• The Journal of Information Technology
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• v.8 no.3
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• pp.11-23
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• 2005

This paper study the way of increasing the credit loan for the Venture Companies. They are very important in national economics. But they are short of financial and mortgage although they have many kinds of superb ideas and technologies. Korean government has tried to financially support them. But the support has had its own limit. Banks and other financial institutions have not been in a positive position to loan money out to venture companies because their businesses are highly risky. The credit evaluation system of medium and small business are need to improve in order to increase the Venture Companies. loan. So, it is necessary to find new measures to activate credit loans to them.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.441-456
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• 2005

The purpose of this paper is to introduce the concept of negative DEA, which aims at identifying worst performers by placing them on the efficient frontier, This paper also proposes to use a layering technique instead of the traditional cut-off point approach, since this enables incorporation of risk attitudes and risk-based pricing. The results of the empirical application on credit risk evaluation validate the method which is proposed in this paper.

• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.312-314
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• 2008

This paper develops an algorithm for probabilistic production cost credit evaluation of wind turbine generators (WTG) with multi-state. Renewable energy resources such as wind, wave, solar, micro hydro, tidal and biomass etc. are becoming importance stage by stage because of considering effect of the environment. Wind energy is one of the most successful sources of renewable energy for the production of electrical energy. Case study demonstrates that the wind speed credit in view point of economics can be assessed by using the proposed methodology.

• Information Systems Review
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• v.9 no.2
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• pp.129-147
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• 2007

At the time the local credit-card companies plunged into a liquidity crisis in 2002, S-Card was urged to take into account the estimated customer income (ECI) to enhance its customer credit evaluation function for the first time in Korean financial industry. Before this new attempt by S-Card, most credit-card companies including S-Card had performed a customer's credit evaluation based on the customer's behavioral factors such as the amount of purchase on credit, debt payment, and financial history that is provided from the Credit Bureau. However, this approach failed to measure customer's potential value which is one of the major factors in judging the customer's ability to pay, and hence, led to difficulties in risk management. The purpose of this case study is to present the better approach to sophisticated risk management for financial firms in Korea by reviewing S-Card's process of customer income estimation and its application to risk management.

• 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.

• Knowledge Management Research
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• v.18 no.1
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• pp.67-81
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• 2017

As the important breakthrough continues in the field of machine learning and artificial intelligence recently, there has been a growing interest in the analysis and the utilization of the big data which constitutes a foundation for the field. In this background, while the economic value of the data held by the corporates and public institutions is well recognized, the research on the evaluation of its economic value is still insufficient. Therefore, in this study, as a part of the economic value evaluation of the data, we have conducted the economic value measurement of the data generated through the small business guarantee program of Korean Federation of Credit Guarantee Foundations (KOREG). To this end, by examining the previous research related to the economic value measurement of the data and intangible assets at home and abroad, we established the evaluation methods and conducted the empirical analysis. For the data value measurements in this paper, we used 'cost-based approach', 'revenue-based approach', and 'market-based approach'. In order to secure the reliability of the measured result of economic values generated through each approach, we conducted expert verification with the employees. Also, we derived the major considerations and issues in regards to the economic value measurement of the data. These will be able to contribute to the empirical methods for economic value measurement of the data in the future.

• Journal of the Korean Home Economics Association
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• v.41 no.12
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• pp.117-132
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• 2003

This study aims to develop an educational program in using credit card for undergraduate students. In order to achieve this aim, a processor has been followed. first of all, a fundamental work to select the educational contents was Preceded with a survey of learners' needs, case studies of counselling at Consumer Protection Board, and preceding studies. After choice of educational contents, learners' demands on how to manage the educational program was executed in advance. Second, reflecting the above mentioned educational contents, a concrete educational program was built. Based on the constructed plans, both preliminary training and main training were proceeded. Third, to evaluate the effects of the educational program, the knowledge difference, behaviors and attitude changes were all diagnosed. The result suggested that the educational effect was significant in all evaluations section. At last, final program of using credit cards was completed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.30-45
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• 2024

This study introduces an effective method for predicting individual local tax delinquencies using prevalent machine learning and deep learning algorithms. The evaluation of credit risk holds great significance in the financial realm, impacting both companies and individuals. While credit risk prediction has been explored using statistical and machine learning techniques, their application to tax arrears prediction remains underexplored. We forecast individual local tax defaults in Republic of Korea using machine and deep learning algorithms, including convolutional neural networks (CNN), long short-term memory (LSTM), and sequence-to-sequence (seq2seq). Our model incorporates diverse credit and public information like loan history, delinquency records, credit card usage, and public taxation data, offering richer insights than prior studies. The results highlight the superior predictive accuracy of the CNN model. Anticipating local tax arrears more effectively could lead to efficient allocation of administrative resources. By leveraging advanced machine learning, this research offers a promising avenue for refining tax collection strategies and resource management.

• Asia pacific journal of information systems
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• v.15 no.1
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• pp.45-61
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• 2005

This study develops the evaluation model for e-Business company using analytic hierarchy process. As the first step of this study, we derived the appraisal standards based on the previous literature and the knowledge of experts from venture capitalists, security companies, credit evaluation companies, and consulting firms. In order to validate the evaluating factors in the models, this study was supported by analysts of top ranked venture capitalists in Korea. Through their assistance, this study can determine necessary evaluating factors that refined and deepened the models. Four expert groups, such as venture capitalists, credit analysts, analysts of security company and e-Business consultants, provide their knowledge for the determination of the weights of evaluating factors in the hierarchical model through the questionnaires and interviews. The results show that the weights of the evaluating factors differed by the maturity of e-Business company.

• International Commerce and Information Review
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• v.13 no.1
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• pp.179-196
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• 2011

This study aims to measure the relative importance of trade insurance using AHP developed by Thomas Saaty of Pennsylvania in early 1970s. Moreover, it provides help in the development of a comprehensive strategy of trade insurance. To obtain priority of trade insurance in its functions, this study discovered significance and relative importance of two evaluation standards and four individual evaluation items. Of the two evaluation standards, importance of credit exposure was 63%. It was discovered that it was more important than political means (37%). Of the four individual evaluation items, importance of banking supplementation was 60%. It was more important than credit investigation of overseas traders (40%). Importance of trade promotion policy was 69%, which was more important than removal of anxiety in trade (31%). As a result of comparing priorities of the f tire evaluation items, priority of banking supplementation was 38% followed by trade promotion policy means (26%), credit investigation of overseas traders (25%) and removal of anxiety in trade (12%).