Hybrid CRO Based FLANN for Financial Credit Risk Forecasting

2014 ◽  
pp. 57-65
Author(s):  
S. R. Sahu ◽  
D. P. Kanungo ◽  
H. S. Behera
Keyword(s):  
Credit Risk ◽  
Risk Forecasting ◽  
Financial Credit

Mining Cross Features for Financial Credit Risk Assessment

2021 ◽  
Author(s):  
Qiang Liu ◽  
Zhaocheng Liu ◽  
Haoli Zhang ◽  
Yuntian Chen ◽  
Jun Zhu
Keyword(s):  
Risk Assessment ◽  
Credit Risk ◽  
Credit Risk Assessment ◽  
Financial Credit

scholarly journals Financial Credit Risk Evaluation Based on Core Enterprise Supply Chains

2018 ◽  
Vol 10 (10) ◽  
pp. 3699 ◽  
Author(s):  
WeiMing Mou ◽  
Wing-Keung Wong ◽  
Michael McAleer
Keyword(s):  
Supply Chain ◽  
Credit Risk ◽  
Supply Chains ◽  
Risk Evaluation ◽  
Operating Conditions ◽  
The Core ◽  
Supply Chain Finance ◽  
Enterprise Credit ◽  
Financial Credit ◽  
Core Enterprise

Supply chain finance has broken through traditional credit modes and advanced rapidly as a creative financial business discipline. Core enterprises have played a critical role in the credit enhancement of supply chain finance. Through the analysis of core enterprise credit risks in supply chain finance, by means of a ‘fuzzy analytical hierarchy process’ (FAHP), the paper constructs a supply chain financial credit risk evaluation system, making quantitative measurements and evaluation of core enterprise credit risk. This enables enterprises to take measures to control credit risk, thereby promoting the healthy development of supply chain finance. The examination of core enterprise supply chains suggests that a unified information file should be collected based on the core enterprise, including the operating conditions, asset status, industry status, credit record, effective information to the database, collecting related data upstream and downstream of the archives around the core enterprise, developing a data information system, electronic data information, and updating the database accurately using the latest information that might be available. Moreover, supply chain finance and modern information technology should be integrated to establish the sharing of information resources and realize the exchange of information flows, capital flows, and logistics between banks. This should reduce a variety of risks and improve the efficiency and effectiveness of supply chain finance.

scholarly journals Financial Credit Risk Control Strategy Based on Weighted Random Forest Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Guo Yangyudongnanxin
Keyword(s):  
Risk Assessment ◽  
Random Forest ◽  
Credit Risk ◽  
Control Strategy ◽  
Control Strategies ◽  
Risk Control ◽  
Evaluation Index System ◽  
Risk Level ◽  
Random Forest Algorithm ◽  
Financial Credit

In order to improve the effectiveness of financial credit risk control, a financial credit risk control strategy based on weighted random forest algorithm is proposed. The weighted random forest algorithm is used to classify the financial credit risk data, construct the evaluation index system, and use the analytic hierarchy process to evaluate the financial credit risk level. The targeted risk control strategies are taken according to different risk assessment results. We compared the proposed method with two other methods, and the experimental results show that the proposed method has higher classification accuracy of financial credit data and the risk assessment threshold is basically consistent with the actual results.

LDC Credit-risk Forecasting and Banker Judgement

2001 ◽  
Vol 28 (3-4) ◽  
pp. 447-464 ◽  
Author(s):  
R. A. Somerville ◽  
R. J. Taffler
Keyword(s):  
Credit Risk ◽  
Risk Forecasting

An improved SMO algorithm for financial credit risk assessment – Evidence from China’s banking

2018 ◽  
Vol 272 ◽  
pp. 314-325 ◽  
Author(s):  
Qi Zhang ◽  
Jue Wang ◽  
Aiguo Lu ◽  
Shouyang Wang ◽  
Jian Ma
Keyword(s):  
Risk Assessment ◽  
Credit Risk ◽  
Credit Risk Assessment ◽  
Financial Credit ◽  
Smo Algorithm
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