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MSEs credit risk assessment Model Based on Federated Learning and Feature Selection

Computers, Materials & Continua 2023年第6期75卷 5573-5595页

作者： Zhanyang Xu Jianchun Cheng Luofei Cheng Xiaolong Xu Muhammad Bilal School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory Novel Software Technology Nanjing UniversityNanjing210023China Department of Computer and Electronics Systems Engineering Hankuk University of Foreign StudiesYongin-siGyeonggi-do17035Korea

Federated learning has been used extensively in business inno-vation scenarios in various *** research adopts the federated learning approach for the first time to address the issue of bank-enterprise information asymmetry in the credit assessment ***,this research designs a credit risk assessment model based on federated learning and feature selection for micro and small enterprises(MSEs)using multi-dimensional enterprise data and multi-perspective enterprise *** proposed model includes four main processes:namely encrypted entity alignment,hybrid feature selection,secure multi-party computation,and global model ***,a two-step feature selection algorithm based on wrapper and filter is designed to construct the optimal feature set in multi-source heterogeneous data,which can provide excellent accuracy and *** addition,a local update screening strategy is proposed to select trustworthy model parameters for aggregation each time to ensure the quality of the global *** results of the study show that the model error rate is reduced by 6.22%and the recall rate is improved by 11.03%compared to the algorithms commonly used in credit risk research,significantly improving the ability to identify ***,the business operations of commercial banks are used to confirm the potential of the proposed model for real-world implementation.

关键词： Federated learning feature selection credit risk assessment MSEs

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Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

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Financial Innovation 2023年第1期9卷 2939-2991页

作者： Zhen‑Song Chen Jia Zhou Chen‑Ye Zhu Zhu‑Jun Wang Sheng‑Hua Xiong Rosa M.Rodríguez Luis Martínez Mirosław J.Skibniewski School of Civil Engineering Wuhan UniversityWuhan 430072China College of Civil Aviation Safety Engineering Civil Aviation Flight University of ChinaGuanghan 618307China School of Management Xi’an Jiaotong UniversityXi’an 710049China Department of Computer Science University of Jaén23071 JaénSpain Department of Civil and Environmental Engineering University of MarylandCollege ParkMD 20742‑3021USA Institute for Theoretical and Applied Informatics Polish Academy of SciencesGliwicePoland Chaoyang University of Technology TaizhongTaiwan

credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and *** the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment ***,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate ***,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment *** improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making ***,a credit risk assessment index for Chinese real estate enterprises is ***,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II *** approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation ***,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and *** study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

关键词： Real estate enterprise credit risk assessment PROMETHEE II Best–worst method Proportional hesitant fuzzy linguistic term sets

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A credit risk assessment model based on SVM for small and medium enterprises in supply chain finance

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Financial Innovation 2015年第1期1卷 208-228页

作者： Lang Zhang Haiqing Hu Dan Zhang School of Economics and Administration Xi’an University of TechnologyShaanxi 710054China

Background:Supply chain finance(SCF)is a series of financial solutions provided by financial institutions to suppliers and customers facing demands on their working *** a systematic arrangement,SCF utilizes the authenticity of the trade between(SMEs)and their“counterparties”,which are usually the leading enterprises in their supply *** in these arrangements the leading enterprises are the guarantors for the SMEs,the credit levels of such counterparties are becoming important factors of concern to financial institutions’risk management(i.e.,commercial banks offering SCF services).Thus,these institutions need to assess the credit risks of the SMEs from a view of the supply chain,rather than only assessing an SME’s repayment *** aim of this paper is to research credit risk assessment models for ***:We establish an index system for credit risk assessment,adopting a view of the supply chain that considers the leading enterprise’s credit status and the relationships developed in the supply ***,We conducted two credit risk assessment models based on support vector machine(SVM)technique and BP neural network ***:(1)The SCF credit risk assessment index system designed in this paper,which contained supply chain leading enterprise’s credit status and cooperative relationships between SMEs and leading enterprises,can help banks to raise their accuracy on predicting a small and medium enterprise whether default or ***,more SMEs can obtain loans from banks through SCF.(2)The SCF credit risk assessment model based on SVM is of good generalization ability and robustness,which is more effective than BP neural network assessment ***,Banks can raise the accuracy of credit risk assessment on SMEs by applying the SVM model,which can alleviate credit rationing on ***:(1)The SCF credit risk assessment index system can solve the problem of banks incorrectly labeling a creditworthy enterprise as a d

关键词： SCF SMEs credit risk assessment SVM BP Neural Network Technique

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Personal credit risk .Scoring Model Based on Rough Set and Neural Network

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Journal of Systems Science and Information 2008年第4期6卷 307-314页

作者： Hui Lu Shangfeng Yao Section of Mathematics and Physics Bengbu Tank Institute Bengbu 233050 Anhui China

In order to improve the precision of personal credit risk assessment, applying rough set and neural network to the credit risk scoring prediction problem in an attempt to suggest a new model with better classification accuracy. To evaluate the prediction accuracy of the model, we compare its performance with those of SVM, linear discriminate analysis, logistic regression analysis, K-nearest neighbors, classification and regression tree, neural network and PCA-NN. The experimental results show the model have a very good prediction accuracy

关键词： credit risk credit risk assessment rough set neural network 5-fold cross-validation

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