• Asia-Pacific Journal of Business
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• v.14 no.2
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• pp.51-61
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• 2023

Purpose - Since COVID-19, the government's expansion of liquidity to stimulate the economy has resulted in an increase in private debt and an increase in asset prices of such as real estate and stocks. The recent sharp rise of the US Federal fund rate and tapering by the Fed have led to a fast rise in domestic interest rates, putting a heavy burden on the Korean economy, where the level of household debt is very high. Excessive household debt might have negative effects on the economy, such as shrinking consumption, economic recession, and deepening economic inequality. Therefore, now more than ever, it is necessary to identify the causes of the increase in household debt. Design/methodology/approach - Main methodology is regression analysis. Dependent variable is household loans from depository institutions. Independent variables are consumer price index, unemployment rate, household loan interest rate, housing sales price index, and composite stock price index. The sample periods are from 2017 to May 2022, comprising 72 months of data. The comparative analysis period before and after COVID-19 is from January 2017 to December 2019 for the pre-COVID-19 period, and from Jan 2020 to December 2022 for the post-COVID-19 period. Findings - Looking at the results of the regression analysis for the entire period, it was found that increases in the consumer price index, unemployment rate, and household loan interest rates decrease household loans, while increases in the housing sales price index increase household loans. Research implications or Originality - Household loans of depository institutions are mainly made up of high-credit and high-income borrowers with good repayment ability, so the risk of the financial system is low. As household loans are closely linked to the real estate market, the risk of household loan defaults may increase if real estate prices fall sharply.

• International Area Studies Review
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• v.15 no.1
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• pp.173-193
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• 2011

Most of the research regarding economic effects of policy loans has thus far been focused on whether policy loans can improve the financial status or the management performance of small and medium enterprises (SMEs). Unlike previous researches, this study implemented an empirical analysis focused on the contribution of policy loans to easing the liquidity restriction of investment. To analyze whether investment liquidity restriction can be alleviated or not, this study attempted an empirical analysis utilizing the nonlinear Euler equation induced through optimization of investment and GMM (generalized method of moments) as its analysis methodology. With the SMEs that received policy financing from the Small and medium Business Corporation (SBC) in 2004, this study analyzed three years of panel data before(2001~2003) and after(2004~2006) receipt of policy loans. According to the empirical results, it appears that policy loans had effects on resolving liquidity restriction of investment, implying that policy financing eases the liquidity restriction of SME investment and would contribute to the growth and development of SMEs. Further, I checked robustness of empirical results using Tobin's q model. The empirical results also support that policy loans help to resolve liquidity constraint. With these results, it is understood that the critical view to date, which has emphasized the ineffectiveness of policy financing due to it having no or insignificant economic effects, may be wrong.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.17-24
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• 2011

The government supports politic funds to Small Business having difficulties of insufficient capital and weak assets. Also the effect of governmental politic funds are evaluated better than the effect of substitute loans of the commercial bank. Especially governmental politic funds contribute to the external growth of the enterprise sales and the increment of total assets size. It is necessary however related supporting programs with funding provision to reduce the risk of insolvency politic funds of small business and reinforce the competitive power of company. This paper introduces the model of the corporate diagnosis system of the Small Business Corporation as part of these intention and analysis supported companies' management performance last four years and proposes direction of development.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.137-144
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• 2012

Seventeen domestic banks, Hongkong & Shanghai Banking Corporation Ltd. and Korea Post provide their subscribers with banking services such as statement service, funds transfer, and application for loans through Internet banking sites, which have become ever-increasing banking services for individual and corporation and government subscribers. First, this study aimed at presenting a process of determining factors to measure customers' perception while using Internet banking for doing transactions. Secondly, this paper attempted to unveil a list of major factors that Internet banking customers perceive while accessing the web sites to do their business with their banks. This study also suggested the features of those factors, which would help improve our understanding of Web usage for Internet banking. This result of the paper will lead further understanding of factors associated with Internet uses in other economic activities, which enable practitioners such as web designers and security specialists to provide Internet banking subscribers with better services in a safe and convenient web pages.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.18
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• pp.159-188
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• 2002

