• KDI Journal of Economic Policy
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• 제39권3호
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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.

• 산업공학
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• 제20권4호
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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.

• 한국경영과학회지
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• 제37권2호
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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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• 제10권2호
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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.

• 통상정보연구
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• 제10권2호
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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.

• 한국인공지능학회지
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• 제9권1호
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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.

• 경영과학
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• 제15권1호
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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.

• 통상정보연구
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• 제15권1호
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• pp.259-283
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• 2013

수출신용보증은 수출계약과 관련하여 외국환은행이 중소기업자인 수출업자에게 수출신용보증서를 담보로 대출함에 따라 발생하는 수출자의 상환채무에 대하여 한국무역보험공사가 그 지급을 연대보증하는 것으로 외국환은행은 안심하고 수출금융을 취급할 수 있다. 또한 중소기업 수출자도 별도의 담보를 제공하지 않아 현재 중소기업은 전용보증제도인 수출보험제도를 가장 선호하고 있다. 하지만 한국무역보험공사가 지원하는 수출신용보증의 경우 최근 5년간 인수실적이 공사 전체 인수실적(보험 및 보증인수 총액, 총 604조여 원)의 2.64%(16조여 원)에 불과한데도 5,262억 원의 보험수지 적자가 발생하는 등 무역기금손실의 주요 요인으로 작용하고 있다. 따라서 본고에서는 중소기업의 건전한 수출지원 정책으로서 안정적인 무역금융지원기반을 마련하고 기금운용의 건전성 확보와 절감 방안을 검토하기 위해 2011년 11월 감사원의 무역보험실태 보고서를 토대로 수출신용보증제도의 사례분석을 통해 문제점을 고찰하고 무역보험운용상의 개선방안을 도출하고자 한다.

• 한국컴퓨터정보학회논문지
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• 제29권5호
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• pp.11-20
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• 2024

최근 IT 기술의 발전과 더불어 금융 시장에서의 불확실성이 증대되는 상황에서 기업 신용등급 평가의 중요성을 인식하고, 이를 개선하기 위한 새로운 접근 방식으로 딥러닝 모델인 TabNet을 제안한다. 이에 본 연구에서는 TabNet을 활용하여 기업 신용등급을 예측하고, 이의 예측 성능을 기존 머신러닝 방법론과 상세하게 비교한다. 한국의 주요 증권시장에 상장된 기업들의 재무 데이터를 기반으로 TabNet 알고리즘을 적용하여 신용등급 예측 모델을 구축하고, 다양한 머신러닝 모델과의 성능을 비교 분석하였다. 실험 결과, TabNet 모델은 Precision 0.884, F1이 0.895로 기존의 머신러닝 모델들보다 우수한 성능을 보였으며, 고위험 기업을 저위험 기업으로 잘못 분류하는 경우가 다른 머신러닝 모델보다 적어 TabNet의 우수성을 확인하였다. 이는 TabNet이 기업 신용등급 예측에 있어 효과적인 도구로 활용될 수 있으며, 금융기관의 신용 위험 관리 및 의사 결정 과정을 지원할 수 있을 것으로 기대한다.

• 한국산학기술학회논문지
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• 제1권1호
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• pp.91-100
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• 2000

과거 국내금융기관의 신용공여는 소수 대기업과 그들의 계열사 및 일부 업종에 집중되었기 때문에 국내금융기관은 위험이 분산된 대출포트폴리오를 소유하지 못했었다. 이번 IMF 금융위기는 다수의 부실채권을 발생시킴으로써 개별 대출에 대한 위험관리뿐만 아니라 대출들로 구성되어진 포트폴리오에 대한 위험관리가 필수적이라는 것을 보여주었다. 본 논문의 목표는 국내금융기관들이 신용위험을 분산시켜 위험-수익 측면에서 효율적인 대출포트폴리오의 관리 방안을 제시하고자 하는 것이다. 본 논문에서는 대출포트폴리오의 효율적 관리를 위하여 선진 금융기관에서 많이 사용하는 계량적 신용위험관리 기법인 KMV Model과 CreditMetrics를 소개하였다. KMV Model은 옵션가격결정모형에 근거하여 기업의 주가수준 및 변동성으로 부터 대출기업의 부도확률을 도출하고, 주가의 상관관계를 토대로 개별 대출들간에 기대수익의 상관관계를 추정한다. 따라서 금융기관은 이 모형을 이용하여 위험이 잘 분산된 효율적인 대출포트폴리오를 구할 수 있다. CreditMetrics는 대출포트폴리오의 위험노출을 계량적으로 평가하는 VaR(Value at Risk)를 구하는 것으로 신용위험으로 인한 대출포트폴리오의 가치변동에 따른 잠재적 손실을 측정하는 기법이다. 이 기법에 따르면 금융기관은 과거 경험에 근거하여 신용등급별로 신용등급의 변동확률을 파악하고, 신용등급의 변동에 따른 대출포트폴리오 가치 변동과 손실가능성을 측정할 수 있다. 이와 같이 국내금융기관은 보다 과학적이고 계량화된 위험관리 기법을 적용하여 개별 대출의 한계위험공헌도 및 대출들 상호간에 위험의 상관관계를 고려하여 신용위험을 분산시키는 대출포트폴리오 관리를 실시해야 할 것이다.