• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.1046-1058
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• 1997

WWW has taken root in Internet as a means of future shopping.But paymetn systems using tpdays show us several security vnlnerabilities.The problem that plain shpter's credit card details are transferred in Internet is included.Thnese risks can break out not only an infringement of pribate information but also economic crime.To solve these risks,we introduce the techique which implrment the encrypted WWW communication using PGP.And we propose SCCP which is new electronic payment protocol.As a result of testing with criteria from IBM,we can find that SCCP is safe and secure electronic payment protocol.As a result of testing with criteria from IBM,we can find that SCCP is safe and secure elctronic payment protocol.

• KDI Journal of Economic Policy
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• v.32 no.1
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• pp.1-26
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• 2010

Securitization was meant to disperse credit risk to those who were better able to bear it. In practice, securitization appears to have concentrated the risks in the financial intermediary sector itself. This paper outlines an accounting framework for the financial system for assessing the impact of securitization on financial stability. If securitization leads to the lengthening of intermediation chains, then risks become concentrated in the intermediary sector with damaging consequences for financial stability. Covered bonds are one form of securitization that do not fall foul of this principle. I discuss the role of countercyclial capital requirements and the Spanish-style statistical provisioning in mitigating the harmful effects of lengthening intermediation chains. For Korea, the stability of funding emerges as a key consideration. Covered bonds may play a role in stabilizing the funding arrangement for banks.

• The Korean Journal of Financial Management
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• v.23 no.2
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• pp.209-237
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• 2006

Since previous default forecasting models for the firms evaluate the probability of default based upon the accounting data from book values, they cannot reflect the changes in markets sensitively and they seem to lack theoretical background. The market-information based models, however, not only make use of market data for the default prediction, but also have strong theoretical background like Black-Scholes (1973) option theory. So, many firms recently use such market based model as KMV to forecast their default probabilities and to manage their credit risks. Korean firms also widely use the KMV model in which default point is defined by liquid debt plus 50% of fixed debt. Since the debt structures between Korean and American firms are significantly different, Korean firms should carefully use KMV model. In this study, we empirically investigate the importance of debt structure. In particular, we find the following facts: First, in Korea, fixed debts are more important than liquid debts in accurate prediction of default. Second, the percentage of fixed debt must be less than 20% when default point is calculated for Korean firms, which is different from the KMV. These facts give Korean firms some valuable implication about default forecasting and management of credit risk.

• International Commerce and Information Review
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• v.14 no.4
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• pp.433-456
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• 2012

The confirming bank undertakes to make payment to the beneficiary, provided that a complying presentation is made and complies with its confirmation. In case L/C fraud is evident, though, the confirming bank as well as the issuing bank does not have the obligation to make payment. That is, the confirming bank does not take the risks involving documentary fraud. The confirming bank cannot exercise the right to recourse toward the beneficiary or the nominated bank when the issuing bank finds the discrepancies which the confirming bank has not noticed. This is because under UCP600, the issuing bank or the confirming bank cannot refuse to make payment with the cause of documentary discrepancy after 5 banking days following the presentation of documents. Even if the issuing bank accepts the discrepant documents following the confirming bank's request to do so, the confirming bank does not have the responsibility for the confirmation. When under Usance Negotiation Credit, the confirming bank acts as the nominated bank, the confirming bank should make payment in no time if the beneficiary presents complying documents. Therefore, unless the confirming bank intends to make immediate payment, they should consider using Deferred Payment or Acceptance L/C in Usance Credit. It is also safer for the beneficiary to have the reimbursing bank's undertaking to the reimbursement than just have confirmation of the credit because in the latter case they may not have full payment due to disputes regarding discrepancies of the documents even if they have confirmation of the credit.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.4
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• pp.442-451
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• 1998

The purpose of this study was to investigate the current brand of mail-order clothing, consumers' attitude over importance of brand and the effectiveness of brand when consumers purchase clothing by mail-order shopping. for this study, mail order catalogs were analyzed and the samples were collected through the questionaire distributed to 214 women. It was analyzed by SAS package. The results are as follows; 1. As a result of mail-order catalog analysis, domestic clothing included few famous brand except foreign brand. 2. The users of mail-order purchasing were old and married women comparably. They were also high clothing-expense users and housekeepers. Item that consumers wanted to buy using mail-order shopping were home-wear, night-wear, accessories and scarves which were involved low risks comparably. 3. Consumers regard brand significantly as a means of credit in purchasing mail-order shopping clothing. In analysis between importance of mail-order clothing brand and demographics, degree of education and clothing expense per month showed significant difference.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.29
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• pp.143-172
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• 2006

This study focuses on the risk management of "Digital Goods" appeared with the progress of information technology(IT) in international transaction. As a result of that digital goods have a lot of uncertainty between the general goods or service which have been deal with object of international transaction broadly because digital goods hold uniqueness. In this study, the author give a definition of "Digital Goods" and make an examination of uniqueness of that in international transaction. Next, six risks are defined base on risk theory and risk analysis matrix applying risk mapping model is made. Conclusionally, risk transfer as insurance is adequate to manage business risk, security risk, credit risk and legal risk. Meanwhile, risk avoidance is adequate to manage reputation risk and market risk. But, this study have following three limits. Firstly, concerning definition of the risk, real case is not applied owing to lack of transaction data. Secondly, measuring of the risk is not based on absolute data but relative data. Lastly, suggesting way of risk management is not concrete and practical to international trader of digital goods.

• Korea Trade Review
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• v.44 no.1
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• pp.129-142
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• 2019

This paper draws implications on the ship finance of the Korean ECAs for shipbuilding industry from the perspective of WTO ASCM through studying the trade disputes on export credits. In consideration of the underwriting practice on the case-by-case basis, the ECAs' law regimes and their ship finance programs as such would be judged not conferring a benefit. The ship finance of international commercial banks could be treated as a market benchmark for the purpose of determining the existence of benefit in the ECA ship finance. The ECAs share securities with international commercial banks for the same exposure to the risks in a syndicate. Therefore, WTO DSB would rule that the ECA ship finance confers no benefit for individual transactions. The items (j) and (k-1) of ASCM Annex I are not allowed to interpret a contrario.

• 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.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.1-23
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• 2019

Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.43
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• pp.169-198
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• 2009

This paper sees some legal phases of the forfaiting transactions performed by using bills of exchange (drafts) or promissory notes. It focuses on the issues of the endorsement without recourse and the aval under the Korean statute for such negotiable instruments which is enacted by succeeding to the Convention Providing a Uniform Law For Bills of Exchange and Promissory Notes (Geneva, 1930) of the League of Nations. This paper purposes to give basic legal guides for forfaiting participants in order for them to be able to prevent and solve some problems caused by lack of understanding for relevant rules of law. Forfaiting is a useful technic as it provides financing for international export businesses by enabling forfaiters to discount future payment obligations on non-recourse basis. It gives benefits to exporters by removing political, transfer and commercial risks of importers or their country. Also it protects exporters from the risks of the increase of interest rates and the fluctuation of exchange rate as well. In traditionally normal forfaiting transactions, exporter of goods generally takes promissory notes or accepted drafts from importers in payment for the price of goods. Further, when the exporter is not comfortable with the importer's credit or is not confident whether the importer will pay the accepted drafts or the promissory notes as they come due, the exporter nomally requires the importer to make the importer's bank (avalizer or guarantor) add an aval, which is made by the written expression of intention, the words of "per aval", and the guarantor's signature on the drafts or promissory notes. The exporter endorses without recourse to transfer the drafts or the promissory notes to the forfaiter, typically a bank, who purchases the drafts or the promissory notes without recourse.