International joint ventures are usually formed and managed by domestic companies and foreign investors for the common objectives. They offer an opportunity for each partner to benefit significantly from the comparative advantages of the other. Local partners bring knowledge of the domestic market; familiarity with government bureaucracies and regulations; understanding of local labor markets; and existing manufacturing facilities. Foreign partners can offer advanced process and product technologies, management know-how, and access to export markets. In Korea, joint ventures have been encouraged to usher in foreign investors with foreign currency capital badly needed during the IMF financial crisis. In the meantime, Korean laws and regulations with respect to joint ventures have been largely overhauled to promote foreign direct investment (FDI) both inbound and outbound. They include four types of FDI, i.e., acquisition of foreign stocks, provision of long-term loans, participation in joint operations like resources development, and establishment of foreign offices. From the legal point of view, the formal joint venture agreement must be an offspring of a series of tough negotiations between domestic and foreign partners. They usually stress the long-term relationship with the good will and dedication to each other, and restrict the free transfer of stocks. Both partners are earnestly interested in the ownership and management of the joint venture. So they keep a close eye on the articles of incorporation, changes of business environment, conflict resolution methods, transparency of accounting and other financial matters. When a multinational corporation (MNC) is involved in the joint venture, conflicts over management strategies, marketing and other issues take place more often than not between the MNC and local partners. We have to pay attention to joint ventures, particularly, in China and North Korea. As witnessed in other transition economies, China is eagerly bringing in foreign direct investments for the development of nation's economy. China encourages foreign investors to establish ordinary joint ventures, contractual joint ventures, solely invested foreign capital companies and jointly operated development companies with local partners. In North Korea, however, joint ventures have a different meaning like contractual joint ventures in China, in which North Korean partners have an initiative in the management. Rather, jointly operated companies or simply processing-for-wage companies are recommended in view of the unpredictable legal infrastructure in North Korea.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.4
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• pp.583-602
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• 2011

Based on the survey, this paper examines entrepreneurs' attitude toward corporate lending in Pusan region. The results show that the relationships of manufacturing firmswith banks are different from those of non-manufacturing firms. These are mainly due to the differences in the operational grounds between them. The non-manufacturing firms have their operational ground in Pusan, thus they have local banks as their mainbanks and depend heavily on mainbanks' credits. However the business network of the local banks is not broad enough to satisfy the manufacturing firms financial service needs. Therefore, the manufacturing firms maintain close relationship with not only regional local banks but also other banks. The results of the study demand the local banks to produce information of the regional firms and to monitor them more widely and tightly. One of the important contributions of this paper is that it has succeeded in making clear the importance of relationship banking of the local banks.

• Journal of Family Resource Management and Policy Review
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• v.24 no.4
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• pp.1-20
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• 2020

This study aims to improve the family friendly certification system by analyzing the actual experience of family friendly certified companies with the certification's incentives and their demand for new incentives. We analyzed 2018 survey data of family friendly certified company incentives and interviewed representatives from 9 family friendly certified companies. First, the use of incentives differs according to the level of corporate classification, number of employees, industry, certification continuation training, and incentive impact. Current family friendly certification incentives indicate that the utilization rate of incentives is high when small and medium sized enterprises (SMEs) with less than 300 employees have newly received family friendly certification. Second, the use of the certification mark significantly differs by industry, certification duration, and incentive impact. Interviews with the companies' family friendly certification managers revealed that the incentives that companies use mainly are the Public Procurement Service bid points and priority immigration service. Large corporations hope for strong incentives, such as the National Tax Service's deferred tax investigation, interest rate cuts for bank loans, and corporate tax cuts. Lastly, the family friendly certification mark is a representative incentive used by 60% of family friendly certified companies. For the qualitative growth and stabilization of the family friendly certification system, the family friendly certification mark should be improved to become a more attractive incentive.

