights Meanwhile, qualitative data, gathered from respondents' backgrounds, positions, and suggestions, offers valuable contextual understanding to identify strategies for continuously reducing BIDV’s non-performing loan ratio.
According to G Zikmund (1997), four fundamental research design techniques are survey, experiment, secondary data, and observation This study employs both survey and secondary data methods to achieve its objectives The survey method enables the collection of primary data to identify four key factors influencing BIDV's non-performing loan ratio, while secondary data analysis provides essential background on credit risk management and helps describe BIDV’s strategies in reducing non-performing loans.
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This study employs a perception survey to understand respondents' subjective feelings about the research problem, which may influence the findings To ensure accuracy and credibility, the researcher also incorporates secondary data collection techniques to gather additional evidence and validate the results.
This section explains the data collection methods, encompassing both primary and secondary sources Secondary data was gathered from reputable sources such as books, previous research studies, BIDV’s annual reports, financial journals, and magazines, ensuring comprehensive background information Primary data was obtained through surveys and interviews conducted directly by the author, providing firsthand insights.
Using secondary data in research offers numerous advantages It is cost-effective, as utilizing existing data is typically less expensive than gathering new, primary data Additionally, secondary data saves significant time in data analysis and interpretation In some cases, it may be the only available source of information from previous periods, making it essential for longitudinal studies Moreover, secondary data is generally permanent, accessible, and can be easily verified by others, ensuring data reliability and reproducibility (Zikmund, 1997).
There are many types of secondary data such as documentary secondary data, multiple source secondary data and survey based secondary data (Saunders, Lewis
This study primarily relies on documentary secondary data sources, including BIDV's internal materials such as regulations and annual reports retrieved from the bank's internet and intranet platforms Additionally, it incorporates other written materials like previous research, books, journals, newspapers, and magazines These secondary data sources are crucial raw information that support the research, providing comprehensive insights into BIDV's operations and framework.
Methodology
The research methodology includes research design, data collection and data analysis
1.5.1 Research design: provide a road map of the whole research,
This study employs both qualitative and quantitative research methods to comprehensively analyze BIDV’s performance Quantitative data, including key performance indicators, business lending metrics, and factors influencing the non-performing loan ratio, provides measurable insights Meanwhile, qualitative data—such as respondents’ backgrounds, positions, and suggestions—offers valuable context and perspectives to understand and address the non-performing loan issue Combining these approaches ensures a thorough and well-rounded analysis to support strategies for reducing BIDV’s non-performing loan ratio.
Based on G Zikmund's (1997) four fundamental research design techniques—survey, experiment, secondary data, and observation—this study employs both survey and secondary data methods The survey approach enables the collection of primary data to identify four key factors influencing BIDV's non-performing loan ratio Meanwhile, secondary data analysis provides essential background on credit risk and offers insights into BIDV’s strategies for managing credit risk and reducing non-performing loans.
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This study employs a perception survey to capture respondents' feelings and opinions about the research problem, providing valuable subjective insights To ensure the reliability of the findings, the researcher also uses secondary data collection methods to gather additional evidence that supports and confirms the research problem Combining both primary and secondary techniques enhances the validity and robustness of the research outcomes.
This section details the data collection methods, incorporating both primary and secondary sources Secondary data was gathered from reputable sources such as books, previous research studies, BIDV’s annual reports, financial journals, and magazines, ensuring comprehensive background information Primary data was obtained through surveys and interviews conducted directly by the author, providing firsthand insights relevant to the research objectives This combined approach ensures a robust and reliable foundation for the analysis, adhering to best practices in data collection for financial research.
Using secondary data in research offers several key advantages It is cost-effective, as utilizing existing data is typically less expensive than collecting primary data through new studies Additionally, secondary data saves valuable time in data analysis and interpretation, allowing researchers to focus on insights rather than data collection In certain cases, secondary data may be the only available source for past periods, enabling historical analysis Moreover, secondary data is generally permanent and easily accessible, facilitating verification and further research (Zikmund, 1997).
There are many types of secondary data such as documentary secondary data, multiple source secondary data and survey based secondary data (Saunders, Lewis
This study primarily relies on documentary secondary data sources, including BIDV's internal materials such as regulations and annual reports obtained from their online and intranet websites Additionally, it utilizes other written materials like previous research papers, books, journals, newspapers, and magazines These secondary data sources provide essential raw information for the research, ensuring a comprehensive understanding of the topic.
