scholarly journals A Study on RB-XGBoost Algorithm-Based e-Commerce Credit Risk Assessment Model

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Weimin Yang ◽  
Lili Gao
Keyword(s):  
Risk Assessment ◽  
Credit Risk ◽  
Index System ◽  
Operating Characteristic ◽  
Evaluation Index System ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Assessment Index ◽  
Credit Risk Assessment ◽  
Assessment Index System

The current method’s e-commerce credit risk assessment is prone to poor data balance and low evaluation accuracy. An RB-XGBoost algorithm-based e-commerce credit risk assessment model is proposed in this study. The adaptive random balance (RB) method is used to sample and process the obtained data to improve the balance degree of the data. An assessment index system is constructed based on the processed data. Based on the risk evaluation index system and the XGBoost algorithm, this paper constructed an e-commerce risk assessment model and assessed the e-commerce credit risk using this model. The experimental results show that the proposed method has good data balance, a high kappa coefficient, and a large receiver operating characteristic (ROC) curve area, which can effectively improve e-commerce credit risk assessment accuracy.

Analytical model for assessing collapse risk during mountain tunnel construction

2016 ◽  
Vol 53 (2) ◽  
pp. 326-342 ◽  
Author(s):  
Guo-Hua Zhang ◽  
Yu-Yong Jiao ◽  
Li-Biao Chen ◽  
Hao Wang ◽  
Shu-Cai Li
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Index System ◽  
Assessment Model ◽  
Tunnel Construction ◽  
Assessment Index ◽  
Assessment Index System ◽  
Geological Prediction ◽  
Tunnel Collapse ◽  
Mountain Tunnel

Risk management for safety in mountain tunnel construction is of great significance. However, existing research lags behind engineering applications. In this paper, the risk of mountain tunnel collapse is used as an example to illustrate a new assessment method based on case-based reasoning, advanced geological prediction, and rough set theory. First, the risk surroundings and risk factors involved in tunnel collapse are integrated and summarized, and a risk assessment index system is established for tunnel collapse. At the same time, because the dynamic response parameters obtained by the advanced geological prediction usually indicate a typical geological structure, sensitive response parameters are introduced in the assessment index system. Advanced risk assessment can be performed for tunnel sections at a certain distance ahead of the tunnel face. Second, the major risk surroundings and the advanced geological prediction results are analyzed for the tunnel under assessment. Cases with similar attribute characteristics are selected via comparison with previous cases. Attribute reduction and calculation of weights are subsequently performed for the risk surroundings and risk factors of similar cases based on the attribute significance theory of rough sets. Finally, index screening and objective weights are applied in the fuzzy comprehensive assessment model. The results of this paper can be used to improve the theoretical level and reliability of risk assessment in tunnel safety and serve as a reference for tunnel construction.

scholarly journals Credit Risk Assessment Model for Small and Micro-Enterprises: The Case of Lithuania

Risks ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 67 ◽  
Author(s):  
Rasa Kanapickiene ◽  
Renatas Spicas
Keyword(s):  
Risk Assessment ◽  
Credit Risk ◽  
Trade Credit ◽  
Assessment Model ◽  
Financial Ratios ◽  
Risk Assessment Model ◽  
Credit Risk Assessment ◽  
Financial Variables ◽  
The Empirical Analysis ◽  
Micro Enterprises

In this research, trade credit is analysed form a seller (supplier) perspective. Trade credit allows the supplier to increase sales and profits but creates the risk that the customer will not pay, and at the same time increases the risk of the supplier’s insolvency. If the supplier is a small or micro-enterprise (SMiE), it is usually an issue of human and technical resources. Therefore, when dealing with these issues, the supplier needs a high accuracy but simple and highly interpretable trade credit risk assessment model that allows for assessing the risk of insolvency of buyers (who are usually SMiE). The aim of the research is to create a statistical enterprise trade credit risk assessment (ETCRA) model for Lithuanian small and micro-enterprises (SMiE). In the empirical analysis, the financial and non-financial data of 734 small and micro-sized enterprises in the period of 2010–2012 were chosen as the samples. Based on the logistic regression, the ETCRA model was developed using financial and non-financial variables. In the ETCRA model, the enterprise’s financial performance is assessed from different perspectives: profitability, liquidity, solvency, and activity. Varied model variants have been created using (i) only financial ratios and (ii) financial ratios and non-financial variables. Moreover, the inclusion of non-financial variables in the model does not substantially improve the characteristics of the model. This means that the models that use only financial ratios can be used in practice, and the models that include non-financial variables can also be used. The designed models can be used by suppliers when making decisions of granting a trade credit for small or micro-enterprises.

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