A study on credit evaluation of power consumer based on the topsis and AHP method

The credit evaluation of power consumer is very important for the power company in the market operation. Inability to pay electricity charges due has always been a fundamental problem in electricity markets. This paper discusses credit evaluation of power consumer concept and constructs evaluation index system for credit power consumer then describes the theories and procedures of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) evaluation method and AHP (Analytic Hierarchy Process) method. “5C” which is often made use of by department of credit management in current credit evaluation, character, capacity, capital, collateral and condition, take as the basic to construct the consumer credit index system. Consumer credit evaluation divide power consumer into different credit rating. Finally, this paper takes ten customers for example data, using TOPSIS and AHP method to evaluate the credit power consumer. The method of TOPSIS, based on the original data matrix after their normalization, is to find out the optimal plan and the worst plan among the limited plans, and then calculate the differences between the various evaluation targets and the optimal and worst plans so as to obtain the relative closeness degree between them, which then will b used to judge whether they are good or bad ones. AHP uses simple pairwise comparisons to determine weights

Network Supplier Credit Management: Models Based on Petri Net

In current credit evaluation methods, the credit condition of the network supplier and the credit degree of each index cannot be described well, and the credit evaluation data only source of the transaction platform have much limitation. This research proposes the method of calculating the importance and the value of the credit evaluation indexes, and proposes to put credit evaluation into big data environment. This research uses the transaction process of B2C as the case, and constructs multiple attribute weighted Petri net credit index subnet (CWPSN) for realizing the credit evaluation of the network supplier, and for presenting the correlations among the evaluation results of the credit evaluation indexes, and for presenting the importance of the indexes and the credit degree of each index, and describes the cost optimization process with credit cost optimization investment process Petri net (CCOIPPN). By the case to verify the credit evaluation method based on Petri net and the cost optimization method based on Petri net. The researches have provided methods for clearly and concretely describing the process of credit evaluation and cost optimization of network supplier, and have guidance significance for similar other researches

Research on Credit Evaluation System of E-business Enterprises from The Perspective of Organizational Resilience Theory

With the rapid development of the electronic business industry and the widespread of information technology, the credit issue of e-business enterprises becomes more and more important. Traditional e-business credit evaluation focuses on the accumulation of transaction credit. However, the widespread phenomenon of credit brushing leads to the deviation of credit evaluation of ebusiness enterprises. To improve the effectiveness of the credit evaluation system, this study introduced resilience-related indicators which represent the dynamic capability and sustainability of enterprises into the credit evaluation system. According to the organizational resilience theory, we capture e-business enterprises’ credit from three dimensions: basic ability symbols, transaction process, and consumer feedback toward transaction outcomes. The potential influence of integrity grade, repeat purchase rate, return rate, and customer satisfaction were considered to mitigate the influence of deception on a credit evaluation. Combined with the analytic hierarchy process, this study constructed an adjusted credit evaluation model of e-business enterprises from the perspective of organizational resilience and tested the model with data from the Alibaba website. Fifteen considerable women\u27s clothing e-business enterprises were selected for credit comparison. Results show that the top enterprise mainly had advantages over other enterprises in terms of the high repeat purchase rate, low return rate, and high consumer satisfaction. Theoretically, our study contributes to enriching the credit evaluation model of e-business enterprises and making an extension on the application of organizational resilience theory. In addition, these findings are helpful to optimize the effectiveness of credit evaluation of e-business enterprises, provide practical implications for e-business enterprises by identifying the key indicators to improve their credit in the uncertain trading environment, and reduce the transaction risk of ebusiness platforms

Rule based Model for Credit Evaluation using Rough Set Approach

Credit plays an important role in the economy. Credit Evaluation of any potential credit application has remained a challenge for banks all over the world till today. Credit evaluation can be defined as a technique that helps lenders to decide whether to grant credit to consumers or not. Its increasing importance can be seen from the growing popularity and application of credit scoring. It is mandatory not only to construct effective credit scoring models to help improve the bottom-line of credit providers, but also to design rule based system for effective credit evaluation system. This paper approaches the use of rough set technique to generate rule based system for credit scoring model