This study utilized a comprehensive literature review based on previous research, books, financial magazines, and academic journals to establish a solid theoretical foundation Additionally, data was gathered from BIDV's annual reports and relevant regulations to ensure accuracy and up-to-date information for analysis and insights.
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Chapter 1: Introduction Page 7 from the official internet and intranet websites of BIDV were used to provide a clear picture about credit risk management of BIDV
Figure 1.3: Method of secondary data collection
Based on the above advantages of secondary data, the researcher decided to use secondary data as one of the sources of information in order to conduct this study
1.5.2.2 Primary data Beside secondary data, the researcher uses primary data in order to get the feelings of respondents about the problem of the study The purpose of this study is to know the factors leading to BIDV success in credit risk management
Therefore, the target population in this research is all BIDV credit staff whose daily work relevant to lending business
Due to limited time and financial resources, this study could not gather data from the entire population of BIDV credit staff Instead, a sample of 100 BIDV credit employees will be surveyed, including 20 managers and vice managers, as well as 30 credit department leaders.
Previous researches, books, journals, newspapers
The most recent annual reports and internal regulations from BIDV provide comprehensive insights into the bank's financial performance and compliance standards These documents are essential for understanding BIDV's strategic focus, risk management practices, and regulatory adherence Staying updated with the latest reports ensures stakeholders and investors are informed about the bank's growth trajectory and operational stability Access to detailed data and analyses facilitates transparency and supports informed decision-making within the financial sector.
Figure 1.4: Population, sample and sampling methods
This study employs the quota sampling technique due to its advantages in saving time, reducing costs, and offering convenience Quota sampling involves selecting participants in specific proportions to represent key segments of the population, ensuring that the sample accurately reflects the diversity of the target group The process consists of three key steps: defining quotas based on relevant demographic variables, selecting participants until each quota is fulfilled, and ensuring that the sample mirrors the population’s characteristics This method is particularly effective for efficient data collection while maintaining representativeness.
The population of BIDV credit staff is structured into three key categories: managers and vice managers, credit department leaders, and credit officers This classification reflects the hierarchical nature of the organization, with higher-positioned staff having more rational perspectives Understanding these roles is essential for analyzing credit management practices and enhances the effectiveness of organizational flow within BIDV.
In the study, the desired proportions for each class were established based on managerial judgment Specifically, the managers and vice managers group comprises 20% of the sample, the credit leaders group accounts for 30%, and credit officers constitute the remaining 50% These proportions ensure a balanced and representative distribution aligned with the research objectives.
This perception survey's findings are influenced by the subjective judgments of respondents, which may impact the overall accuracy To ensure reliable insights, half of the selected sample consists of high-ranking credit staff, including managers and vice managers Benefiting from BIDV membership, the researcher had easy access to communicate with senior managers and credit department leaders, facilitating comprehensive data collection for the study.
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This study highlights that the sample comprises only 50% credit officers, whereas Chau (2009)'s sample included 90%, which significantly influenced the research outcomes As a result, the researcher retested the four hypotheses established by Chau (2009) to validate their applicability within the different sample context and ensure the robustness of the findings.
• Finally, quota sample (100 respondents) is fixed The sample of this study is about 100 respondents (over 5 times of observed variables) including 20 managers/vice managers, 30 credit department leaders and 50 credit officers
This number was decided after considering some previous researches For example, see Tho & Trang (2008, p.35) or Trong & Ngoc (2008, p31)
To obtain the desired sample size, a total of 150 self-administered questionnaires were distributed to the respondents by the researcher Of these, 100 questionnaires were returned making effective response rate 67%
Significance of the study
This study helps readers realize the crucial importance of credit risk management and know the main factors that influence the reduction of non-performing-loan ratio in BIDV.
Structure of the study
Chapter 3: Case study of BIDV
Chapter 4: Data analysis and findings
This study aims to analyze the impact of credit information, technology, loan policies, and credit staff competency on reducing the non-performing loan (NPL) ratio at BIDV Chapter One provides an overview of the research objectives and background The study is structured into five additional chapters, each focusing on different aspects such as methodology, data analysis, and findings related to these key factors influencing loan performance.
