• KDI Journal of Economic Policy
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• v.39 no.3
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• pp.43-62
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• 2017

This paper proposes an integrated risk-management framework that includes 1) measuring the risk of credit portfolios, 2) implementing a (macro) stress test, and 3) setting risk limits using the estimated systematic latent factor specific to capture the housing market cycle. To this end, we extract information from a set of real-estate market variables based on the FAVAR methodology proposed by Bernanke, Boivin and Eliasz (2005). Then, we show the method by which the estimated systematic factor is applied to risk management in the housing market in an integrated manner within the Vasicek one-factor credit model. The proposed methodology is well fitted to analyze the risk of slow-moving and low-defaultable forms of capital, such as alternative investments.

• IE interfaces
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• v.20 no.4
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• pp.448-457
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• 2007

The small & micro business has the characteristics of both consumer credit risk and business credit risk. In predicting the bankruptcy for small-micro businesses, the problem is that in most cases, the financial data for evaluating business credit risks of small & micro businesses are not available. To alleviate such problem, we propose a bankruptcy prediction mechanism using the credit card sales information available, because most small businesses are member store of some credit card issuers, which is the main purpose of this study. In order to perform this study, we derive some variables and analyze the relationship between good and bad signs. We employ the new statistical learning technique, support vector machines (SVM) as a classifier. We use grid search technique to find out better parameter for SVM. The experimental result shows that credit card sales information could be a good substitute for the financial data for evaluating business credit risk in predicting the bankruptcy for small-micro businesses. In addition, we also find out that SVM performs best, when compared with other classifiers such as neural networks, CART, C5.0 multivariate discriminant analysis (MDA), and logistic regression.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.2
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• pp.17-29
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• 2012

We examine a mortgage bank's incentive distortion problem when the bank sells its existing loan through MBS(Mortgage-Backed Security), considering the mortgage market structure and varying investors' risk attitude. Main findings in our comparative statics are the followings. The bank's monitoring incentive on the loan sold is distorted downwards when the deposit interest rate is lower than the coupon rate of MBS. Credit enhancement associated with the loan sale may mitigate the incentive distortion problem. However, the downward distortion of monitoring incentive does not disappear unless the credit enhancement, a loan guarantee, is provided up to 100%. Finally as the investors' risk preference changes from risk-neutral to risk-averse type, the incentive distortion problem becomes more severe. At the end, we recommend the introduction of covered bond in order to mitigate the incentive distortion problem, which is inevitable to current pass-through MBS.

• Asia pacific journal of information systems
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• v.10 no.2
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• pp.149-176
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• 2000

As companies become more dependent upon information systems(IS), the potential losses of IS resources become critical. IS management must assume the increasing responsibility for protection of IS resources as the IS and business environments become more vulnerable to various threats. The major issues facing management, when attempting to manage risks, include the assessment of the impact of risks on business objectives and the design of security safeguards to reduce the unacceptable risks to an acceptable level. This paper provides a case study of the risk management for IS. A Korean credit card company which has the high sensitivity for customers security was selected as a case. The risk management procedure using a powerful tool, CRAMM(the Central Computer and Telecommunications Agencys Risk Analysis and Management Method) was applied for this company.

• International Commerce and Information Review
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• v.10 no.2
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• pp.283-304
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• 2008

According to globalization and localization of world economics international trade payment method was also changed. A traditional payment was Letter of Credit basis, however it is being increased to various methods such as remittance, documentary collection(D/P, D/A) and open account. In order to acquire a secure export payment, exporters prefer to L/C basis which is guaranteed by a reliable bank. However, the L/C should bear a security so that importers would rather documentary collection than L/C. The reasons for the preference of collection payment rather than L/C are a low commission cost, the conversion of buyer's market from seller's market due to severe competition in the world market, transaction increase between main office and branches and a right to control the goods until executing the payment by exporters. Besides of them, collection payment can handle safer and faster than open account basis. However, the collection payment has a risk which it isn't guaranteed by bank for the payment so that I would suggest countermeasures to minimize the payment risk utilizing the collection basis as follows; using export credit insurance system, a large domestic credit report provider such as D&B for absolutely fresh and new information, a collection proxy service for overseas deferred credit and suggestion specifying to order B/L not straight one on consignee in order to transfer the right of ownership with endorsement without problem.

• Korean Journal of Artificial Intelligence
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• v.9 no.1
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• pp.21-27
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• 2021

In this Paper, Since the 1990s, Korea's credit card industry has steadily developed. As a result, various problems have arisen, such as careless customer information management and loans to low-credit customers. This, in turn, had a high delinquency rate across the card industry and a negative impact on the economy. Therefore, in this paper, based on Azure, we analyze and predict the delinquency and delinquency periods of credit loans according to gender, own car, property, number of children, education level, marital status, and employment status through linear regression analysis and enhanced decision tree algorithm. These predictions can consequently reduce the likelihood of reckless credit lending and issuance of credit cards, reducing the number of bad creditors and reducing the risk of banks. In addition, after classifying and dividing the customer base based on the predicted result, it can be used as a basis for reducing the risk of credit loans by developing a credit product suitable for each customer. The predicted result through Azure showed that when predicting with Linear Regression and Boosted Decision Tree algorithm, the Boosted Decision Tree algorithm made more accurate prediction. In addition, we intend to increase the accuracy of the analysis by assigning a number to each data in the future and predicting again.

• Korean Management Science Review
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• v.15 no.1
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• pp.137-148
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• 1998

We proposed a framework for computer-supported credit evaluation systems for the effective management of credit risks in Korean commercial banks. Especially for medium and small sized companies, credit evaluators used to depend much on past experience rather than formalized principles and rules. Therefore, we applied case-based reasoning. The credit grade of a company is roughly determined by searching for alreadygraded similar companies in terms of usually accepted evaluation items. And then the grade is refined and adjusted by considering additional information about exceptional facts or by reflecting other evaluation results from different methods or techniques. Booch's object-oriented analysis and design method, Visual Basic 5.0 and MS Access 97 are used for the development of this prototype system.

• International Commerce and Information Review
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• v.15 no.1
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• pp.259-283
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• 2013

In this study has been suggested on the basis of the Court of Audit's report on trade insurance issues presented and the Export Credit Guarantee Insurance Improvement. First, the improvement insurance underwriting standards and come up with measures to improve the soundness of the insurance fund trading. In order to do this, (1) warranty for a lower credit companies strengthen underwriting standards, (2) raise short-term solvency and the accuracy of financial statements Review criteria Borrowings calculated based, (3) trustee companies Warranty Terms for improvement, (4) for closure of businesses quickly take measures of bond conservation measures. Second, through improved risk management measures to strengthen risk management for export credit guarantees are to be provided.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.11-20
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• 2024

This study presents TabNet, a novel deep learning method, to enhance corporate credit rating accuracy amidst growing financial market uncertainties due to technological advancements. By analyzing data from major Korean stock markets, the research constructs a credit rating prediction model using TabNet. Comparing it with traditional machine learning, TabNet proves superior, achieving a Precision of 0.884 and an F1 score of 0.895. It notably reduces misclassification of high-risk companies as low-risk, emphasizing its potential as a vital tool for financial institutions in credit risk management and decision-making.

• 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.