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-comm...

Technology evaluation has played a crucial role in selecting and supporting companies with innovative technology. Previous studies have focused on developing technology evaluation methods such as scorecard. However, technology credit rating is rarely applied, despite its convenient usage for technology financing. In this paper, we propose a technology credit rating system, called cross matrix, ...

The assessment of credit risk usually involves the development of rating models that classify credit applicants (firms or individuals) into predefined risk groups. A plethora of methodologies have been proposed to develop such rating models. Among them support vector machines (SVMs) have rapidly evolved in statistical learning theory as new modeling technique for developing classification model...

The purpose of this work is to examine the relationship various financial and non-financial (qualitative) factors performance companies their credit ratings.
 We developed scoring model which was based on methodologies international Russian rating agencies. modelled ratings for 2018–2020 were compared with actual assigned by agencies discrepancies explained. sample includes from retail, pr...

We consider the estimation of credit scores by means of semiparametric logit models. In credit scoring, the fitted rating score shall not only provide an optimal classification result but serves also as a modular component of a (typically quite complex) rating system. This means in particular that a rating score should be given by a linearly weighted sum of rating factors. That way the rating p...

expert systems can help to build banks customers' credit scoring models. here, selection of key features of the credit scoring is important. also, it is possible to express the features values as fuzzy. the problem is how to improve features selection by genetic algorithm, in way that these features can be employed as input in fuzzy expert system. this paper presents a hybrid credit scorin...

Lenders experience positive net revenue impacts from lending if they increase the classification power of their credit scoring systems. If loan officers’ subjective assessments of otherwise intangible borrower characteristics contain additional information about a borrower, a lender may improve the default forecast quality of his internal credit scoring systems by utilizing this subjective info...