Chapter 2: Literature Review: This chapter will provide general theories related to credit risk management Furthermore, the researcher’s insights on these theories will also be discussed
Chapter 3: Case study of BIDV: This chapter provides an overview of bank for investment and development of Vietnam (BIDV) and BIDV’s credit risk management is the main part of this chapter
Chapter 4: Data analysis and findings: analyzing the collected data in order to get results to test the hypotheses and answer the research questions in chapter one
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Chapter 5: Recommendation and conclusion: based on these analysis and findings from chapter five, some suggestions or recommendations about the credit risk management strategies that BIDV can adopt to manage credit risk will be given. nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
Literature review
Introduction
This chapter introduces existing literature on the core activities of commercial banks, focusing on credit risk arising from lending operations It reviews both external factors—such as financial deregulation, supervisory re-regulation, increased competition, and recent financial crises—and internal factors like information systems, loan policies, credit staff competence, and technological advancements that influence credit risk levels Additionally, the chapter discusses various methods of credit risk measurement, emphasizing how excessive credit risk can compromise bank profitability, threaten financial stability, and impact the global economy The 2008 financial crisis exemplifies this, demonstrating how rising banking risks can trigger worldwide recession, destabilize economies beyond the U.S., and undermine global financial systems.
Therefore, banks should recognize the importance of credit risk management and employ an effective strategy to manage credit risk in order to protect themselves from credit losses.
Basic functions of banks
A bank is an organization that primarily engages in accepting deposits and making loans, serving as a cornerstone of the financial system Its core functions include playing a vital role in the payment system, acting as an intermediary between depositors and borrowers through various deposit and loan products, and offering a range of financial services such as fiduciary responsibilities, investment banking (including stock and bond underwriting), and off-balance sheet risk management These activities position banks as essential institutions in supporting economic growth and financial stability.
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Banks traditionally serve as financial intermediaries by mobilizing funds from depositors with surplus money and lending them to borrowers in need, facilitating the flow of capital within the economy (Ritter, Silber & Udell, 2000).
Lending business
According to Benton E.Gup & James W.Kolari (Commercial banking, 2005, p250-
A bank’s board of directors holds ultimate responsibility for all loans made by the institution To ensure effective oversight, the board must establish a comprehensive written loan policy outlining the guidelines and principles for the bank’s credit risk management This credit risk strategy should balance the goals of maintaining credit quality, achieving earnings, and fostering growth, reflecting the essential risk/reward tradeoff inherent in lending activities.
Loan policies vary significantly between banks, with small local banks typically focusing on lending to nearby customers, while large banks often specialize in business loans Nonetheless, both types of banks emphasize their core objective: making sound, profitable loans to ensure financial stability and growth.
An effective loan policy must emphasize that a crucial aspect of the lending process is establishing a clear repayment plan at the time the loan is issued This ensures borrower accountability and helps mitigate repayment risks, supporting sound financial management Incorporating explicit repayment terms in the initial loan agreement is essential for transparency and compliance, promoting responsible lending practices.
Other parts of the loan policy deal with:
• Loan authority: Who has the authority to make loans; the lending limits relative to capital, deposits, or assets; the lending approval process
A bank's loan portfolio encompasses various types of loans, including consumer loans, startup business financing, large corporate loans, farm loans, and international loans An effective loan policy should establish clear guidelines on the mix of these loans, including limits on the concentration of specific loan types to ensure a balanced and risk-managed portfolio.
Geography plays a crucial role in defining the trade area where banks can extend loans, with most small and medium-sized businesses (97%) relying on financial institutions within a 30-mile radius of their main office This proximity-based lending pattern highlights the importance of local banking services in supporting regional economic growth.
• Policies for determining interest rates, fees, and contractual terms of the loans
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• Limits and guidelines for off-balance sheet exposures from loan commitments, letters of credit, securitized loans, and derivative products (swaps, options, and futures, etc.)
• A loan review process to evaluate lending procedures and the quality of the loan portfolio
Lending procedure is the process that banks loans are provided to borrowers through proper evaluation of customers’ financial condition and credit worthiness (Rose &
According to Hempel and Simonson (1999), despite variations in the methods used by different banks to make their final lending decisions, they generally adhere to a standard lending procedure This procedure involves several fundamental steps designed to ensure a consistent and thorough evaluation process, ultimately supporting sound credit decisions across financial institutions.
