Results 281 to 290 of about 9,973,528 (335)
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Corporate social responsibility and credit risk
Finance Research Letters, 2020We study the effects of corporate social responsibility on credit risk for U.S. and European firms over the period 2003 to 2018. Differentiating between the various facets of corporate social responsibility shows that only environmental aspects reduce ...
C. Bannier, Yannik Bofinger, Björn Rock
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Information Sciences, 2020
The misclassification of loan applicants by credit scoring model is one of the main factors causing the loss of investors’ profits in P2P lending. Class imbalance of credit data is a main factor that affects classification performance of the model.
Kun Niu +3 more
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The misclassification of loan applicants by credit scoring model is one of the main factors causing the loss of investors’ profits in P2P lending. Class imbalance of credit data is a main factor that affects classification performance of the model.
Kun Niu +3 more
semanticscholar +1 more source
Applied Soft Computing, 2020
With the rapid growth of the P2P online loan industry in the “Three Rurals” (agriculture, rural areas, and farmers) sector, it is imperative to manage the borrowing risk of borrowers in the rural areas.
Congjun Rao +3 more
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With the rapid growth of the P2P online loan industry in the “Three Rurals” (agriculture, rural areas, and farmers) sector, it is imperative to manage the borrowing risk of borrowers in the rural areas.
Congjun Rao +3 more
semanticscholar +1 more source
Evaluating the credit risk of SMEs using legal judgments
Decision Support Systems, 2020Loan application assessments of small and medium-sized enterprises (SMEs) are difficult because of information asymmetry. To mitigate the information asymmetry, this paper focuses on information found in legal judgments involving the company and its ...
Changye Yin +3 more
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Liquidity risk, credit risk and stability in Islamic and conventional banks
Research In International Business and Finance, 2019The aim of this paper is to provide a thorough assessment of Islamic banks’ (IBs) liquidity risk compared to conventional banks (CBs). We firstly investigate the relationship between liquidity and credit risk. Employing a simultaneous structural equation
M. Hassan, Ashraf Khan, A. Paltrinieri
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Threshold effects of liquidity risk and credit risk on bank stability in the MENA region
Journal of Policy Modeling, 2020This paper studies the relationships between both liquidity and credit risks on bank stability for a panel data set of 75 conventional banks belonging to 11 countries of the MENA region observed during the period 1999–2017.
N. Djebali, Khemais Zaghdoudi
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Mining Semantic Soft Factors for Credit Risk Evaluation in Peer-to-Peer Lending
Journal of Management Information Systems, 2020While Peer-to-Peer (P2P) lending is rapidly growing, it is also accompanied by high credit risk due to information asymmetry. Besides conventional hard information, soft information also enters into the lending decision process.
Zhao Wang +3 more
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Cluster Analysis for mixed data: An application to credit risk evaluation
, 2020Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative ...
G. Caruso +3 more
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2007
Abstract Part I provided a conceptual overview of the scheme of the book. This involved a series of five structures. The first is the introduction of varied risks into the financial system in the form of credit risk; this is the subject of section 2.1 of this chapter. The remaining four structures are the four types of financial position,
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Abstract Part I provided a conceptual overview of the scheme of the book. This involved a series of five structures. The first is the introduction of varied risks into the financial system in the form of credit risk; this is the subject of section 2.1 of this chapter. The remaining four structures are the four types of financial position,
openaire +2 more sources
Integration of unsupervised and supervised machine learning algorithms for credit risk assessment
Expert systems with applications, 2019For the sake of credit risk assessment, credit scoring has become a critical tool to discriminate “bad” applicants from “good” applicants for financial institutions.
Wang Bao, Lianju Ning, K. Yue
semanticscholar +1 more source