• Journal of Korean Tunnelling and Underground Space Association
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• v.3 no.4
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• pp.35-55
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• 2001

Recently, as tunnel structures are getting older and decrepit, many tunnel inspections are carried out for evaluating the tunnel state and safety. But, because there is no exact standard for tunnel state and safety, depending on subjective decision, the new standard to assess the tunnel state is required. The existing standard including mainly the assessment of the state of tunnel lining is not considered the characteristics of tunnel as underground structures. Also, the item of assessment and process of grading and classifying the state of tunnel is not objective and systemetic. In this study, new standard for assessment of tunnel state is presented for improving the problems in evaluating the tunnel state and safety. In the new standard, the new items of assessment including geotechnical condition were selected and graded, the process in classifying the tunnel state is quantitative for objective assessment for tunnel state. This new standard and method is practically used in effective safety inspection and diagnosis and tunnel maintenance.

• Journal of Venture Innovation
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• v.2 no.2
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• pp.95-115
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• 2019

In the context of today's business environment, not only is the nation or company's credit rating considered very important in our recent society, but it is also becoming important in international transactions. Likewise, at this point of time when the importance and reliability of credit evaluation are becoming important at home and abroad, this study analyzes financial ratios related to corporate profitability, safety, activity, financial growth, and profit growth to study the impact of financial indicators on enterprise value and corporate taxes on credit evaluation. To proceed with this, the financial ratio of 465 companies of KOSPI securities listed in 2017 was calculated and the impact of enterprise value and corporate taxes on credit evaluation was analyzed. Especially, this further study tried to derive a reliable and consistent conclusion by analyzing the financial data of KOSPI securities listed companies for eight years from 2011, which is the first year of K-IFRS introduction, to 2018. Research has shown that the significance levels among variables that show the profitability, safety, activity, financial growth, and profit growth of each financial ratio were significant at the 99% level, except for the profit growth. Validation of the research hypothesis found that while the profitability of KOSPI-listed companies significantly affects corporate value and income tax, indicators such as safety ratio and growth ratio do not significantly affect corporate value and income tax. Activity ratio resulted in significant effects on the value of enterprise value but not significant impacts on income taxes. In addition, it was found that the enterprise value has a significant effect on the company's credit and corporate income taxes, and that corporate income taxes also have a significant effect on the corporate credit evaluation, and this also shows that there is a mediating function of corporate tax. And as a result of further study, when looking at the financial ratio for eight years from 2011 to 2018, it was found that two variables, KARA and LTAX, are significant at a 1% significant level to KISC, whereas LEVE variables is not significant to KISC. The limitation of this study is that credit rating score and financial score cannot be said to be reliable indicators that investors in the capital market can normally obtain, compared to ranking criteria for corporate bonds or corporate bills directly related to capital procurement costs of enterprise. Above all, it is necessary to develop credit rating score and financial score reflecting financial indicators such as business cash flow or net assets market value and non-financial indicators such as industry growth potential or production efficiency.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.423-440
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• 2007

Although various models have been developed to establish the enterprise credit scoring, no model has utilized the enterprise human resource so far. The purpose of this study was to build an enterprise credit scoring model using enterprise human resource factors. The data to measure the enterprise credit score were made by the first-year research material of HCCP was used to investigate the enterprise human resource and 2004 Credit Rating Score generated from KIS-Credit Scoring Model. The independent variables were chosen among questionnaires of HCCP based on Mclagan(1989)'s HR wheel model, and the credit score of Korean Information Service was used for the dependent variables. The statistical method used for data analysis was logistic regression. As a result of constructing a model, 22 variables were selected. To see these specifically by each large area, 6 variables in human resource development(HRD) area, 15 in human resource management(HRM) area, and 1 in the other area were chosen. As a consequence of 10 fold cross validation, misclassification rate and G-mean were 30.81 and 68.27 respectively. Decile having the highest response rate was bigger than the one having the lowest response rate by 6.08 times, and had a tendency to decrease. Therefore, the result of study showed that the proposed model was appropriate to measure enterprise credit score using enterprise human resource variables.

• 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.

• Information Systems Review
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• v.9 no.2
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• pp.129-147
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• 2007

At the time the local credit-card companies plunged into a liquidity crisis in 2002, S-Card was urged to take into account the estimated customer income (ECI) to enhance its customer credit evaluation function for the first time in Korean financial industry. Before this new attempt by S-Card, most credit-card companies including S-Card had performed a customer's credit evaluation based on the customer's behavioral factors such as the amount of purchase on credit, debt payment, and financial history that is provided from the Credit Bureau. However, this approach failed to measure customer's potential value which is one of the major factors in judging the customer's ability to pay, and hence, led to difficulties in risk management. The purpose of this case study is to present the better approach to sophisticated risk management for financial firms in Korea by reviewing S-Card's process of customer income estimation and its application to risk management.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.797-800
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• 2008

Online signature verification system is widely used in banking account, credit card and so on, because system for online signature verification is easy to implementation and inexpensive. Therefore there are a lot of study on online signature verification. However there is little research about online signature is safe or not. This paper shows a way of online signature estimation using various information of signature. This paper make a experiment about relation sorority grade of online signature and 2-D information of online signature like the number of strokes and cross points, density of points, standard deviation of direction, velocity and acceleration, lengths of signature and convex hull etc. Finally, this paper presents several features of safe online signature.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.12-16
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• 2009