Step 1: Receiving application: Customers including individuals and corporations apply for a loan from banks by filling out a loan application
Step 2: Evaluating application: Bank credit officers evaluate the loan application
Evaluating loan requests involves interviewing customers to assess their character and borrowing purposes Banks can also access customers’ credit history from their internal databases if there is an existing relationship Additionally, financial institutions and credit bureaus serve as vital sources for gathering comprehensive credit information, ensuring informed lending decisions.
Step 3: Lending decision: Refusing application or Granting credit Refusing application: If credit officers realize that the customer is ineligible for receiving the bank loan, they may reject the loan application Credit officers will then issue a formal announcement on the loan application status to the customers within a certain period of time
When a loan application meets the bank's requirements, a loan agreement can be issued and signed between the customer and an authorized bank officer It is essential to consider additional steps, such as verifying and collecting collateral assets, to secure the loan Proper collateral management ensures the loan is backed by assets valued as collateral, reducing the bank's risk.
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Step 4: Monitor loan: After granting credit, credit officers must monitor customers in order to ensure that customers use the loan accordingly with the purpose stated on the loan agreement In addition, as credit officers can quickly assess customers’ financial condition or their ability to pay the loan back by a proper monitoring process, banks managers and credit officers who are aware of the importance of this process can effectively help preventing their banks from credit losses
Step 5: Collecting loan: The duty of credit officers has not finished upon granting the loan to customers Their last and important mission is to collect debt and liquidate credit agreement However, one of four things can happen to an outstanding loan: (1) It can be repaid on schedule; (2) It can be renew and extend;
The bank has the option to sell the loan to another investor, which is a desirable outcome Additionally, transferring the loan can help mitigate potential risks However, if the loan goes into default, the bank may sustain significant losses, representing the worst-case scenario These outcomes highlight the importance of managing loan risks effectively.
Before granting a loan, banks evaluate the borrower's creditworthiness by assessing their character, financial condition, and ability to repay through future income or asset sales Once approved, all loan terms—including the credit facility, borrowed amount, repayment schedule, interest rate, collateral, and covenants—are detailed in a comprehensive loan agreement After disbursement, banks continuously monitor the loan to ensure repayment, aiming for full repayment while managing the risk of potential losses if the loan defaults.
Credit risk in banks
Banking involves managing risk to generate profits, as banks accept certain risks while striving to maximize shareholder wealth They carefully balance various strategies based on their risk and return profiles to achieve optimal financial performance Effective risk management is essential for banks to sustain profitability and grow their market presence.
According to Jane E.Hughes and Scott B.MacDonald (2002, p.297), a banker’s job is to manage risk, not avoid it Banks face a variety of risks in their operations such
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However, credit risk seems to be the most popular risk that most modern banks face due to their main business functions: lending and borrowing
Credit risk, as defined by Benton E Gup et al (2005, p 247), is the risk of repayment failure, representing the possibility that an obligor may not fulfill their agreed financial obligations This type of risk is relevant across various banking activities, including loans, derivatives, foreign exchange transactions, and investment portfolios, highlighting its critical role in banking and financial management.
This study defines credit risk specifically within the context of bank lending activities Credit risk refers to the potential for borrowers to default on their loans, leading to financial losses for banks When borrowers repay the full amount of principal and interest on time, banks face no credit risk However, even if borrowers partially settle their principal or interest, regardless of their repayment willingness or capacity, banks are exposed to credit risk, increasing the likelihood of financial loss.
Credit risk management plays an important role in preventing not only the banks’ lending business but also banks’ operations from failure (Madura 2006)
Banks play a vital role in the economy and society, making them too important to fail The failure of any bank can have severe negative impacts on households, the corporate sector, and the overall economy Ensuring the stability of banking institutions is essential to maintain financial stability and prevent widespread economic disruptions.
The failure of a single bank can quickly spread to others both domestically and globally, exemplified by events like the recent U.S subprime mortgage crisis This interconnectedness in the banking sector means that when funds cease to flow into one institution, other banks with financial ties—such as placements or credit holdings—may face liquidity shortages Such systemic risks highlight how closely linked banks are, making bank failures potentially contagious within the financial system.
