• 산경연구논집
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• 제13권10호
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• pp.1-8
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• 2022

Purpose: Support vector machines (SVMs) ensemble has been proposed to improve classification performance of Credit risk recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. To deal with this problem, this paper designs a support vector machines (SVMs) ensemble method based on fuzzy integral, which aggregates the outputs of separate component SVMs with importance of each component SVM. Research design, data, and methodology: This paper designs a personal credit risk evaluation index system including 16 indicators and discusses a support vector machines (SVMs) ensemble method based on fuzzy integral for designing a credit risk assessment system to discriminate good creditors from bad ones. This paper randomly selects 1500 sample data of personal loan customers of a commercial bank in China 2015-2020 for simulation experiments. Results: By comparing the experimental result SVMs ensemble with the single SVM, the neural network ensemble, the proposed method outperforms the single SVM, and neural network ensemble in terms of classification accuracy. Conclusions: The results show that the method proposed in this paper has higher classification accuracy than other classification methods, which confirms the feasibility and effectiveness of this method.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.873-880
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• 2021

The purpose of this study is to investigate the impact of internal control on credit risk of joint stock commercial banks in Vietnam from 2007 to 2018. Furthermore, we specify bank-specific characteristics and macroeconomic conditions, and analyze how these factors affect credit risk of banks: the number of board members, the number of board members with banking or finance background as ratio of total board members, loans to total assets ratio, loans to deposit ratio, the number of days between the year-end and the publication of the financial statements, and the use of top four auditing firms proxy for five elements of internal control. By using the dataset of 30 Vietnamese joint stock commercial banks and Bayesian linear regression via Random-walk Metropolis Hastings algorithm, the results of this study show that five elements of internal control have a impact on bank credit risk, namely, control environment, risk assessment, control activities, information and communication, and monitoring activities. For factors of banks' characteristics, bank size and financial leverage have a negative impact on banks' credit risk, and bank age has a positive effect. For macroeconomic factors, inflation has a positive impact and economic growth has a negative impact on banks' credit risk.

• 한국건설관리학회논문집
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• 제21권5호
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• pp.64-73
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• 2020

정부는 신용평가시스템을 객관화하여 회생가능성이 있는 기업은 자금을 지원하고, 회생가능성이 없는 기업은 조기에 구조조정을 추진하는 방안을 발표하였다. 이러한 정부발표는 자본시장을 통한 구조조정의 기반을 강화하여 신속한 구조조정이 이루어질 수 있는 기틀을 마련함으로써 재무건전성이 낮은 중견건설사는 구조조정 위험에 확대될 수 있다. 본 연구는 2019년 기준으로 주택사업에 집중된 10개 중견건설사를 선정하여 은행의 재무심사기법을 통해 재무건전성을 분석하였고, 이러한 분석결과를 통해 구조조정 위험에 노출될 가능성이 높음을 확인할 수 있었다. 2020년에는 경제성장률 하락과 부동산규제 강화로 건설업 성장률이 전반적으로 하락될 것으로 판단되어 자본금 납입비율이 낮은 중견건설사는 안정적인 신용등급을 유지할 가능성이 낮아 구조조정에 포함될 가능성이 높다. 본 연구는 중견건설사가 구조조정 위험에서 벗어날 수 있도록 공신력 있는 연구기관의 자료를 활용하여 KCSI 평가모델을 설정하였고, 실무전문가 설문조사를 통해 각 항목마다 차별화된 위험비율을 나타냈다. 이러한 연구결과는 중견건설사 경영진에게 신용리스크 저감방안을 실천하도록 제언할 수 있었고, 구조조정 위험에 벗어날 수 있는 기틀을 마련하였다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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• pp.347-354
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• 1999

The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.

• 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.

