• Korean Management Science Review
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• v.33 no.3
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• pp.105-117
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• 2016

In this paper, we present empirical testing result to examine the validity of inbound supply and outbound demand risk factors in the sense of early predicting the firm's bankruptcy risk level. The risk factors are drawn from industry uncertainty attributes categorized as uncertainties of input market (inbound supply), and product market (outbound demand). On the basis of input-output table, industry level inbound and outbound sectors are identified to formalize supply chain structures, relevant inbound and outbound uncertainty attributes and corresponding risk factors. Subsequently, publicly available macro-economic indicators are used to appropriately quantify these risk factors. Total 68 industry level bankruptcy risk forecasting results are presented with the average R-square scores of between 53.4% and 37.1% with varying time lag. The findings offers useful insights to incorporate supply chain risk to the body of firm's bankruptcy risk level prediction literature.

• 해운
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• s.84
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• pp.10-16
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• 2011

2002년 이후 지속되어온 미국의 재정적자가 금융위기 중 확대되면서 미국 국가채무가 2012년에는 GDP를 초과할 것으로 전망된다. 미 의회는 5개월 이상 협상을 지속한 결과 2011년 8월 1일 국가채무 한도 상향조정을 포함한 예산통제법을 통과시켜 국가부도사태는 발발하지 않았다. 이러한 미 의회의 국가채무 한도 상향 조정에도 불구하고, S&P는 지난 8월 3일 미국의 국가신용등급을 AAA에서 AA+로 강등하였으며, 주식시장의 경우도 미국의 재정지출 감축으로 인한 경기회복지연, 신용등급 강등 영향으로 인한 국제금융시장의 위험자산 회피현상으로 급락하였다. 미국 재정지출 감축과 위험자산 회피현상에 따른 우리나라의 국내총생산 감소는 미미할 것으로 분석되지만, 재정긴축 계획으로 향후 5년 동안 미국 경제에 평균 -0.5%정도의 GDP 감소 효과가 있으며, 우리나라 GDP도 평균적으로 -0.02% 정도 감소시킬 것이다. 이에 따라 우리나라 기업들도 미국 재정긴축 및 신용등급 강등으로 인하여 발생할 수 있는 사항들을 다각적으로 분석하여 대처를 할 필요성이 제기되고 있다. 다음은 대외경제정책연구원에서 발표한 "미국 재정긴축 및 신용등급 강등의 효과분석"의 주요 내용을 정리 요약한 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.737-741
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• 2004

본 연구에서는 지리정보시스템을 이용한 홍수범람에 대한 변화, 홍수범람면적, 홍수범람 위험지역을 산정하기 위해 HEC-GeoRAS 와 HEC-RAS 및 GIS Tool인 ArcView를 이용하여 경안천 유역에 이를 적용하였다. 1:5000 DEM과 경안천 수계 하천정비 기본계획상의 부도를 바탕으로 HEC-GeoRAS를 이용하여 HEC-RAS로 입력하기 위한 기하학적인 자료를 추출하였으며, 추출된 단면을 보정하기 위해 경안천 수계 하천정비기본계획상의 하천단면자료을 이용하였다. 그리고 20년, 30년, 50년, 80년, 100년 빈도별 홍수량자료를 사용하여 경안천 유역의 홍수범람을 모의하였다. 그 결과 빈도별 홍수량에 따른 홍수범람면적과 범람위험지역을 파악할 수 있었다.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.525-535
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• 2018

If the frequency of a particular class is excessively higher than the frequency of other classes in the classification problem, data imbalance problems occur, which make machine learning distorted. Corporate bankruptcy prediction often suffers from data imbalance problems since the ratio of insolvent companies is generally very low, whereas the ratio of solvent companies is very high. To mitigate these problems, it is required to apply a proper sampling technique. Until now, oversampling techniques which adjust the class distribution of a data set by sampling minor class with replacement have popularly been used. However, they are a risk of overfitting. Under this background, this study proposes ROSE(Random Over Sampling Examples) technique which is proposed by Menardi and Torelli in 2014 for the effective corporate bankruptcy prediction. The ROSE technique creates new learning samples by synthesizing the samples for learning, so it leads to better prediction accuracy of the classifiers while avoiding the risk of overfitting. Specifically, our study proposes to combine the ROSE method with SVM(support vector machine), which is known as the best binary classifier. We applied the proposed method to a real-world bankruptcy prediction case of a Korean major bank, and compared its performance with other sampling techniques. Experimental results showed that ROSE contributed to the improvement of the prediction accuracy of SVM in bankruptcy prediction compared to other techniques, with statistical significance. These results shed a light on the fact that ROSE can be a good alternative for resolving data imbalance problems of the prediction problems in social science area other than bankruptcy prediction.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.25-41
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• 2011

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 them 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 so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.