The "other banks" mentioned are likely to encounter similar challenges, triggering a domino effect that could lead to a widespread collapse of the banking system This scenario mirrors the events of the recent financial crisis, highlighting the systemic risks and the importance of robust risk management strategies within the banking sector (Yehning, Hasan & Iftekhar, 2008).
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In market-oriented economies, banks play a vital role by channeling funds from savers to individuals and businesses with investment opportunities Their primary function is to facilitate the smooth flow of funds within the economy, ensuring efficient allocation of capital and supporting economic growth.
Effective bank operations are crucial for ensuring smooth fund flows and increasing funding opportunities for profitable projects A failure or crisis in a few banks can threaten the stability of the entire banking system, impacting the global economy and society as a whole Such disruptions can cause savers to lose their savings and interest income, while entrepreneurs may face setbacks in securing investments, hindering economic development Consequently, robust credit risk management is essential not only for individual banks but also for maintaining the stability of the banking system and supporting economic growth.
In 2005, the governor of the State Bank of Vietnam issued Decision 1 on loan classifications and provisioning for bad debts of credit institutions, establishing essential guidelines for financial stability The regulation stipulates that, based on overdue indicators of debts, a loan portfolio is classified into five distinct groups, ensuring effective risk management and accurate assessment of credit quality This classification framework helps credit institutions monitor overdue debts and determine appropriate provisioning levels, supporting sound banking practices in Vietnam.
- Group 1 (standard debts): includes undue debt, whose principal and interest are assessed by credit institutions to be fully recoverable when they become due
Debts under this category are not subject to provisioning (0% rate of provisioning);
Group 2 includes debts that require special attention, such as those overdue for less than 90 days and rescheduled debts that are now no longer due under revised terms These debts should be provisioned at a rate of 5%, reflecting their potential risk Proper identification and provisioning of Group 2 debts are essential for accurate financial reporting and risk management.
Group 3, classified as sub-standard, comprises debts overdue between 90 and 180 days, along with rescheduled debts overdue for less than 90 days according to the rescheduled terms These loans are provisioned at a rate of 20%, reflecting their higher risk status.
- Group 4 (doubtful debts): includes debts overdue for between 181 and 360 days and rescheduled debts that are overdue for between 90 and 180 days
Decision 493/2005/QD-NHNN dated 22 April 2005 stipulates that this group is subject to a provisioning rate of 50%, in accordance with the revised terms.
Group 5 comprises debts with potentially unrecoverable principal, including overdue debts exceeding 360 days, debts frozen while awaiting government action, and rescheduled debts that are now over 180 days overdue based on the new terms These debts are automatically provisioned at 100%, reflecting their high likelihood of default.
With respect to debt frozen by the government, specific provisions shall be set up according to the financial capability of the credit institution
Credit institutions are permitted to classify loans according to their credit rating system, provided that their risk provision policy has been approved by the State Bank of Vietnam (SBV) This classification process involves dividing the loan portfolio into five distinct groups, ensuring consistent risk assessment and regulatory compliance.
Credit risk measurement
Differentiating between traditional and new approaches can be challenging, as modern models often incorporate key concepts from traditional frameworks Many innovative ideas in contemporary models build upon the foundational principles established by traditional methods, making the distinction less clear This blending of concepts highlights the evolution of financial modeling, where traditional ideas continue to influence and shape newer, more advanced approaches.
The traditional approach is comprised of four classes of models
In expert systems for credit decisions, the branch lending officer's expertise and judgment play a crucial role in determining loan approval The officer evaluates key factors, primarily focusing on the five “Cs”: character, capital, capacity, collateral, and economic cycle, to make informed lending decisions Incorporating these vital criteria ensures a comprehensive assessment of borrower reliability and repayment ability, ultimately enhancing the accuracy and efficiency of the credit evaluation process.
