• Journal of the Korea Safety Management & Science
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• v.10 no.2
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• pp.71-83
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• 2008

Most researches on the corporate credit rating are generally classified into the area of bankruptcy prediction and bond rating. The studies on bankruptcy prediction have focused on improving the performance in binary classification problem, since the criterion variable is categorical, bankrupt or non-bankrupt. The other studies on bond rating have predicted the credit ratings, which was already evaluated by bond rating experts. The financial institute, however, should perform effective loan evaluation and risk management by employing the corporate credit rating model, which is able to determine the credit of corporations. Therefore, in this study we present a medium sized corporate credit rating system by using Artificial Neural Network(ANN) and Analytical Hierarchy Process(AHP). Also, we developed AHP model for credit rating using non-financial information. For the purpose of completed credit rating model, we integrated the ANN and AHP model using both financial information and non-financial information. Finally, the credit ratings of each firm are assigned by the proposed method.

• The Journal of Information Systems
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• v.16 no.3
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• pp.1-20
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• 2007

Most researches on the corporate credit rating are generally classified into the area of bankruptcy prediction and bond rating. The studies on bankruptcy prediction have focused on improving the performance in binary classification problem, since the criterion variable is categorical, bankrupt or non-bankrupt. The other studies on bond rating have predicted the credit ratings, which was already evaluated by bond rating experts. The financial institute, however, should perform effective loan evaluation and risk management by employing the corporate credit rating model, which is able to determine the credit of corporations. Therefore, this study presents a corporate credit rating method using business failure probability map(BFPM) and AHP(Analytic Hierarchy Process). The BFPM enables us to rate the credit of corporations according to business failure probability and data distribution or frequency on each credit rating level. Also, we developed AHP model for credit rating using non-financial information. For the purpose of completed credit rating model, we integrated the BFPM and the AHP model using both financial and non-financial information. Finally, the credit ratings of each firm are assigned by our proposed method. This method will be helpful for the loan evaluators of financial institutes to decide more objective and effective credit ratings.

• Korean Management Science Review
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• v.20 no.2
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• pp.165-177
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• 2003

This paper presents the prototype of corporate credit rating system using analytic hierarchy process (AHP). Prior studios have proposed various models of credit rating system, but most studies considered only financial information. Financial information, however, is only a small part of corporate information. In this study, the proposed credit rating system integrates both financial and non-financial information. Fifteen corporations are tested for the usefulness of the proposed system.

• KDI Journal of Economic Policy
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• v.28 no.1
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• pp.1-47
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• 2006

Even after significant changes in the financial market due to the financial crisis the corporate debt markets have seen created turmoil caused such as by Daewoo, Hyundai, and credit card companies in the financial system. These lagging improvements of corporate debt markets are mainly due to inadequate market infrastructure. Specifically, the credit rating agencies have not been successful in providing proper and timely information on the loan repayment abilities of debtors. This study analyzes past performance of credit rating agencies in Korea and tries to develop policy implications to improve the role of credit rating agencies based on the recent discussions on credit rating agencies by academics and the SEC. In addition, this study focuses on unique operation environments of Korean credit rating agencies, which have kept credit rating agencies from providing fair, timely, and useful information. To warrant proper operation of credit rating agencies, it is essential to cope with unique problems in Korean credit rating agencies. We classify the unique problems of Korean credit rating agencies into ownership and governance structure, conflict of interests due to ancillary fee-based business, legal recognition of credit rating in the court, and code of conduct problem, etc. and propose policy directions to improve the quality and credibility of credit ratings.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.9-20
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• 2018

Global rating agencies, such as Moody's and S&P, have assigned credit ratings to corporate bonds issued by Japanese firms since 1980s. Local Japanese rating agencies, such as R&I and JCR, have more market share than the global raters. We examine the yield spreads of 1,050 yen-denominated corporate bonds issued by financial firms in Japan from 1998 to 2014 and find no evidence that bonds rated by at least one global agency are associated with a significant reduction in the cost of debt as compared to those rated by only local rating agencies. Unlike non-financial firms, the reputation effect of global rating agencies does not exist for Japanese financial firms. We also observe that firms with less information asymmetry are more likely to acquire ratings from Moody's or S&P. Additionally, the firm's financial profile does not affect its choice to seek out ratings from global raters. Our findings are contradictory to those by Han, Pagano, and Shin (2012), who employ bonds issued by non-financial firms in Japan. Our conjecture is that the asymmetric nature of financial firms makes investors less likely to depend on a credit risk assessment by rating agencies in determining the yields of new bonds.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.25-32
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• 2019