• Korean small business review
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• v.43 no.3
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• pp.1-20
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• 2021

The survival period according to technological capability was analyzed for about 22,500 innovative SMEs in the service industry. The survival period was defined as the occurrence of overdue and default, and the technological capability was divided into two clusters. As a result of estimating the survival period according to technological capability through Kaplan-Meier analysis, it was confirmed that the estimated survival period of T1-T4 grade service innovative SMEs was significantly greater in both overdue and default. As a result of the analysis of the Cox proportional hazard model applying the control variable, it was confirmed that the higher technological capability, the lower the risk in the group of start-up companies. However, in the group of non-start-up companies the technological capability did not significantly affect the survival period, and the influence of the variables related to the size of the company was found to increase. Therefore, the technological capability is meaningful as additional information that has a significant effect on the survival period of innovative SMEs in the start-up companies group of service industry. In addition, it was concluded that it is necessary to reflect the technological capability when establishing the SME support and promotion policy of the start-up companies group in the service industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.1 no.1
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• pp.91-100
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• 2000

In 1997 the recession of Korean economy brought about the bankruptcy of large corporations and the large size of non-Performing financial assets which led to IMF financial crisis. One of the major reasons for IMF financial crisis was poor loan management of domestic financial institutions . During the restructuring process of financial institutions since the IMF financial crisis, the importance of the loan management has been recognized. Especially. financial institutions' credit allocation had been concentrated on a few big conglomerates and their subsidies as well as some specific business areas. Hence, risk-diversifying portfolio effects were not reflected in any loan portfolios. The IMF financial crisis in 1997 has clearly showed that credit-risk management is essential not only for individuals' loan but also for portfolios consisting of various loans The main objective of this paper is to provide some suggestions on the direction for financial institutions in Korea to improve their loan portfolio management. Particularly, for the effective management of loan portfolios, this paper introduces quantitative credit-risk management schemes such as KMV models and CreditMetrics which are commonly used in financial institutions in advanced countries. Financial institutions in Korea should make their best efforts to establish a more scientific as well as quantitative loan portfolio management.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.371-371
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• 2022

하천관리지리정보시스템(RIMGIS)은 하천정보의 표준화 및 전산화를 통한 정보제공과 하천에 관련한 업무를 지원하기 위해 개발된 시스템으로 5개의 지방국토관리청에서 관리하고 있는 하천대장 및 부도, 구조물도 등의 다양한 하천 관련 정보를 정보화하여 인허가 및 하천기본계획 등의 하천업무를 신속하고 효율적으로 수행할 수 있도록 운영되고 있다. 국가 주요 기반시설을 생애주기 관점에서 관리하고 소요재원의 확보근거를 마련하고자 "지속 가능한 기반시설 관리 기본법"이 제정되었고 최근에 시행되었다. 이에 따라 국토안전관리원에서는 도로·철도·철도 하천 등과 같은 사회기반시설(15종)의 노후화에 대비하여 전략적인 투자와 관리방식 도입을 목적으로 인프라 총조사 사업을 진하천 등과 같은 사회기반시설(15종)의 노후화에 대비하여 전략적인 투자와 관리방식 도입을 목적으로 인프라 총조사 사업을 진행하고 관리를 위해서 기반터 시스템을 도입하였다. 하천관리지리정보시스템과 기반터 시스템은 하천 기반시설의 정보가 데이터베이스에서 다뤄진다는 점에서 유사하지만, 기반터 시스템은 하천관리지리정보시스템과 달리 유지관리 측면에 대한 필요한 보수 주기, 필요 예산 등과 같은 정보를 산정할 수 있도록 프레임워크가 구성되어 있다. 그러나 하천과 기반시설의 코드를 연결하는 작업들은 현재 상황에서는 미흡한 실정이고, 유지관리와 시설물의 노후화를 가속화하는 홍수와 침수피해 등을 전체적으로 고려할 수 있는 방안에 대한 연구도 미진한 상황이다. 이에 본 연구에서는 하천 기반시설의 유지관리를 위해 하천, 제방, 인명에 대한 위험지수를 고려한 잠재 인명피해 위험도와 잠재 홍수피해 위험도를 평가기준으로 설정하고 적용하였다. 또한 이를 포함시킨 투자우선순위 평가기법을 도입하여 감가상각과 위험요소 등을 고려할 수 있는 데이터베이스 구성 방안을 제시하고자 한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.14-27
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• 2020

Pedestrian deaths account for a high percentage of deaths in traffic accidents in Korea, raising interest in pedestrian safety policy. However, since the walk signal time is applied based on the length of the crosswalk without considering the walker and the signal cycle, the walk waiting time is relatively longer than the crosswalk, causing pedestrian jaywalking. In this study, due to an unreasonable signal time plan during a road crossing where a signal is installed, the pedestrian's walk signal was given twice a cycle of crossings, and the operational and safety effects of the signal system were quantitatively and qualitatively analyzed, and the operational effects of the signal interval and jaywalking rate were assessed by different signal intervals. The results showed that jaywalking and waiting time decreased, and the shorter the interval between the application of the walk signal time, the less jaywalking is analyzed. However, there is a risk of vehicle conflict due to pedestrian exposure, and measures for expanding safety for operation were proposed.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.473-483
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• 2014

Even though the ROC manifold for more than three dimensional space which is an extension of the ROC curve and surface has difficulty to represent graphically, the hypervolume under the ROC manifold (HUM) statistic can be defined and obtained based on AUC and VUS measures for the ROC curve and the ROC surface. Hence the definition and characteristics of the HUM for four dimensional space are studied in this work. By extension of the standard criterion of AUC for probabilities of default based on Basel II, the 13 classes of standard criterion of HUM are proposed in order to discriminate four classification models and some application methods are discussed. In order to explore the standard criterion of HUM whose values are obtained from various distributions, ternary plot is used and explained.