1 Character: A measure of the reputation of the firm, its willingness to repay, and its repayment history In particular, it has been established empirically that the age of a firm is a good proxy for its repayment reputation
2 Capital: The equity contribution of owners and its ratio to debt (leverage)
These are viewed as good predictors of bankruptcy probability High leverage suggests a greater probability of bankruptcy
3 Capacity: The ability to repay, which reflects the volatility of the borrower’s earnings If repayments on debt contracts follow a constant stream over time, but earnings are volatile (or have a high standard
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4 Collateral: In the event of default, a banker has claims on the collateral pledged by the borrower The greater the priority of this claim and the greater the market value of the underlying collateral, the lower the exposure risk of the loan
5 Cycle (or Economic) Conditions: The state of the business cycle; an important element in determining credit risk exposure, especially for cycle- dependent industries For example, durable goods sectors tend to be more cycle-dependent than nondurable goods sectors Similarly, industries that have exposure to international competitive conditions tend to be cycle- sensitive Taylor (1998), in an analysis of Dun and Bradstreet bankruptcy data by industry (both mean and standard deviation), finds some quite dramatic differences in U.S industry failure rates during the business cycle
In addition to the 5 Cs, an expert may also take into consideration the level of interest rate
Many expert systems rely on induction to replicate human decision-making, addressing the challenges of time-consuming and error-prone computerized expertise systems Artificial neural networks have emerged as effective solutions, simulating the human learning process by analyzing the relationships between inputs and outputs These networks learn through repeated sampling of input/output data, improving their accuracy in decision inference.
An internal rating system is essential for financial institutions to effectively manage and control credit risks associated with lending and other operations It evaluates and categorizes borrowers’ creditworthiness and assesses the quality of credit transactions, enabling better risk management Financial institutions rely on these internal rating systems for the origination and continuous monitoring of loans, ensuring sound credit practices and minimizing potential losses (Bank of Japan, August 2005).
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Banks have refined their pass/performing loan categories over the years by subdividing them into detailed internal rating systems, typically on a scale from 1 to 9 or 1 to 10 These ratings help assess the likelihood of default, acknowledging that even loans classified as performing carry a probability of default, thus necessitating appropriate reserve provisions This systematic approach ensures effective risk management and financial stability within banking institutions.
Bond Rating Score Risk Level
Table 2.2: Example of a loan rating system and bond rating mapping
Source: Adapted from Saunders A & Allen L, 2002
Credit scoring, as defined by Benton and James (2005), involves using statistical, operational research, and data mining models to assess the credit risk of potential borrowers A credit score is a numerical value generated by credit bureaus or companies like Fair Isaac Corporation's FICO score, which plays a crucial role in making informed credit decisions and other financial assessments This data-driven approach helps lenders evaluate borrower reliability efficiently and accurately.
The advantages of using credit scoring model are that they reduce the cost of evaluating credit and increase the speed, consistency, and accuracy of credit decisions
Credit scores reflect the past financial behavior of similar groups of borrowers and serve as an essential tool for assessing creditworthiness A high credit score indicates lower credit risk, making it easier for borrowers to access favorable loan terms Different lenders set their own minimum thresholds based on their risk appetite, often utilizing specific credit rating systems to evaluate potential borrowers.
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• FICO scores of 720 and above: Excellent credit
• 584 and below: Very-high-risk-credit
2.5.2 Modern approaches 2.5.2.1 Value At Risk (VAR):
Adapted from Anthony Saunders (2002), VAR is a technique used to estimate the probability of portfolio losses based on the statistical analysis of historical price trends and volatilities
Value at Risk (VAR) is a crucial tool for financial institutions focused on assessing their exposure to significant losses It helps answer critical questions like, "What is my worst-case scenario?" and "How much could I potentially lose during a very bad month?" By estimating potential losses in adverse conditions, VAR enables banks and financial firms to manage risk effectively and ensure financial stability.
A VAR (Value at Risk) statistic comprises three essential components: the time period, the confidence level, and the loss amount or percentage Understanding these elements is crucial when analyzing potential financial risks, as they determine the scope and severity of possible losses For example, VAR helps quantify the maximum expected loss over a specific time frame at a given confidence level, providing valuable insights for risk management By focusing on these key factors, organizations can better assess and prepare for potential adverse financial scenarios.
• What is the most I can - with a 95% or 99% level of confidence - expect to lose in default on loan repayment over the next month?
• What is the maximum percentage I can - with 95% or 99% confidence - expect to lose over the next year?
Since the 1980s, banks have effectively implemented modern portfolio theory (MPT) to manage market risk, enhancing their risk assessment strategies Today, many financial institutions utilize advanced models such as earnings at risk (EAR) and value at risk (VAR) to monitor and control their interest rate and market risk exposures These quantitative tools enable banks to better understand potential losses and optimize their risk mitigation efforts in a dynamic financial environment.
