• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.55-65
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• 2019

The purpose of this study is to discover the interaction between credit growth and operational self-sustainability and to examine factors that affect credit growth and operational self-sustainability of people's credit funds (PCFs). Credit growth and operational self-sustainability are factors affecting the operations and the goals of people's credit funds (PCFs) in the Mekong Delta region of Vietnam. After regression analysis on a set of panel data from 2013 to 2018 of 24 PCFs, it appears that deposit growth and loan-to-deposit ratio have positive relationships with credit growth, while capital adequacy ratio and operational self-sustainability have negative relationships with credit growth of PCFs; capital adequacy ratio, deposit growth and income have positive relationships with operational self-sustainability, while credit growth and non-performing loan ratio have negative relationships with the operational self-sustainability of PCFs. At the same time, credit growth and operational self-sustainability have a relationship to interact with each other in a contrary trend. The results of this research are accurate according to the characteristics and development history of PCFs in the Mekong Delta region of Vietnam from 2013-2018. This study helps researchers and managers to understand the key determinants for better management of PCFs.

• The Journal of Information Systems
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• v.16 no.3
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• pp.1-20
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• 2007

Most researches on the corporate credit rating are generally classified into the area of bankruptcy prediction and bond rating. The studies on bankruptcy prediction have focused on improving the performance in binary classification problem, since the criterion variable is categorical, bankrupt or non-bankrupt. The other studies on bond rating have predicted the credit ratings, which was already evaluated by bond rating experts. The financial institute, however, should perform effective loan evaluation and risk management by employing the corporate credit rating model, which is able to determine the credit of corporations. Therefore, this study presents a corporate credit rating method using business failure probability map(BFPM) and AHP(Analytic Hierarchy Process). The BFPM enables us to rate the credit of corporations according to business failure probability and data distribution or frequency on each credit rating level. Also, we developed AHP model for credit rating using non-financial information. For the purpose of completed credit rating model, we integrated the BFPM and the AHP model using both financial and non-financial information. Finally, the credit ratings of each firm are assigned by our proposed method. This method will be helpful for the loan evaluators of financial institutes to decide more objective and effective credit ratings.

• The Journal of Fisheries Business Administration
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• v.39 no.1
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• pp.43-61
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• 2008

Excessive public loan with low interest and other tax benefits have been provided for fishermen, but much of them turned out to be little performed. There were the moral hazards of Suhyup in the process of executing the public loans. As the government gave the reimbursement on the financial loss of Suhyup resulting from the public loans, Suhyup had no responsibility of the bad debt loss. Therefore, Suhyup gave little efforts to reduce the non-performing. The government perceived this problem and tried to reduce the under-performing loans. Thus, the government decided to take limited responsibilities. Suhyup made the progress to reduce the under-performing public loans. Suhyup dealt with these situation and made the credit evaluation model of the fisherman's public loan. This paper is for the credit evaluation model in the fisherman's public loan, which explains the model development methodology and the model characteristics in detail. This evaluation model is composed of two sub-component model. the one is the quantitative model and the other is the qualitative model. The quantitative sub-model is for the identification of fishermen financial status and is based on the financial transaction information. Its development methodology is the CSS modeling for the consumer market. The qualitative sub-model is for the evaluation the business prospect and is based on the business information such as fisherman's management skills, technology, equipment. Its development methodology is the AHP. It provides the detailed information in the model development methodology, which is the ideal example such as the public loan. In addition it gives the information to the interest parties such as policy makers, suhyup and fishermen.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.59-72
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• 2020

This paper examines whether lending structure can lower credit risk by employing econometric techniques of panel data for the Vietnamese banking system at the bank level used by economic sectors from 2011 to 2016. New light is being shed on assessing the impact of each industry's debt outstanding on credit risk. Adopting findings from previous studies, we assess credit risk from two different sources, including loan loss provision and non-performing loan. Moreover, we also focus on observing lending structure in many different aspects, from concentrative levels to the short-term and long-term stability levels of lending structure. The Generalized Method of Moments (GMM) estimator was applied to analyze the relationship between concentration and banking risks. In general, the results show that lending concentration may decrease credit risk. It is interesting to observe that the Vietnamese commercial bank lending portfolios have, on average, higher levels of diversity across different sectors. In particular, the increase in hotel and restaurant lending contributes to decrease credit risk while the lending portfolios of banks in agriculture, electricity, gas and water increase credit risk. This study suggests the need for further analysis and research about portfolio risks in lending activities for maintaining efficiency and stability in the commercial banking system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.1044-1051
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• 2002

