• 대한안전경영과학회지
• /
• 제10권2호
• /
• pp.71-83
• /
• 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.

• Journal of Information Processing Systems
• /
• 제11권2호
• /
• pp.173-183
• /
• 2015

At present, it is simple to the electronic commerce credit scoring model, as a brush credit phenomenon in E-commerce has emerged. This phenomenon affects the judgment of consumers and hinders the rapid development of E-commerce. In this paper, that E-commerce credit evaluation model that uses a Gaussian density function is put forward by density test and the analysis for the anomalies of E-commerce credit rating, it can be fond out the abnormal point in credit scoring, these points were calculated by nonlinear credit scoring algorithm, thus it can effectively improve the current E-commerce credit score, and enhance the accuracy of E-commerce credit score.

• 전기학회논문지
• /
• 제57권12호
• /
• pp.2153-2160
• /
• 2008

This paper develops an algorithm for probabilistic production cost credit evaluation of wind turbine generators(WTG) with multi-state. Renewable energy resources such as wind, wave, solar, micro hydro, tidal and biomass etc. are becoming importance stage by stage because of considering effect of the environment. Wind energy is one of the most successful sources of renewable energy for the production of electrical energy. Case study demonstrates that the wind speed credit in view point of economics can be assessed by using the proposed methodology.

• 경영과학
• /
• 제15권1호
• /
• pp.97-115
• /
• 1998

This study aims to develop the methodology based on the AHP(Analytic Hierarchy Process) of evaluation for commercial paper. commercial paper is the ma product of merchant banks. commercial paper evaluation is annually performed by the credit-evaluation agency. Credit evaluation is performed by the informal judgemental system, which has potential to induce serious inconsistencies in decision-making. We present an objective scoring model which does not suffer from the weakness of the subjective judgement system. The model used is illustrated by analyzing the commercial paper evaluation for the 3 motor-companies(H, K and S motors).

• 한국정보시스템학회지:정보시스템연구
• /
• 제16권3호
• /
• pp.1-20
• /
• 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.

• 기술혁신연구
• /
• 제25권4호
• /
• pp.1-15
• /
• 2017

2014년, 금융위원회는 기술신용평가기관(TCB, Tech Credit Bureaus)을 지정하여 기술신용평가서를 발급하게 하였고 현재까지 5개의 기술신용평가기관과 금융위원회 권고, 레벨 4에 진입한 KEB하나은행, 국민은행, 우리은행, 신한은행 등에서 기술신용평가서를 발급하고 있다. 한편, KEB하나은행의 기술평가모델은 25개의 세부평가항목으로 구성되어 있으며, 이러한 항목등급이 가중 결합되어 기술등급이 산출, 기술등급은 신용등급과 결합하여 최종적으로 기술신용등급이 산출된다. 본 연구에서는 KEB하나은행에서 2016년 하반기에 자체발급한 406건의 기술평가결과를 분석하였으며, 경영주 동업종 근무년수, 기술개발전담부서 보유여부, 기술인력, 연구개발투자금액, 인증수, 특허수를 기반으로 지표간의 상관분석 및 기술등급과의 영향력을 분석하였다. 분석결과에 의하면, 기술개발전담부서, 특허수, 연구개발투자금액 등의 정량적지표가 기업 기술등급에 상당한 영향을 끼치는 것으로 나타났으며, 특히, 기술개발전담부서 보유여부는 기술등급과 가장 높은 상관관계를 나타내고 있음을 나타냈다.

• 한국융합학회논문지
• /
• 제9권1호
• /
• pp.1-8
• /
• 2018

본 연구는 기업의 사회적 책임과 감사인 규모가 기업의 신용등급에 어떠한 영향을 미치는지를 실증적으로 분석하였다. 본 연구는 관심변수를 기준으로 2005년부터 2011년까지 경실련 경제정의연구소가 경제정의기업으로 선정한 기업을 대상으로 최종표본 159개 기업/연 자료를 분석하였다. 분석결과는 다음과 같다. 첫째, CSR 항목 중 건전성과 기업의 사회적 책임활동 총점이 높을수록 기업신용등급은 유의하게 높게 나타났다. 이러한 결과는 신용평가기관이 기업의 사회적 책임활동을 긍정적으로 평가하여 신용등급에 반영한다는 것을 의미한다. 그러나 환경보호만족도와 기업신용등급 간에는 반대의 결과가 나타났다. 둘째, CSR 활동 중 공정성과 경제발전기여도가 높고 대형감사인이 감사할수록 기업신용등급은 유의하게 높게 나타났다. 반면, 건전성이 높고 대형감사인이 감사할수록 기업신용등급은 낮게 나타나 신용평가기관이 신용등급을 평가함에 있어 CSR 활동 간에 차별적인 반응이 있는 것으로 파악된다.

• 경영정보학연구
• /
• 제4권2호
• /
• pp.361-376
• /
• 2002

본 논문은 국내 은행금응기관의 신용위험관리를 보다 효율적이고 과학적으로 지원하기 위한 통합 위험관리시스템의 프레임웍을 제시한다. 즉, 담보 보증중심의 사전관리 위주의 대출관리에서 신용중심의 사후관리 위주의 대출관리로 전환되어야 함에 따라 신용평가시스템, 대출의사결정시스템, 사후관리시스템, 그리고 통합 신용위험관리시스템에 이르기까지 각 단위 시스템이 전체적으로 하나의 시스템으로 통합되어야 한다. 특히, 통합 위험관리시스템은 신용위험을 은행전체의 신용 포트폴리오의 관점에서 측정하고 분석함을 의미한다. 통합 위험관리시스템은 개별 대출기업 혹은 개별 대출에 대한 신용위험을 분석함과 동시에 이를 기초 데이터로하여 은행 전체 신용 포트폴리오의 신용위험 노출정도를 파악한다. 또한, 개별 대출기업의 신용등급 변화로 인한 은행전체 신용위험의 변화를 자동적으로 파악하고 조기 경보함으로써 은행의 총체적인 통합 신용위험관리가 가능하도록 한다.

• 산경연구논집
• /
• 제13권10호
• /
• pp.1-8
• /
• 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.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2002년도 추계정기학술대회
• /
• pp.491-501
• /
• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.