• 한국무역상무학회:학술대회논문집
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• 2006.06a
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• pp.45-72
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• 2006

The Equator Principles are a set of voluntary environmental and social guidelines for ethical project finance. These principles commit banks and other signatories to not finance projects that fail to meet these guidelines. The principles were conceived in 2002 on an initiative of the International Finance Corporation and launched in 2003. Since then, dozens of major banks have adopted the Principles, and with these banks among them accounting for more than three quarters of all project loan market volume the Principles have become the de facto standard for all banks and investors on how to deal with potential social and environmental effects of projects to be financed. While regarding the Principles an important initiative, NGOs have criticised the Principles for not producing real changes in financing activities and for allowing projects to go through that should have been screened out by the Principles, such as the Sakhalin-II oil and gas project in Russia. In early 2006, a process of revision of the principles was begun. The Equator Principles state that endorsing banks will only provide loans directly to projects under the following circumstances: - The risk of the project is categorized in accordance with internal guidelines based upon the environmental and social screening criteria of the International Finance Corporation (IFC). - For all medium or high risk projects (Category A and B projects), sponsors complete an Environmental Assessment, the preparation of which must meet certain requirements and satisfactorily address key environmental and social issues. - The Environmental Assessment report addresses baseline environmental and social conditions, requirements under host country laws and regulations, applicable international treaties and agreements, sustainable development and use of renewable natural resources, protection of human health, cultural properties, and biodiversity, including endangered species and sensitive ecosystems, use of dangerous substances, major hazards, occupational health and safety, fire prevention and life safety, socio-economic impacts, land acquisition and land use, involuntary resettlement, impacts on indigenous peoples and communities, cumulative impacts of existing projects, the proposed project, and anticipated future projects, participation of affected parties in the design, review and implementation of the project, consideration of feasible environmentally and socially preferable alternatives, efficient production, delivery and use of energy, pollution prevention and waste minimization, pollution controls (liquid effluents and air emissions) and solid and chemical waste management. - Based on the Environmental Assessment, Equator banks then make agreements with their clients on how they mitigate, monitor and manage those risks through an 'Environmental Management Plan'. Compliance with the plan is required in the covenant. If the borrower doesn't comply with the agreed terms, the bank will take corrective action, which if unsuccessful, could ultimately result in the bank canceling the loan and demanding immediate repayment. - For risky projects, the borrower consults with stakeholders (NGO's and project affected groups) and provides them with information on the risks of the project. - If necessary, an expert is consulted. The Principles only apply to projects over 50 million US dollars, which, according to the Equator Principles website, represent 97% of the total market. In early 2006, the financial institutions behind the Principles launched stakeholder consultations and negotiations aimed at revising the principles. The draft revised principles were met with criticism from NGO stakeholders, who in a joint position paper argued that the draft fails by ignoring the most serious critiques of the principles: a lack of consistent and rigorous implementation.

• Knowledge Management Research
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• v.21 no.4
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• pp.195-210
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• 2020

Recently, the value of intellectual property rights including patents has been estimated for various purposes. In particular, the evaluation of loans, guarantees and collateral through patent valuation is increasing with the revitalization of technology financing. Although various studies have been conducted on patent valuation, little research has been done on the adequacy of patent valuation. In this study, using the DCF model, which is the most commonly used method of technology valuation, we examine the appropriateness of the patent valuation by comparing and analyzing the estimated value and actual value of the patent. An empirical result shows that the difference between estimated value and the actual value is statistically significant, and there is a significant difference between the estimated value and the actual value depending on the classification of evaluation work. In addition, while there is no difference between professors, patent attorneys, and researchers in the analysis of value differences according to technical evaluators, there is a significant difference between patent attorneys and other evaluators. Finally, we find a significant value difference between estimated value and actual value of technology subject to evaluation by industry.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.