This paper proposes a two-phase mathematical programming approach by considering classification gap to solve the proposed credit scoring problem so as to complement any theoretical shortcomings. Specifically, by using the linear programming (LP) approach, phase 1 is to make the associated decisions such as issuing grant of credit or denial of credit to applicants. or to seek any additional information before making the final decision. Phase 2 is to find a cut-off value, which minimizes any misclassification penalty (cost) to be incurred due to granting credit to 'bad' loan applicant or denying credit to 'good' loan applicant by using the mixed-integer programming (MIP) approach. This approach is expected to and appropriate classification scores and a cut-off value with respect to deviation and misclassification cost, respectively. Statistical discriminant analysis methods have been commonly considered to deal with classification problems for credit scoring. In recent years, much theoretical research has focused on the application of mathematical programming techniques to the discriminant problems. It has been reported that mathematical programming techniques could outperform statistical discriminant techniques in some applications, while mathematical programming techniques may suffer from some theoretical shortcomings. The performance of the proposed two-phase approach is evaluated in this paper with line data and loan applicants data, by comparing with three other approaches including Fisher's linear discriminant function, logistic regression and some other existing mathematical programming approaches, which are considered as the performance benchmarks. The evaluation results show that the proposed two-phase mathematical programming approach outperforms the aforementioned statistical approaches. In some cases, two-phase mathematical programming approach marginally outperforms both the statistical approaches and the other existing mathematical programming approaches.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.624-626
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• 2023

Credit scoring is a technique used by financial institutions to assess the creditworthiness of potential borrowers. This involves evaluating a borrower's credit history to predict the likelihood of defaulting on a loan. This paper presents an ensemble of two Transformer based models within a framework for discriminating the default risk of loan applications in the field of credit scoring. The first model is FinBERT, a pretrained NLP model to analyze sentiment of financial text. The second model is FT-Transformer, a simple adaptation of the Transformer architecture for the tabular domain. Both models are trained on the same underlying data set, with the only difference being the representation of the data. This multi-modal approach allows us to leverage the unique capabilities of each model and potentially uncover insights that may not be apparent when using a single model alone. We compare our model with two famous ensemble-based models, Random Forest and Extreme Gradient Boosting.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.361-371
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• 2010

This paper analyses the information contents of the trade credit in Korea. Trade credit is not only a settlement device in business cycle but also an information messenger in the financial market with an asymmetric information. The empirical results support that in addition to the bank loan, trade credit takes a significant role in that it provide a cheap and reliable credit to firms that have financial difficulties because of the information problem.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.365-373
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• 2021

Loan monitoring is a fundamental element of credit control. The importance of loan monitoring is to reduce loan defaults and to increase loan repayment performance. The ex-post monitoring can also increase the loan quality and thus a concern to many creditors in the market economy. This study identifies the role of ex-post monitoring on loan repayment performance in the context of rural Vietnam. Employing primary data from rural areas of Vietnam, this study investigates the impacts of ex-post monitoring on loan repayment performance of individual borrowers in terms of on-time loan repayment and the rate of loan repayment. Descriptions of borrower demographics, loan information, and ex-post monitoring show the initial picture of borrowers and loans in Vietnam's rural areas. Quantitative estimations that use the Probit and the Tobit model confirm the argument that better ex-post monitoring would result in better loan repayment performance in both on-time repayment and repayment rate. Thus, some policy suggestions have been made to improve the monitoring system in each financial institution. The study also indicates that some other factors too affect loan repayment performance such as borrower's characteristics (education, agricultural working area, and income) as well as loan's characteristics (loan size, maturity, and loan purpose).

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.411-425
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• 2013

The importance and necessity of the credit loan are increasing over time. Also, it is a natural consequence that the increase of the risk for borrower increases the risk of non-performing loan. Thus, we need to predict accurately in order to prevent the loss of a credit loan company. Our final goal is to build reliable and accurate prediction model, so we proceed the following steps: At first, we can get an appropriate sample by using several resampling methods. Second, we can consider variety models and tools to fit our resampling data. Finally, in order to find the best model for our real data, various models were compared and assessed.

• 한국벤처창업학회:학술대회논문집
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• 2007.11a
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• pp.81-109
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• 2007

The loan rate of the government loan program offered by the Small Business Corporation(SBC) can be determined as a sum of three factors such as a reference interest rate, a policy aim spread, and a credit risk spread. However the loan rate has been lower than the loan rate in the banking sector. The profit has continually run in the red figures and hence the stability the fund managed by the SBC has been damaged. Even though a policy aim spread could be emphasized, the stability and profitability of the fund should be prioritized. This means that the loan rate of the SBC should be determined such that the loss might not be occurred. This requires the policy aim spread to change from relatively large negative to near zero.