• Journal of Information Technology Applications and Management
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• 제14권2호
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• pp.151-168
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• 2007

The corporate credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this study, the corporate credit rating model employs artificial intelligence methods including Neural Network (NN) and Case-Based Reasoning (CBR). At first we suggest three classification models, as partitioned neural networks, all of which convert multi-group classification problems into two group classification ones: Ordinal Pairwise Partitioning (OPP) model, binary classification model and simple classification model. The experimental results show that the partitioned NN outperformed the conventional NN. In addition, we put to use CBR that is widely used recently as a problem-solving and learning tool both in academic and business areas. With an advantage of the easiness in model design compared to a NN model, the CBR model proves itself to have good classification capability through the highest hit ratio in the corporate credit rating.

• 디지털융복합연구
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• 제17권9호
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• pp.71-78
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• 2019

본 연구는 P2P 대부 플랫폼에서 우수 대출자를 예측시 유용한 합성 소수집단 오버샘플링 기법을 제안하고 그 성과를 실증적으로 검증하고자 한다. P2P 대부 관련 우수 대출자를 추정할 때 일어나는 문제점중의 하나는 클래스 간 불균형이 심하여 이를 해결하지 않고서는 우수 대출자 예측이 쉽지 않다는 점이다. 이러한 문제를 해결하기 위하여 본 연구에서는 SMOTE, 즉 합성 소수집단 오버샘플링 기법을 제안하고 LendingClub 데이터셋에 적용하여 성과를 검증하였다. 검증결과 SMOTE 방법은 서포트 벡터머신, k-최근접이웃, 로지스틱 회귀, 랜덤 포레스트, 그리고 딥 뉴럴네트워크 분류기와 비교하여 통계적으로 우수한 성과를 보였다.

• The Journal of Asian Finance, Economics and Business
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• 제7권11호
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• pp.893-904
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• 2020

The study examines the relationship between credit risk and operational risk (understanding of risk management, risk identification, risk assessment and control, and risk monitoring) on risk management practices followed by private and public sector commercial banks. The cross-sectional data method was used to check the impact of risk management practices. Data was collected from the bank employees and a total of 284 respondents were finally selected for further analysis. Measurement Invariance of Composite Models analysis is used to test the quality of the measurement model for sub-samples, and multi-group analysis is used for path analysis in sub-sample through PLS-SEM. The findings of the study as the total sample show that both types of banks are managing adequate and significant risk management practices. On the other hand, sub-groups' results show private sector banks are more momentous than public sector banks. Risk identification is significantly different at the sub-group level, which shows public sector banks are more concentrating on this type of risk. Understanding of risk management has no significant effect on both types of banks and risk assessment & control for public sector banks, and there is a difference in the risk management practices among private and public sector commercial banks.

• 전기학회논문지
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• 제65권6호
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• pp.923-933
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• 2016

This paper proposes a new method for evaluating Effective Load Carrying Capability(ELCC) and capacity credit(C.C.) of power system including Wind Turbine Generator(WTG) combined with Battery Energy Storage System(BESS). WTG can only generate electricity power when the fuel(wind) is available. Because of fluctuation of wind speed, WTG generates intermittent power. In view point of reliability of power system, intermittent power of WTG is similar with probabilistic characteristics based on power on-off due to mechanical availability of conventional generator. Therefore, high penetration of WTG will occur difficulties in power operation. The high penetration of numerous and large capacity WTG can make risk to power system adequacy, quality and stability. Therefore, the penetration of WTG is limited in the world. In recent, it is expected that BESS installed at wind farms may smooth the wind power fluctuation. This study develops a new method to assess how much is penetration of WTG able to extended when Wind Turbine Generator(WTG) is combined with Battery Energy Storage System(BESS). In this paper, the assessment equation of capacity credit of WTG combined with BESS is formulated newly. The simulation program, is called GNRL_ESS, is developed in this study. This paper demonstrates a various case studies of ELCC and capacity credit(C.C.) of power system containing WTG combined with BESS using model system as similar as Jeju island power system. The case studies demonstrate that not only reasonable BESS capacity for a WTG but also permissible penetration percent of WTG combined with BESS and reasonable WTG capacity for a BESS can be decided.

• The Journal of Asian Finance, Economics and Business
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• 제5권4호
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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.