• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.851-868
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• 2012

After the financial crisis in 2008, the financial market still seems to be unstable with expanding the insolvency of the financial companies' real estate project financing loan in the aftermath of the lasted real estate recession. Especially after the illegal actions of people's financial institutions disclosed, while increased the anxiety of economic subjects about financial markets and weighted in the confusion of financial markets, the potential risk for the overall national economy is increasing. Thus as economic recession prolongs, the people's financial institutions having a weak profit structure and financing ability commit illegal acts in a variety of ways in order to conceal insolvent assets. Especially it is hard to find the loans of shareholder and the same borrower sharing credit risk in advance because most of them usually use a third-party's name bank account. Therefore, in order to effectively detect the fraud under other's name, it is necessary to analyze by clustering the borrowers high-related to a particular borrower through an analysis of association between the whole borrowers. In this paper, we introduce Analysis Techniques for detecting financial loan frauds in advance through an analysis of association between the whole borrowers by extending SNA(social network analysis) which is being studied by focused on sociology recently to the forensic accounting field of the financial frauds. Also this technique introduced in this pager will be very useful to regulatory authorities or law enforcement agencies at the field inspection or investigation.

• Journal of the Korean Professional Engineers Association
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• v.13 no.4
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• pp.31-47
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• 1980

Since medium and small manufacturing enterprises have , played a very important role not only in national economy but also in political and social relationships all of the countries in the world have paid favorable policies and programmes for protecting and promoting this sector. In Korea main ingredients of promoting policy for this sector consist of (1) encouragement to modernize facilities and rationalize operation (2) special priority in bank loan (3) promotion of industrial cooperatives (4) prevention of infringement by large industries. However, substantial investigation for problems incurred in medium industries has revealed that unless medium industries improve and raise their technological and managerial skillfulness for themselves all other measures are useless to solve the problems. This realization has induced all of the countries to render extension services on both of technology and management to assist and support their own effort for rationalization. Also in Korea during past 20 years many technical and managerial research institutes have rendered free consultancy services to medium industries by the support of government subsidy. Among them the joint extension services project performed by the Medium Industry Bank and UNDP during 1967 and 1975 might he listed as model case because of its broad and integrated activities and participation of foreign experts. We think many precepts should be :learned from the study of this project. Korean economy is expected to develop rapidly throughout coming'80 in spite of many obstacles, tut there is an apprehension that gap in of every facet between medium and large enterprises might he deepened and enlarged. To prevent the actualization of so-called dual structure of national economy and to promote stabilized medium industries with high added value productivity which are shown in well developed countries, consultancy assistance ana extension services should be strengthened much more than ever. Fortunately in 1978 legislation of "Medium and small industry promotion act" has paved the way for the systematic achivement of consultancy and extension services which shall be integrated by the government overall program. Under new framework thoughtfull accomplishment should be undertaken considering precious precepts obtained from past experience and failure. Special attention should be given to the technical liaison officer scheme, exclusive participation of only professional institutes, strict qualification and training for consultants for the future succsseful implementation.

• Journal of Arbitration Studies
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• v.26 no.1
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• pp.89-105
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• 2016

2008 began with the American financial crisis which gave way to the liquidity crisis (Fannie Mae and Freddie Mac) situation in which 'the withdrawal of investment initiated from the insufficiency of the U.S. subprime mortgage loan companies', 'the large size loss situation of the financial company (Bear Stearns) due to the American structured bond insufficiency' and the second half opening part national debt mortgage company. Within the American financial crisis was propagated the crisis of international derivatives. Due to this, the withdrawal of foreign investment progressed in the interior of a country with the considerable. By the end of 2007, the exchange rate fluctuation was absorbed in the domestic financial circle on the belief the potentiality of the domestic financial market had been growing drastically through the expansion of the foreign currency debt according to this and it came to the defence but while the exchange rate jumped up to the dollar shortage according to the international crisis, the small and medium companies making the banks and exchange rate-related derivatives contract were going bankrupt due to the derivatives loss. The small and medium factories establish the bank exchange rate-related derivatives has nose (KIKO), pivot (PIVOT), and snowball (Snowball) etc. at that time and the damage which it is the KIKO grasped at 6 end of the months in 2008 caused by reaches to 1 thousand billion 4 thousand hundred million dollars. Small and medium companies in which the dollar which it has to denounce among small and medium companies bearing the KIKO contract in fact with the Knock-In generation city bank exceeds the amount of sales were known to be 68 enterprises among 480 enterprises. This paper departs in this awareness of a problem and tries to look into the risk factor of the derivatives, including nose and study the essential ring risk management plan of small and medium manufacturer.