In the Korean capital market, there are three credit rating agencies. Potential credit ratings based on credibility in the financial market are calculated independently for each rating agency. It often happens that despite the fact that the grades of the rating agencies are the same and have the same rating system, their actual ratings are different, even for the same firm. In such circumstances, investors may wonder why. In this study, we assume that the cause is the information environment in which the company operates. The credit ratings of rating agencies are mainly classified into bonds or commercial papers. The bonds are rated primarily for long-term of three years or more, and commercial papers specify ratings for less than one year. The information environment to be verified in this study was observed with a commercial paper. Under the assumption the larger the analyst following is, the more transparent is the information environment, we analyzed the influence of the number of analysts following on the degree to which ratings conflicted among credit rating agencies. The results of our analysis confirmed that opinion conflict among credit rating agencies is clearly reduced for companies with good information environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3627-3641
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• 2021

Fintech, which stands for financial technology, is growing fast globally since the economic crisis hit the United States in 2008. Fintech companies are striving to secure a competitive advantage over existing financial services by providing efficient financial services utilizing the latest technologies. Fintech companies can be classified into several areas according to their business solutions. Among the Fintech sector, peer-to-peer (P2P) lending companies are leading the domestic Fintech industry. P2P lending is a method of lending funds directly to individuals or businesses without an official financial institution participating as an intermediary in the transaction. The rapid growth of P2P lending companies has now reached a level that threatens secondary financial markets. However, as the growth rate increases, so does the potential risk factor. In addition to government laws to protect and regulate P2P lending, further measures to reduce the risk of P2P lending accidents have yet to keep up with the pace of market growth. Since most P2P lenders do not implement their own credit rating system, they rely on personal credit scores provided by credit rating agencies such as the NICE credit information service in Korea. However, it is hard for P2P lending companies to figure out the intentional loan default of the borrower since most borrowers' credit scores are not excellent. This study analyzed the voices of telephone conversation between the loan consultant and the borrower in order to verify if it is applicable to determine the personal credit score. Experimental results show that the change in pitch frequency and change in voice pitch frequency can be reliably identified, and this difference can be used to predict the loan defaults or use it to determine the underlying default risk. It has also been shown that parameters extracted from sample voice data can be used as a determinant for classifying the level of personal credit ratings.

• Journal of Digital Convergence
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• v.13 no.2
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• pp.105-113
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• 2015

If the watchdog role of good corporate governance, corporate executives and reduce agency costs and information asymmetries. Corporate governance score higher because enterprise internal control systems and financial reporting system is well equipped with the company management is enabled and corporate performance is higher because the high financial credit rating. Under these assumptions and hypotheses set up this study corporate governance (CGI) has been studied demonstrated how the financial impact on the credit rating (CFR). Findings,

relevant corporate governance (CGI) and financial credit rating was found to significantly affect the positive (+), Regression coefficient code is expected code of positive (+), the value

indicated by the value of all positive. The results of corporate governance (CGI) has showed excellent results, such as the more predictable will increase the credit score financial rating. The results of this study will have more CGI-credit financial rating the greater good. This study might be expected to provide a useful guide that corporate social responsibility, the company with a good governance and oversight systems enable to to get a higher credit rating in practice and research.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.89-92
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• 2000

The purpose of this thesis is to investigate the information content of commercial paper credit rating changes of Korean firms. The result shows neither sinificant daily abnormal returns nor significant cumulative daily abnormal returns over the test window. This ind icates that commercial paper rating changes are not informative to investors. A sensitivity analysis conducted for the portfolio of subsample shows a similar result. This thesis, however, may contribute to the better operation of Korean financial market by providing several directions to establish credit-based financial transactions.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.615-631
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• 2008

Current credit evaluation models based on only financial data except non-financial data are used continuous data and produce credit scores for the ranking. In this work, some problems of the credit evaluation models based on transformed continuous financial data are discussed and we propose improved credit evaluation models based on categorized financial data. After analyzing and comparing goodness-of-fit tests of two models, the availability of the credit evaluation models for categorized financial data is explained.