Structure, Clearinghouses and Symmetry

We introduce and justify a taxonomy for the structure of markets and minimal institutions which appear in constructing minimally complex trading structures to perform the functions of price formation, settlement and payments. Each structure is presented as a playable strategic market game and is examined for its efficiency, the number of degrees of freedom and the symmetry properties of the structure.Strategic market games, Clearinghouses, Credit evaluation, Default

Credit Scoring with AHP and Fuzzy Comprehensive Evaluation Based on Behavioural Data from Weibo Platform

It is increasingly necessary to evaluate the customers\u27 credit. In the era of big data, Information on the Internet is commonly used to judge the credit worthiness of customers. Some users\u27 credit information is incomplete or unavailable, so credit managers cannot judge the true credit situation of these users. However, with the support of social data especially behavioural data and credit evaluation system, this problem can be effectively solved. This study used Weibo to obtain the behavioural data of Chinese users for credit evaluation. Two methods are used to calculate the credit scores of Weibo users, which are the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation methods. By analysing social processes and inviting experts to make decisions, we constructed a credit evaluation system to expose users\u27 behavioural characteristics. We found that the three key indexes determining the user’s social credit are personal identification, behavioural characteristics and interaction among friends. Then, AHP was used to determine the weight of each index. Finally, a static algorithm was proposed to compute the credit evaluation system of Weibo users using fuzzy comprehensive evaluation methods

Credit risk evaluation by using nearest subspace method

AbstractIn this paper, a classification method named nearest subspace method is applied for credit risk evaluation. Virtually credit risk evaluation is a very typical classification problem to identify “good” and “bad” creditors. Currently some machine learning technologies, such as support vector machine (SVM), have been discussed widely in credit risk evaluation. But there are many effective classification methods in pattern recognition and artificial intelligence have not been tested for credit evaluation. This paper presents to use nearest subspace classification method, a successful face recognition method, for credit evaluation. The nearest subspace credit evaluation method use the subspaces spanned by the creditors in same class to extend the training set, and the Euclidean distance from a test creditor to the subspace is taken as the similarity measure for classification, then the test creditor belongs to the class of nearest subspace. Experiments on real world credit dataset show that the nearest subspace credit risk evaluation method is a competitive method

A Dynamic Credit Evaluation Approach Using Sensitivity-Optimized Weights for Supply Chain Finance

Supply chain financing provides important funding channels for micro and small enterprises (MSEs), but effectively evaluating their creditworthiness remains challenging. Past methods overly rely on static financial indicators and subjective judgment in determining credit evaluation weights. This study proposes a dynamic credit evaluation approach that uses sensitivity analysis to optimize the weighting scheme. An indicator system is constructed based on the unique characteristics of e-commerce MSEs. The weight optimization integrates subjective, objective, and sensitivity-based methods to reflect specific financing scenarios. A system dynamics model simulates the credit evaluation mechanism and identifies the sensitivity of each influencing factor. The resultant comprehensive weights are applied in a TOPSIS-GRA dynamic evaluation model to assess MSE credit levels over time. An empirical analysis of 20 online stores demonstrates the proposed model\u27s advantages in accurately revealing credit rankings relative to conventional static models. This research provides an effective data-driven weighting technique and dynamic evaluation framework for supply chain finance credit assessment

USE OF CREDIT EVALUATION PROCEDURES AT AGRICULTURAL BANKS IN MINNESOTA: 1991 SURVEY RESULTS

Agricultural Finance,

Performance of Different Institutional Units in the Czech Republic and the Role of External Financing

The paper analyses the relationship between the financial structure of the different institutional units in the Czech Republic and their performance, by testing several theoretical hypotheses. It employs Data Envelopment Analysis to estimate separately corporate and individual farms' technical efficiency, and investigates the effect of indebtedness on efficiency in a second stage, accounting for potential endogeneity. No substantial differences were detected between individual and corporate farms. For both groups higher long-term indebtedness negatively affects farm performance (agency theory and adjustment hypothesis), while the latter is used for appraising loan applications (credit evaluation). Case studies to banks and farms confirmed these findings.corporate farms, credit, Czech Republic, individual farms, technical efficiency, Agribusiness,