• International Area Studies Review
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• v.12 no.2
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• pp.27-53
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• 2008

This paper investigates factors determining the level of nontraditional activities at banks around the world. Specifically, the paper examines what kinds of firm-specific and country-specific characteristics determine the level of noninterest income using a comprehensive multi-country database. This paper focuses beyond the traditional U.S. based analyses and provides detailed asset-liability management practices of banks around the world.The findings suggest that banks' size and loan loss provision, explicit deposit insurance, banking restriction, banking freedom ranking of respective countries, the extent of state and foreign ownership, governance, and transparency of the country have positive effects on the level of nontraditional activities. Greater dependence on traditional lending and financing, market based economy, and multiple bank supervisory bodies in the country have negative associations with noninterest income. The economic development of country however affects the extent of the relationship.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.469-476
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• 2022

As the 3D modeling technology and conversational algorithm is developed, digital humans are being used in various fields, and also virtual bankers have begun to appear in banks, including major banks such as Shin-Han Bank and Nong-Hyup Bank. However, most of the research of digital human mainly focus on its appearance, and research on robot persona that should be considered in anthropomorphizing a robot is insufficient. In this study, an experiment was conducted to find out the user experience of three scenarios (student ID receipt, deposit and withdrawal account opening, leasehold loan consultation) in which the level of anthropomorphism of the speech strategy and the level of personal information use differed in the specific context of banking. As a result of the study, social presence and usefulness had an interactive effect on the scenario and the level of anthropomorphism. There was no interaction effect on intimacy, trustworthiness, and perceived intelligence, but a tendency could be confirmed.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.241-249
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• 2020

This study aims to empirically examine the effect of foreign direct investment (FDI) and corruption on the development of public-service sectors in 10 ASEAN countries. It then investigates whether this relationship is different between two FDI compositions including greenfield FDI and FDI in the form of cross-border merger and acquisitions (M&As). Using a panel database of 10 ASEAN countries during the period 1996-2015 from various sources including the World Development Indicators of the World Bank and UNCTAD, we first find that FDI strongly and positively contributes to the development of the public-service sectors in the recipient nations, except for the electricity sector. However, we show that this relationship is dependent on the type of FDI modes of entry. Specifically, while greenfield investment exerts a beneficial influence on the development of telecommunication and transportation sectors, cross-border M&A has no effect on these sectors, perhaps because of the distinct differences among three public service sectors. Finally, we found that in a highly corrupt environment, aggregate FDI might have no influence on all three public-service sectors, possibly because the two contradictory influences of the interaction terms between corruption and two FDI sub-types seem to cancel each other out.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.509-515
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• 2005

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved it more powerful than traditional artificial neural networks (ANNs)(Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al, 2005; Kim, 2003). The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is cost-sensitive. Therefore, it is necessary to convert the output of the classifier into well-calibrated posterior probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create probabilities (Platt, 1999; Drish, 2001). This study applies a method to estimate the probability of outputs of SVM to bankruptcy prediction and then suggests credit scoring methods using the estimated probability for bank's loan decision making.

• 사회경제평론
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• no.38
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• pp.199-240
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• 2012

According to the Post Keynesian endogenous money theory, money is created by the bank deposit which is dependent on the banks' supply of loan. And the demand for loans is dependent on investment by firms. In the money creating process, real value(or investment) and money are connected with banks' credit. In this paper, we investigated Keynes and Post Keynesian endogenous money theory with critical reviews of Hwang (2005). We came to three conclusions. First, Post Keynesian endogenous money theory is based on Keynes' theory. Second, Keynes' endogeneity of money is essentially different from that of Wicksellian. Third, focusing on the differences of the starting point of the arguments not on the conclusions, two Post Keynesian views, namely horizontalists and structuralists are compatible with liquidity preference theory in the Keynes' system.

• The Journal of Industrial Distribution & Business
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• v.13 no.10
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• pp.1-8
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• 2022

Purpose: Support vector machines (SVMs) ensemble has been proposed to improve classification performance of Credit risk recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. To deal with this problem, this paper designs a support vector machines (SVMs) ensemble method based on fuzzy integral, which aggregates the outputs of separate component SVMs with importance of each component SVM. Research design, data, and methodology: This paper designs a personal credit risk evaluation index system including 16 indicators and discusses a support vector machines (SVMs) ensemble method based on fuzzy integral for designing a credit risk assessment system to discriminate good creditors from bad ones. This paper randomly selects 1500 sample data of personal loan customers of a commercial bank in China 2015-2020 for simulation experiments. Results: By comparing the experimental result SVMs ensemble with the single SVM, the neural network ensemble, the proposed method outperforms the single SVM, and neural network ensemble in terms of classification accuracy. Conclusions: The results show that the method proposed in this paper has higher classification accuracy than other classification methods, which confirms the feasibility and effectiveness of this method.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.8
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• pp.89-97
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• 2022

The e-commerce market faces significant credit risks due to the complexity of the industry and information asymmetries. Therefore, credit risk has started to stymie the growth of e-commerce. However, there is no reliable system for evaluating the creditworthiness of e-commerce companies. Therefore, this paper constructs a credit risk evaluation index system that comprehensively considers the online and offline behavior of online retail enterprises, including 15 indicators that reflect online credit risk and 15 indicators that reflect offline credit risk. This paper establishes an integration method based on a fuzzy integral support vector machine, which takes the factor analysis results of the credit risk evaluation index system of online retail enterprises as the input and the credit risk evaluation results of online retail enterprises as the output. The classification results of each sub-classifier and the importance of each sub-classifier decision to the final decision have been taken into account in this method. Select the sample data of 1500 online retail loan customers from a bank to test the model. The empirical results demonstrate that the proposed method outperforms a single SVM and traditional SVMs aggregation technique via majority voting in terms of classification accuracy, which provides a basis for banks to establish a reliable evaluation system.