• 한국정보시스템학회지:정보시스템연구
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• 제16권3호
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• pp.109-132
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• 2007

In the paper, we builds an advanced new credit evaluation system for Micro-small sized individual firms through appropriate evaluation factors derived by logistic regression analysis for credit evaluation model using in Korean Federation of Credit Guarantee Foundations, and the weights of factors computed by analytic hierarchy process(AHP). Industry characteristics are more applied to previous credit model with the additional the financial fact-information and non-financial judgement-information. Our results show that the financial factors have become more important than three years ago. Moreover, in the non-financial factors, the fact-information factors consider more important then the judgement-information factors. A new credit evaluation system is developed based on this credit evaluation model.

• The Journal of Asian Finance, Economics and Business
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• 제9권8호
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• pp.89-97
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• 2022

The e-commerce market faces significant credit risks due to the complexity of the industry and information asymmetries. Therefore, credit risk has started to stymie the growth of e-commerce. However, there is no reliable system for evaluating the creditworthiness of e-commerce companies. Therefore, this paper constructs a credit risk evaluation index system that comprehensively considers the online and offline behavior of online retail enterprises, including 15 indicators that reflect online credit risk and 15 indicators that reflect offline credit risk. This paper establishes an integration method based on a fuzzy integral support vector machine, which takes the factor analysis results of the credit risk evaluation index system of online retail enterprises as the input and the credit risk evaluation results of online retail enterprises as the output. The classification results of each sub-classifier and the importance of each sub-classifier decision to the final decision have been taken into account in this method. Select the sample data of 1500 online retail loan customers from a bank to test the model. The empirical results demonstrate that the proposed method outperforms a single SVM and traditional SVMs aggregation technique via majority voting in terms of classification accuracy, which provides a basis for banks to establish a reliable evaluation system.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.51-60
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• 2023

This study focuses on the design of a GPT-based system for relatively rapid technology credit assessment of SMEs. This system addresses the limitations of traditional time-consuming evaluation methods and proposes a GPT-based model to comprehensively evaluate the technological capabilities of SMEs. This model fine-tunes the GPT model to perform fast technical credit assessment on SME-specific text data. Also, It presents a system that automates technical credit evaluation of SMEs using GPT and LLM-based chatbot technology. This system relatively shortens the time required for technology credit evaluation of small and medium-sized enterprises compared to existing methods. This model quickly assesses the reliability of the technology in terms of usability of the base model.

• Journal of the Korean Data and Information Science Society
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• 제19권3호
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• pp.789-800
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• 2008

Current credit evaluation models based on financial data make use of smoothing estimated default ratios which are transformed from each financial variable. In this work, some problems of the credit evaluation models developed by financial experts are discussed and we propose improved credit evaluation models based on the stepwise variable selection method and Box-Cox transformed data whose distribution is much skewed to the right. After comparing goodness-of-fit tests of these models, the validation of the credit evaluation models using statistical methods such as the stepwise variable selection method and Box-Cox transformation function is explained.

• Communications for Statistical Applications and Methods
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• 제15권4호
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• pp.615-631
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• 2008

재무자료에 대한 신용평가모형은 각각의 재무변수를 평활한 예측부도율로 변환하여 사용한다. 본 연구에서는 연속형 재무자료를 변환하여 설정된 신용평가모형의 문제점을 살펴보고, 연속형 재무변수를 다양한 형태로 범주화한 신용평가모형들을 제안한다. 범주형 재무자료를 사용해서 개발한 여러 종류의 신용평가모형들의 성과를 다양한 적합성 검증 방법으로 비교하고, 범주형 재무자료를 이용한 신용평가모형의 유용성을 토론한다.