본 연구에서는 중소기업진흥공단이 보증한 P-CBO pool에 편입된 중소기업들의 재무적 특성을 기준으로 중소기업의 재무적 특성과 기업가정신의 관련성을 분석하였다. 중소기업진흥공단의 혁신성 위주의 선정기준과 투기등급 업체의 위험감수성에 기반하여 중소기업진흥공단 P-CBO 편입 중소기업의 경우 재무적 특성과 기업가정신 관련성이 클 것으로 해석하였다. 또한 설문을 통한 기업가정신과 재무적 성과에 관한 기존연구를 바탕으로 P-CBO 편입 중소기업의 재무적 특성이 일반 중소기업의 재무적 특성과 차별적일 것이라고 예상하였다. 주요 재무적 변수를 중심으로 2000년~2005년까지 보증된 중소기업진흥공단 P-CBO 편입업체와 유사한 신용평가등급(투기등급) 수준을 보이는 일반중소기업의 재무적 특성을 비교하였다. 연구 결과 P-CBO 편입 중소기업과 일반중소기업간에는 재무적 특성을 기준으로 한 유의적인 차이를 발견하지 못했다. 다만 P-CBO 편입 일반중소기업의 설립 후 경과연수는 유의적인 차이를 보였다. 향후에는 설문 위주의 기업가정신과 재무적 성과에 대한 연구와 더불어 설문 결과 및 재무적 특성을 실증적으로 상호 비교하고 나아가 이를 바탕으로 한 시계열적인 연구가 필요하다.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.77-90
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• 2023

This study aims to investigate the potential of alternative credit assessment through Social Networking Sites (SNS) as a complementary tool to conventional loan review processes. It seeks to discern the impact of SNS usage characteristics and loan product attributes on credit loan repayment. To achieve this objective, we conducted a binomial logistic regression analysis examining the influence of SNS usage patterns, loan characteristics, and personal attributes on credit loan conditions, utilizing data from Company A's credit loan program, which integrates SNS data into its actual loan review processes. Our findings reveal several noteworthy insights. Firstly, with respect to profile photos that reflect users' personalities and individual characteristics, individuals who choose to upload photos directly connected to their personal lives, such as images of themselves, their private circles (e.g., family and friends), and photos depicting social activities like hobbies, which tend to be favored by individuals with extroverted tendencies, as well as character and humor-themed photos, which are typically favored by individuals with conscientious traits, demonstrate a higher propensity for diligently repaying credit loans. Conversely, the utilization of photos like landscapes or images concealing one's identity did not exhibit a statistically significant causal relationship with loan repayment. Furthermore, a positive correlation was observed between the extent of SNS usage and the likelihood of loan repayment. However, the level of SNS interaction did not exert a significant effect on the probability of loan repayment. This observation may be attributed to the passive nature of the interaction variable, which primarily involves expressing sympathy for other users' comments rather than generating original content. The study also unveiled the statistical significance of loan duration and the number of loans, representing key characteristics of loan portfolios, in influencing credit loan repayment. This underscores the importance of considering loan duration and the quantity of loans as crucial determinants in the design of microcredit products. Among the personal characteristic variables examined, only gender emerged as a significant factor. This implies that the loan program scrutinized in this analysis does not exhibit substantial discrimination based on age and credit scores, as its customer base predominantly consists of individuals in their twenties and thirties with low credit scores, who encounter challenges in securing loans from traditional financial institutions. This research stands out from prior studies by empirically exploring the relationship between SNS usage and credit loan repayment while incorporating variables not typically addressed in existing credit rating research, such as profile pictures. It underscores the significance of harnessing subjective, unstructured information from SNS for loan screening, offering the potential to mitigate the financial disadvantages faced by borrowers with low credit scores or those ensnared in short-term liquidity constraints due to limited credit history a group often referred to as "thin filers." By utilizing such information, these individuals can potentially reduce their credit costs, whereas they are supposed to accrue a more substantial financial history through credit transactions under conventional credit assessment system.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.573-584
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• 2007

A well estimated probability of default is most important for constructing a good credit scoring process. The maximum expected utility (MEU) model has been suggested as an alternative of the traditional logistic regression model. Because the MEU model has been constructed using financial data arising from North America and European countries, the MEU model may not be suitable to Korean private firms. Thus, we propose a Korea-specific MEU model by estimating the parameters involved in kernel functions. This Korea-specific MEU model is illustrated using 34,057 private firms to show the performance of the MEU model relative to the usual logistic regression model.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.39-42
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• 2010

최근 보행자가 교량의 진동에 의한 불안감을 느끼는 경우가 발생되면서 설계 단계에서 진동에 대한 고려하고 있다. 그러나 설계자는 범용유한요소프로그램에 이동하중을 적용하여 동적응답해석을 하는 것에 어려움을 느끼고 있으며 그 결과 Meister감각곡선에 의한 진동사용성 평가도 정확히 수행되지 않고 있다. 본 연구에서는 설계자들이 수행하는 교량의 진동사용성 평가방법의 간편한 적용을 위하여 이동하중모델 생성툴을 연구하였으며, 범용유한요소프로그램으로 모델링 된 교량의 매개변수를 변화해가며 진동사용성 평가를 수행하였고 연구 결과 중 매개변수의 하나인 보요소의 길이에 따른 진동사용성 평가결과만을 작성하였다. 평가결과 보요소의 길이에 따라 교량에 발생되는 진동과 가속도의 응답치가 다르게 나타났으며, 발생되는 주요주파수 범위도 다르게 해석되었다. 이러한 동적응답의 결과가 다르게 해석되면서 Meister 감각곡선에 의한 평가등급이 차이도 발생되었다. 따라서 정확한 진동사용성 평가를 위해서는 동적응답해석 시 다양한 매개변수에 의한 동적응답의 결과에 대한 연구는 물론 다양한 교량 형식과 그에 맞는 모델링에 대한 많은 연구가 필요할 것으로 사료된다.