• Korean Journal of Human Ecology
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• v.7 no.4
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• pp.71-81
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• 2004

This study was to understand the credit economic society and the frequency of credit use, and to suggest the method of home management in credit economic society. First of all, the consumer education of credit will have to convenience the utilization of consumer education, to supply the information of credit value and a contract thinking, and to develop the variety of media and tools in consumer education.

• 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.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.1-8
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• 2018

This study analyzed annual final sample data from 159 companies based on firms selected as economic justice companies by Economic Justice Institute in Citizens' Coalition for Economic Justice in South Korea according to interest variables from 2005 until 2011. Analyzed results are as follows. First, higher scores in soundness and corporate social activities among CSR items suggested that corporate credit rating upgraded. This indicates that credit rating institutions give a good evaluation on their social activities and reflect them in credit rating assessment. However, environmental protection satisfaction and corporate credit rating showed the opposite results. Second, high objectivity and contribution to the economic development as well as supervision by giant auditors had substantial effects on higher corporate credit rating. In contrast, high soundness and supervision by giant auditors reduced corporate credit rating. Based on this outcome, it is estimated that there is a discriminatory response among CSR activities in terms of credit rating evaluation conducted by credit rating institution.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.147-156
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• 2012

Most people in our society use credit card instead of cash or check, so credit card is very important economic method. Credit card supposed to be safe, but hackers hack credit card for illegal deal. Also hackers make fake credit card and issue fake credit card to other people. In this thesis it will study and analyze damage case for safe credit card deal. It will use safe credit card system to insert variety of information and data of using pattern in artificial intelligence network, so print out the possibility of risk and monitor the risk of credit card user's deal pattern, so if one of user's pattern is different than normal pattern, it will pop up message in consultant's screen. This thesis will study and suggest way of prevent from illegal deal and user friendly credit card checking system.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.128-132
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• 2001

In this paper, we evaluate and contrast four neural network rule extraction approaches for credit scoring. Experiments are carried our on three real life credit scoring data sets. Both the continuous and the discretised versions of all data sets are analysed The rule extraction algorithms, Neurolonear, Neurorule. Trepan and Nefclass, have different characteristics, with respect to their perception of the neural network and their way of representing the generated rules or knowledge. It is shown that Neurolinear, Neurorule and Trepan are able to extract very concise rule sets or trees with a high predictive accuracy when compared to classical decision tree(rule) induction algorithms like C4.5(rules). Especially Neurorule extracted easy to understand and powerful propositional if -then rules for all discretised data sets. Hence, the Neurorule algorithm may offer a viable alternative for rule generation and knowledge discovery in the domain of credit scoring.

• 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.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.164-169
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• 2008

The increasing late-payment rate of credit card customers caused by a recent economic downturn are incurring not only reduced profit of department stores but also significant loss. Under this pressure, the objective of credit forecasting is extended from presumption of good or bad customers to contribution to revenue growth. As a method of managing defaults of department store credit card, this study classifies credit delinquents into some clusters, analyzes repaying patterns of customers in each cluster, and develops credit forecasting system to manage delinquents of department store credit card using data of Korean D department store's delinquents. The model presented by this study uses Kohonen network, a kind of artificial neural network of data mining techniques to cluster credit delinquents into groups. Logistic regression model is also used to predict repayment rate of customers of each cluster per period. The accuracy of presented system for the whole clusters is 92.3%.

• 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 the Economic Geographical Society of Korea
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• v.19 no.2
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• pp.265-285
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• 2016

This paper analyses the regional financial market of Kyungbuk-East Coast region. The result shows that the credit unions do not do much for easing the credit constraints of small firms in the region. Many papers suggest that it is necessary for them to adhere closely to the regional economy. But they do not do their best to collect borrowers' private informations. Instead they rely on the credit scoring system to assess their creditworthiness and require collaterals to reinforce their weak credits. That is the real root of weak competitiveness of credit unions. To overcome such a problem they need to actively participate in the development of the regional economy, bearing in mind the cooperative principles, especially commitment for the community. On the other hand the government should contrive plans to foster them. When they function actively the regional financial market will become efficient and the regional economy grow smoothly.

• Korean Security Journal
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• no.9
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• pp.27-68
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• 2005

Recently, because credit card crime using a personal credit information is increasing, professionalizing, and spreading the area, the loss occurring from credit card crime is enormous and is difficult to arrest and punish the criminals. At past, crime from forging and counterfeiting the credit card was originated by minority criminals, but at present, the types and appearance of credit card crime is very different to contrasting past crime. The numbers of people using credit card in the middle of 1990's was increasing and barometer of living conditions was evaluated by the number having credit card, therefore this bad phenomenon occurring from credit card crime was affected by abnormal consumption patterns. There is no need emphasizing the importance of personal credit card in this credit society. so, because credit card crime using personal credit card information has a bad effect, and brings the economic loss and harms to individuals, credit card company, and members joining credit card. Credit card crime using personal credit card information means the conduct using another people's credit card information(card number, expiring duration, secret number) that detected by unlawful means. And crime using dishonest means from another people's credit information is called a crime profiting money-making and a crime lending an illegal advance by making false documents. A findings on countermeasures of this study are as follows: Firstly, Diverting user's mind, improving the art of printing, and legitimating password from payment gateway was suggested. Secondly, Complementing input of password, disseminating the system of key-board protection, and promoting legitimations of immediate notification duty was suggested. Thirdly, Certificating the electronic certificates as a personal certificates, assuring the recognition by sense organ of organism, and lessening the ratio of crime occurrence, and restricting the ratio of the credit card crime was suggested.