• 기술혁신연구
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• 제26권2호
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• pp.129-149
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• 2018

기술금융은 금융당국이 금융산업 선진화, 중소기업발전을 위해 강력한 정책적 의지를 가지고 도입하여 시행하고 있는 분야이다. 이러한 배경으로 은행의 자체적인 기술평가가 2016년 9월부터 시행되었다. 기술우수기업은 기술평가과정에서 산출된 높은 기술등급으로 기존 신용등급이 상향되게 되며, 결과적으로 높아진 신용등급만큼 금융거래시 혜택을 받게 된다. 분석대상은 KEB하나은행이 2016년 9월부터 2017년 하반기까지 수행한 기술평가 대상 2,719개 업체를 분석하였다. 2016년 하반기 수행된 406개 업체에 대한 기술력평가 예비 연구에서 기존 신용등급과 산출된 기술등급을 결합한 결과, J58'출판업'의 기술신용등급은 신용등급대비 1.05등급 상향되어 상향정도가 가장 높았으며, C10'식료품 제조업'이 두 번째로 상향정도가 높았다. 이로써 기술력평가를 통한 수혜업종을 가려낼 수 있었으며, 업종별 기술 평가의 유용성을 확인할 수 있었다. 이에, 전체 수행기간동안 평가된 2,719개 업체에 대하여 기술력, 업력, 성장유망업종별 분석을 수행하였다. 분석결과 기술력 T-4이상 등급 업체들의 신용등급 상향정도가 가장 높았으며 5년 기준 업력에 따른 기술력평가의 유효성은 미미한 것으로 파악되었다. 정책지원의 효율성차원에서 지정된 성장유망업종에 해당하는 업체들을 대상으로 분석한 결과 일반기업대비 신용등급의 상향정도가 높아 성장유망업종 지원의 유용성을 확인할 수 있었다. 향후, 은행의 업체 발굴 또는 당국의 정책수립시에 T-4이상의 기술력 우수기업, 성장유망 업종에 집중하면 자금지원 효과를 극대화할 수 있을 것으로 판단된다.

• 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.

• 한국건설관리학회논문집
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• 제5권4호
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• pp.97-106
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• 2004

국내 금융기관들의 현행 건설기업 신용평가는 그 자체로서 많은 문제점을 가지고 있고 건설산업의 특성 및 건설경영의 실제에서도 많이 벗어나 있다. 본 연구는 이러한 문제점들을 해결할 수 있는 대안으로서 DCiF(discounted cash Inflow) 모델을 개발하고 이의 적용방법론을 논의한다. 또한 실증자료에 근거하여 건설기업들의 DCiF 지수를 실제로 산출하고 이를 기존의 신용평가모델들과 비교함으로써 DCiF 모델의 변별력을 검증했다. 실증분석결과를 바탕으로 건설기업 신용평가에서의 동 모델의 보다 효율적인 적용을 위한 유의점 및 대안도 제시했다.

• Journal of Information Technology Applications and Management
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• 제11권1호
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• pp.161-174
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• 2004

This study is intended to suggest1 the optimized data mining model for the efficient customer credit evaluation in the capital finance industry. To accomplish the research objective, various data mining models for the customer credit evaluation are compared and analyzed. Furthermore, existing models such as Multi-Layered Perceptrons, Multivariate Discrimination Analysis, Radial Basis Function, Decision Tree, and Logistic Regression are employed for analyzing the customer information in the capital finance market and the detailed data of capital financing transactions. Finally, the data from the integrated model utilizing a genetic algorithm is compared with those of each individual model mentioned above. The results reveals that the integrated model is superior to other existing models.

• 한국정보시스템학회지:정보시스템연구
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• 제14권1호
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• pp.41-65
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• 2005

The credit ration is a significant area of financial management which is of major interest to practitioners, financial and credit analysts. The components of credit rating are identified decision models are developed to assess credit rating an the corresponding creditworthiness of firms an accurately ad possble. Although many early studies demonstrate a priori which of these techniques will be most effective to solve a specific classification problem. Recently, a number of studies have demonstrate that a hybrid model integration artificial intelligence approaches with other feature selection algorthms can be alternative methodologies for business classification problems. In this article, we propose a hybrid approach using rough set theory as an alternative methodology to select appropriate attributes for case-based reasoning. This model uses rough specific interest lies in lthe stable combining of both rough set theory to extract knowledge that can guide dffective retrevals of useful cases. Our specific interest lies in the stable combining of both rough set theory and case-based reasoning in the problem of corporate credit rating. In addition, we summarize backgrounds of applying integrated model in the field of corporate credit rating with a brief description of various credit rating methodologies.