• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.149-154
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• 2003

Credit scoring system (CSS) starts from an analysis of delinquency trend of each individual or industry. This paper conducts a research on credit card delinquency of bank customers as a preliminary step for building effective credit scoring system to prevent excess loan or bad credit status. To serve this purpose, we use association rules that ore generating method. Specifically, we generate sets of rules of customers who are in bad credit status because of delinquency by using association rules. We expect that the sets of rules generated by association rules could act as an estimator of good or bad credit status classifier.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.123-144
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• 2015

Through the event study methodology and the case study on the Company T and its subsidiaries, this study analyzes the effect of credit rating downgrade in the Korean stock market. Our empirical results cast some doubts on whether credit rating agencies made adequate credit rating adjustments on the Chaebol companies, and suggest that little information was provided to the bond market investors. This study provides some policy implications by recommending that regulators encourage credit rating agencies to provide more accurate and appropriate information to market participants.

• Journal of Technology Innovation
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• v.5 no.1
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• pp.181-205
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• 1997

There has been considerable controversy over the impacts of the tax credit on R&D expenditures in many countries. Korea has adopted various kinds of tax credit system to stimulate private firm' R&D expenditures. Korean government, Recently, is trying to reform tax system to reduce tax credit programmes according to Uruguay Round agreement and in line with OECD policy standards. The purpose of this paper is to analyze the effectiveness of current tax credit system on technology innovation in Korea and derive some policy implications over tax reform. In this paper, firstly, I investigate the size of tax reduction effects from each program in theoretical models and simulate the actual rate of individual tax incentive to a unit of R&D expenditure. I find that theoretically the reserve fund for technology development program has given the largest tax reduction effects to private firms irrespective of the R&D incentive system reform. Tax credit on R&D expenditure also has been very effective instrument to firm's tax reduction. Secondly, I try to measure the effectiveness of tax credit through the estimation of effective margianl tax rate between with the system and without the system of credit on R&D expenditure during the tax credit reform periods. I find that the tax credit on R&D has lowered firm's investment cost since the system introduced. I also have strong results that there has been a positive relation between the fluctuation of firm's R&D expenditure and the change of effective marginal tax rate. I suggest that it is better to sustain the system of tax credit on R&D for a while to increase firm's R&D expenditure.

• Journal of the Korea Convergence Society
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• v.7 no.4
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• pp.9-17
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• 2016

This study is to analyze korea credit card market and the China credit card market, and predict future economic activity by developing the Algorithm for future economic trend Estimation As a results, there is no significant correlation between personal income growth and the credit card usage amount, and significant correlation between the credit card per capita and the credit card usage amount, in korea. there is significant correlation between personal income growth and the credit card usage amount, and between the credit card per capita and the credit card usage amount in china. it could be predicted that the china credit card market would be increased and the rate of increase would be gradually increased over the next five years, under the condition without constraints in the external environment.

• Korean Management Science Review
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• v.20 no.2
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• pp.165-177
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• 2003

This paper presents the prototype of corporate credit rating system using analytic hierarchy process (AHP). Prior studios have proposed various models of credit rating system, but most studies considered only financial information. Financial information, however, is only a small part of corporate information. In this study, the proposed credit rating system integrates both financial and non-financial information. Fifteen corporations are tested for the usefulness of the proposed system.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.35-54
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• 2009

The recent economic crisis not only reduces the profit of department stores but also incurs the significance losses caused by the increasing late-payment rate of credit cards. Under this pressure, the scope of credit prediction needs to be broadened from the simple prediction of whether this customer has a good credit or not to the accurate prediction of how much profit can be gained from this customer. This study classifies the delinquent customers of credit card in a Korean department store into homogeneous clusters. Using this information, this study analyzes the repayment patterns for each cluster and develops the credit prediction system to manage the delinquent customers. The model presented by this study uses Kohonen network, which is one of artificial neural networks of data mining technique, to cluster the credit delinquent customers into clusters. Cox proportional hazard model is also used, which is one of survival analysis used in medical statistics, to analyze the repayment patterns of the delinquent customers in each cluster. The presented model estimates the repayment period of delinquent customers for each cluster and introduces the influencing variables on the repayment pattern prediction. Although there are some differences among clusters, the variables about the purchasing frequency in a month and the average number of installment repayment are the most predictive variables for the repayment pattern. The accuracy of the presented system leaches 97.5%.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.5
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• pp.1209-1219
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• 2016

In knowledge based society, lifelong learning is increasing in order to meet educational needs of adult learners. Credit Bank system which is credited by individual experience, learning and qualifications are also emphasized for continuing learning participation. However, in spite of the importance of concern in the Credit Bank System, adult learners expectation and value are not high. The purpose of this study is to analyze participation valence and learning flow of adult learner in the Credit Bank System. The result of this study is summarized as follows: first, adult learners participated in the Credit Bank System to get new knowledge and skill based on internal and external motivation and requirement not involved with individual degree. Second, adult learners participating in the Credit Bank System are experiencing learning flow realizing that behavior of participation is compensated, adult learners are concentrating and feeling with satisfaction and pleasure to study. Third, participation in the Credit Bank System based on adult learner's own right learning requirement have been analyzed as it has a positive effect to the learning flow and have indicated that adult learners having high level of valence experience, recognition immersion, behavioral devotion, and egoistic immersion. Based on the conclusion, further studies are suggested.

• Journal of Information Technology Applications and Management
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• v.15 no.4
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• pp.21-36
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• 2008

As the great disturbance from abusing credit cards in Korea becomes stabilized, credit card companies need to interpret credit-card delinquents classification models from the viewpoint of profit. However, hit ratio which has been used as a measure of goodness of classification models just tells us how much correctly they classified rather than how much profits can be obtained as a result of using classification models. In this research, we tried to develop a new utility-based measure from the viewpoint of profit and then used this new measure to analyze two classification models(Neural Networks and Decision Tree models). We found that the hit ratio of neural model is higher than that of decision tree model, but the utility value of decision tree model is higher than that of neural model. This experiment shows the importance of utility based measure for credit-card delinquents classification models. We expect this new measure will contribute to increasing profits of credit card companies.

• Journal of the Semiconductor & Display Technology
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• v.13 no.1
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• pp.57-62
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• 2014

This paper proposes a new optical recognition method of credit card numbers. Firstly, the proposed method segments numbers from the input image of a credit card. It uses the significant differences of standard deviations between the foreground numbers and the background. Secondly, the method extracts gradient features from the segmented numbers. The gradient features are defined as four directions of grayscale pixels for 16 regions of an input number. Finally, it utilizes an artificial neural network classifier that uses an error back-propagation algorithm. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using real credit card images. The results show that the proposed algorithm is quite successful for most credit cards. However, the method fails in some credit cards with strong background patterns.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.789-800
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• 2008

Current credit evaluation models based on financial data make use of smoothing estimated default ratios which are transformed from each financial variable. In this work, some problems of the credit evaluation models developed by financial experts are discussed and we propose improved credit evaluation models based on the stepwise variable selection method and Box-Cox transformed data whose distribution is much skewed to the right. After comparing goodness-of-fit tests of these models, the validation of the credit evaluation models using statistical methods such as the stepwise variable selection method and Box-Cox transformation function is explained.