Unfortunately, however, even though credit risk remains the largest risk facing most banks, the practical of MPT to credit risk has lagged (William Margrabe, 2007)
Banks recognize how credit concentrations can adversely impact financial performance
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As a result, a number of sophisticated institutions are actively pursuing quantitative approaches to credit risk measurement, while data problems remain an obstacle
External factors that affect the level of credit risk
Financial deregulation is defined by Casu, Girardone and Molyneuz (2006, p.37) as:
The removal of controls and regulations that previously protected financial institutions, particularly banks, marks a significant shift in the banking industry Historically, governments imposed strict regulations on banks to maintain the stability of the national financial system This deregulation trend has implications for financial stability, risk management, and the overall health of the banking sector.
Furthermore, governments tend to protect their domestic banks from competition, especially from foreign banks by setting complicated barriers and requirements
Globalization has expanded banks' operations beyond their domestic markets, increasing competition in the banking industry In this context, government control may hinder rather than support banks' growth and stability Consequently, financial deregulation has become an inevitable trend in modern banking systems, fostering innovation and competitiveness in a globalized economy.
Financial deregulation offers significant benefits by granting banks greater operational freedom, but it also introduces notable challenges The reduction of government control allows banks to operate more independently; however, this increased independence entails higher risks, as banks must now shoulder full responsibility for their decisions without government intervention Consequently, modern banks face heightened threats from elevated risk levels, often due to the misuse of their newfound freedom to extend credit to high-risk businesses.
2.6.2 Supervision and re-regulation Re-regulation is defined as: The process of implementing new rules, restrictions and controls in response to market participants efforts circumvent existing regulations (Casu, Girardone and Molyneuz, 2006, p.38)
Deregulation in the banking sector has led to an increase in credit risk within the current financial system To address this, governments worldwide, as highlighted by Hubbard (2008), strive to regulate financial markets and institutions to ensure stability and reduce potential risks.
• Ensuring that all participants in the financial system have the opportunities to access to timely and accurate information in order to make their financial decisions
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• Maintaining the stability and safety of the overall banking sector by preventing the failures of banks
In July 2008, the G30 (Group of Thirty), comprising leading financial experts from public, private, and academic sectors, launched the project "Financial reform: a framework for financial stability." This initiative analyzed the global financial crisis and highlighted the crucial role of robust supervisory systems and central bank functions in managing risks, particularly credit risk, to maintain the stability of the global banking system.
2.6.3 Competition Before the deregulation process, in most countries, governments highly regulate and control the banking industry and protect domestic banks from competition especially from foreign banks The main objective was to ensure the stability of banking system and prevent banking crises (Lange et al 2007)
There are contrasting opinions on the impact of competition on banking system stability Some scholars, including Smith (1984), Keeley (1990), Repullo (2004), and Benton E Gup et al (2005), argue that increased competition encourages banks to engage in riskier activities, potentially threatening stability Conversely, theoretical studies by Caminal and Matutes (2002) and Mishkin (1999) suggest that competition can enhance stability by promoting efficiency and reducing moral hazard.
Research by 2009 highlights that an uncompetitive or highly concentrated banking industry tends to promote risk-taking behavior among bank managers This occurs because managers often believe they will be rescued by government bailouts if their banks face failure, reducing their incentives to exercise caution and increasing the likelihood of risky financial decisions.
Recent financial crises highlight that increasing competition significantly raises credit risk in the banking industry, threatening bank profitability and market position As banks lose control over traditional lending to the commercial paper market and securitization, they are compelled to engage in riskier areas like subprime mortgages and credit cards to sustain profits Consequently, the complexity of banks’ lending operations has grown, making it more challenging to effectively monitor and manage risks.
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Internal factors that affect the level of credit risk
The recent financial crisis originating in the U.S has significantly impacted the global financial system and the world economy Key effects include the collapse of the housing market, a slowdown in the global economy, increased difficulties within the financial sector, and rising unemployment rates These issues stem from high levels of credit risk in banks, highlighting the urgent need for improved risk management As a result, financial experts worldwide have begun to prioritize and strengthen credit risk management practices within the banking industry to ensure greater financial stability.
