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Credit risk prediction for small and medium enterprises utilizing adjacent enterprise data and a relational graph attention network
Wang, Jiaxing; Liu, Guoquan; Xu, Xiaobo; Xing, Xinjie - In: Journal of management science and engineering 9 (2024) 2, pp. 177-192
Credit risk prediction for small and medium enterprises (SMEs) has long posed a complex research challenge. Traditional approaches have primarily focused on enterprise-specific variables, but these models often prove inadequate when applied to SMEs with incomplete data. In this innovative study,...
Persistent link: https://www.econbiz.de/10014631875
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Clues from networks : quantifying relational risk for credit risk evaluation of SMEs
Long, Jingjing; Jiang, Cuiqing; Dimitrov, Stanko; Wang, Zhao - In: Financial innovation : FIN 8 (2022), pp. 1-41
Owing to information asymmetry, evaluating the credit risk of small- and medium-sized enterprises (SMEs) is difficult. While previous studies evaluating the credit risk of SMEs have mostly focused on intrinsic risk generated by SMEs, our study considers both intrinsic and relational risks...
Persistent link: https://www.econbiz.de/10013413115
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Impact of enterprises relationship on ML's ability to forecast SME's credit risk in SCF : a research based on complex network
Peng, Qiaosheng; Chi, Xie; Li, Jing; Zhu, You; Wang, … - In: Emerging markets, finance & trade : a journal of the … 60 (2024) 11, pp. 2594-2612
Persistent link: https://www.econbiz.de/10015049754
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Comparison of different methods of credit risk management of the commercial bank to accelerate lending activities for SME segment
Cipovova, Eva; Dlaskova, Gabriela - In: European research studies 19 (2016) 4, pp. 17-26
Persistent link: https://www.econbiz.de/10012009577
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Forecasting distress in European SME portfolios
Michala, Dimitra; Grammatikos, Theoharry; Ferreira … - 2013
We develop distress prediction models for non-financial small and medium sized enterprises (SMEs) using a dataset from eight European countries over the period 2000-2009. We examine idiosyncratic and systematic covariates and find that macro conditions and bankruptcy codes add predictive power...
Persistent link: https://www.econbiz.de/10011862221
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Credit risk early warning of small and medium-sized enterprises based on blockchain trusted data
Tong, Shekun; Zhang, Ting; Zhang, Zhigang - In: Journal of information & knowledge management : JIKM 21 (2022) 2, pp. 1-12
Persistent link: https://www.econbiz.de/10013389598
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Implications of network structure on small firms' performance : evidence from Italy
Rubino, Michele; Vitolla, Filippo - 2018
) influence small firms' performance. Since the '70s Italy has had a long history of network alliances characterized by the …
Persistent link: https://www.econbiz.de/10012105897
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Retail Credit Risk Management
Anolli, Mario (ed.); Beccalli, Elena (ed.);  … - 2013
Introducing the fundamentals of retail credit risk management, this book provides a broad and applied investigation of the related modeling theory and methods, and explores the interconnections of risk management, by focusing on retail and the constant reference to the implications of the...
Persistent link: https://www.econbiz.de/10012106304
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Measuring and managing credit risk in SMEs : a quantitative and qualitative rating model
De Noni, Ivan (contributor); Lorenzon, Antonio (contributor) - 2007
Persistent link: https://www.econbiz.de/10003783644
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A credit risk assessment model based on SVM for small and medium enterprises in supply chain finance
Zhang, Lang; Hu, Haiqing; Zhang, Dan - In: Financial innovation : FIN 1 (2015) 14, pp. 1-21
, rather than only assessing an SME’s repayment ability. The aim of this paper is to research credit risk assessment models for … improve the credit rating status in the process of SME financing. (2)By analyzing and comparing the empirical results, we find … that the SVM assessment model, on evaluating the SME credit risk, is more effective than the BP neural network assessment …
Persistent link: https://www.econbiz.de/10011541786