• KDI Journal of Economic Policy
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• v.27 no.1
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• pp.39-79
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• 2005

This paper addresses the question of whether a monopolistic banking system can lead to a higher steady state level of capital stock. Information externality has enhanced as the advance of the financial system such as the establishment of the credit bureau system, networking, etc. Hence this paper aims to analyze the effects of both information externality and economic development on the determination of the optimal banking market structure. This paper shows that the presence of information externality together with asymmetric information would explain how a monopoly bank leads to a higher steady state level of capital stock. It also shows that not only under-developed countries but industrialized countries may also benefit from a concentrated banking system. This analysis provides an alternative explanation of the recent deregulation and resulting trends in mergers and acquisitions. This also provides a theoretical foundation to support governments' policy changes toward promoting merger and acquisition activities.

• Journal of Convergence for Information Technology
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• v.10 no.1
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• pp.1-12
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• 2020

The Government provides a financial assistance to stimulate firm R&D and innovation activities. Previous papers on the impact of public subsidies on firm R&D investments mainly had a focus on an individual policy tool regardless of potential impacts of other policy instruments. This study addresses this gap by examining the effects of policy mix regarding a subsidy and a tax credit. The empirical analyses from fixed effect model using Survey on Technology of SMEs 2015-2017 revealed valuable points. First, policy mix induces more R&D investment of SMEs, which in turn, shows a complementary relationship between two instruments. Second, even if impact of tax credit controlled, subsidy is positively associated with SMEs R&D investment. These findings justify policy mix interventions to promote SME R&D activity. Moreover, grants can be applied as a more useful policy tool for SMEs that are constrained by resources and capabilities.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.11-20
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• 2016

This study examines the possibility of implementing the technology financing for export-import based small and medium sized enterprises. Our sample consists of 2,753 small and medium sized enterprises, receiving financial support from the Export-Import Bank of Korea for the period of 2011-2013. We find that only 400(200) firms reserve IPs(patents) annually. Given that IPs are likely to concentrate on manufacturer industries such as electronic components, computers, video, sound and communication equipment manufacturing(KSIC 26), other machinery and equipment manufacturing(KSIC 29), manufacture of motor vehicles and trailers(KSIC 31). We also find that the total assets, sales and R&D expenses of IP holding companies greatly exceeds those of companies without IPs. In addition, IP holding companies' liquidity seems slight edge and the leverage ratio is somewhat lower. However, profitability ratios of IP holding companies are rather than harsh or similar level. 20~30% of IP holding firms show very week credit scores, implying that banks' default risk is expected to be significant.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.303-309
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• 2021

This study examines the effects of CBDC(Central Bank Digital Currency) on the Korean economy in the digital currency era and discusses the response strategies for CBDC. With the review of the definition and the development status of digital currency, we explore the characteristics and current status of CBDC in Korea as well as the possibility for internationalization of CBDC. The result shows that CBDC can reduce credit risk, improve transaction transparency compared to cash, and increases monetary policy capacity. Meanwhile, the credit and intermediary function of financial institutions may be weakened, and side effects such as financial alienation may occur. Nevertheless, as the issuance of CBDC is an important opportunity to enhance the possibility of internationalization of Korean Won, preemptive measures are required to keep pace with the competition and cooperation with each country toward the digital key currency. We need to accelerate the digital financial environment through Korea's comparative advantage, and develop a strategy to achieve the internationalization of the financial industry and the Korean Won through CBDC issuance. From the early stage of CBDC designing, it is necessary to achieve international agreements through cooperation with other central banks and to develop policies suitable for the transition to digital currency.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.211-222
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• 2020

This study examines simultaneous relationships between regulatory capital, risk, and cost-inefficiency for a sample of 30 commercial banks in Bangladesh from 2006 to 2018. To conduct the analysis, we used the Generalized Methods of Moments (GMM) in an unbalanced panel data framework. The empirical results show that there is a negative and significant relationship between capital regulation and credit, and overall risk. It is also evident from the results that the capital adequacy ratio is positively and significantly related to default risk and liquidity risk. Therefore, higher capitalized banks take an effort to prevent more credit risk and promote financial stability by reducing liquidity risk. Results also report that banks have been characterized as inefficient, less capitalized, and high risk. On the other hand, efficient banks are more stable but have a high level of liquidity risk. Besides, from the size of the bank, large banks are defined as having lower regulatory capital, are more risk seekers but stable with higher cost-efficiency. Notably, higher capitalized banks are more profitable and cost-efficient by reducing risk. Finally, this study also provides some insightful policy suggestions to the stakeholders.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.151-156
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• 2020

Small and medium enterprises (SMEs) play a very important role in developing countries. In Vietnam, SMEs operating in the field of handicrafts, besides contributing to the economy, also tasked to maintain and develop traditional handicrafts. However, accessing loans from banks of SMEs faces many difficulties. This study explores the determinants of bank lending decision for SMEs, particular, in traditional handicrafts business. Using dataset based on a survey conducted in Binh Duong province, Vietnam, we investigated to what determinant effects for loan approval. The analytical methods used include descriptive statistics for overall assessment, principal component analysis and regression to examine determinants of lending decisions. The results indicate that company's collateral was the most positive determinant to bank lending decision, follow by company's business plan. The role of company's leader is very important for banks considers to approve credit because company's leaders experience and relationship with stakeholders as well as banks have positive relations with bank's lending decision. Agreed with previous studies, the company's financial statement and company's credit history with banks are also significant determinants for lending decision. Whereas, the business environment seam unaffected lending decision as their relations is not significant..

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.369-376
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• 2020

Credit capital from customers' savings deposit (CSD) of banks has an important meaning in the business activities of the banking industry. There are many factors that influence the CSD satisfaction with banks. Certain changes have been made when there are fluctuations due to COVID-19. The article is based on an analysis assessing the factors that influence the CSD satisfaction of Vietnamese commercial banks in the context of COVID-19. The authors use a sample of 1,639 CSD. The results show that there are three variables that positively affect CSD satisfaction, including legal provisions of the Central bank (Legal), policies and mechanisms of commercial banks (Policy), and products of commercial banks (Product). Accordingly, in order to contribute to strengthening this capital mobilization of savings deposit, the Central bank of Vietnam needs to play a pivotal role in the regulations of the banking system to ensure its stability; control well monetary policy, interest rates, and inflation to keep a stable position in the economy; and provide timely financial support packages to enhance the confidence of CSD. Moreover, Vietnamese commercial banks need flexible policies and mechanisms to stimulate CSD; strengthen support on deposit rates for CSD; and diversify products to easily adapt to each CSD's situation.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.67-76
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• 2019

As the attracting foreign student has become a very important strategy, detailed researches on their college selection and their satisfaction with college life are needed. Especially it is necessary to distinguish ordinary international students and those who take classes in Local Education Centers (LEC) before coming to Korea. The central purpose of this study is to identify how the two types of students differ in their perception of college selection factors and what factors affect their satisfaction with college life. A total of 186 international students participated in the study. It was found that the most important college selection factor of the pre-educated LEC students was 'obtaining academic ability through online classes and transfer of credit hours'. Second, these students reported that the two influential factors for their satisfaction with college life were 'quality of education' and 'cultural experience program'. Third, it was found that the major college selection factors influencing ordinary international students' college life satisfaction were 'expertise of faculty', 'transfer of credit through curriculum links', and 'recommendation from teachers at home country'. Fourth, the major factors affecting the pre-educated LEC students' satisfaction with college life were 'KSL classes at LE's', 'expertise of faculty', and 'financial aid system'.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.699-707
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• 2021

The objective of this study is to examine the determinants of the liquidity of 17 commercial banks listed on the Vietnamese Stock Exchanges, HOSE, HNX and UPCoM. The study uses the quarterly audited financial statements from the first quarter of 2006 to first quarter of 2020; it includes 496 observations. Data on GDP and inflation are compiled from the International Monetary Fund and the General Statistics Office of Vietnam. Once collected, the data were organized along the line of unbalanced panel data. The results show that total asset size, return on total assets, and credit growth are positively associated with the liquidity of the listed banks; whereas the interaction between the bank size and the return on total assets has a negative impact on the liquidity of commercial banks listed on the HNX, HOSE, UPCoM. In order to maintain good liquidity, commercial banks need to focus on effective credit growth, ensure a high rate of profit over total assets, and at the same time focus on developing the scale of total assets. However, the development of the size of the total assets should be noted in the balance between the total assets and the rate of return on the total assets.