2.7 Internal factors that influence NPL ratio
Chau (2009) proposed a comprehensive credit risk management strategy model for Vietnamese banks, emphasizing four critical factors: accurate and timely credit information, skilled and ethical staff, significant investment in technology and innovation, and clear, well-communicated loan policies These elements are essential for effectively mitigating credit risks and ensuring financial stability within the banking sector.
Credit information that banks collect for making lending decisions is in terms of borrower’s characteristics, loan purposes, the primary and secondary sources of loan repayment (Sinkey 1998)
Accurate and timely credit information is essential for banks to assess a loan applicant’s willingness and capacity to repay It plays a critical role in reducing credit risk by ensuring loans are granted to suitable customers Without up-to-date credit data, banks face significant challenges in making well-informed lending decisions, ultimately protecting financial stability and fostering responsible lending practices.
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In their 2005 book "Commercial Banking," Benton E Gup and James W Kolari discuss the crucial role of asymmetric information in credit risk management They explain that asymmetric information refers to the unequal distribution of information between the bank and the borrower, which can significantly impact lending decisions and risk assessment Understanding this information imbalance is essential for effective credit risk mitigation and improving financial stability in banking.
Asymmetric information occurs when borrowers have more knowledge about their financial situation than banks, leading to the risk of adverse selection where higher-risk borrowers are more likely to be attracted to loans This information imbalance also creates moral hazard issues post-loan disbursement, as borrowers may engage in riskier activities with the borrowed funds to seek higher returns Such risky behavior increases the likelihood of loan default, posing significant challenges for lenders.
Chau (2009) emphasized the vital role of credit information in strengthening Vietnamese banks’ ability to manage credit risk, highlighting four key aspects: the impact of credit information, sources of credit data, the sharing of credit information among institutions, and the importance of credit information checking.
According to Hempel and Simonson (1999), banks need reliable credit information sources to enhance credit quality and manage credit risk effectively They identify three primary sources of credit information: customers, internal bank records, and external institutions However, collecting information from these sources can pose challenges, affecting the accuracy and reliability of credit assessments.
First, there is a conflict interest between banks and borrowers in lending practices
Borrowers typically have a better understanding of their financial situation than banks do, which can lead to concealed information during the loan application process This tendency to hide financial details increases the risk for banks, as relying solely on borrowers’ self-reported data may result in inaccurate assessments Accurate credit evaluation is essential for banks to mitigate risks and make informed lending decisions.
Banks can utilize their existing database to collect credit information for borrowers with whom they already have a relationship However, upgrading technology systems to access and analyze this data requires significant financial investment.
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Banks can gather valuable information from third-party sources such as suppliers, credit rating agencies, or other banks, enhancing their ability to make informed lending decisions However, reliance on third-party data also introduces risks, as inaccurate or outdated information from these sources can lead to poor lending outcomes Therefore, while third-party information can serve as an additional reference, banks must verify and validate these data to mitigate potential errors.
Advancements in technology are transforming banking operations, particularly in the lending sector Modern banks leverage technology to efficiently store, transmit, and analyze credit information, streamlining the decision-making process The use of sophisticated statistical techniques enables more accurate predictions of customer default risk, leading to better credit assessments Consequently, technological support has made the credit analysis process faster and easier, improving overall lending efficiency (Ritter, Silber & Udell, 2000).
The banking industry is highly reliant on information technology due to its unique products and services involving large volumes of customers' confidential data and funds To maintain competitive advantage, financial institutions worldwide invest billions of dollars annually in advanced computer systems and technological infrastructure This IT investment is essential for enhancing operational efficiency, security, and customer service in the financial sector (Seymann, 1998).
Technology streamlines manual processes, enabling efficient and effective information management in banks By leveraging advanced technological solutions, financial institutions can reduce operating costs while boosting staff productivity and accuracy, leading to improved overall efficiency.
Summary
This chapter combines essential insights into credit risk management, providing an overview of key concepts such as the main functions of banks, the lending process, and the factors influencing the level of credit risk It covers critical aspects of credit risk measurement and strategies for effective management Additionally, the chapter highlights four vital internal factors that play a significant role in managing credit risk, offering a comprehensive understanding for readers interested in banking and financial risk mitigation.
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Chapter 2: Literature Review Page 36 including credit information, technology and innovation, loan policy, ethic and skills of credit staff are also mentioned In summary, literature review is a preparation step which provides readers an adequate knowledge for the next chapters nghiep do wn load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg