A Credit Scoring Technology Based on Bayes Discriminant Analysis

2019 ◽  
Vol 09 (03) ◽  
pp. 222-231
Author(s):  
声华 周
Keyword(s):  
Discriminant Analysis ◽  
Credit Scoring ◽  
Bayes Discriminant Analysis

Regression model of assessment of customer solvency and banking risks in the process of lending

2019 ◽  
pp. 69-73
Author(s):  
Zoryna Yurynets ◽  
Rostyslav Yurynets ◽  
Nataliya Kunanets ◽  
Ivanna Myshchyshyn
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Regression Model ◽  
Likelihood Ratio ◽  
Credit Scoring ◽  
Bank Loans ◽  
Management Decisions ◽  
Computer Data ◽  
Proposed Model ◽  
Loan Risk

In the current conditions of economic development, it is important to pay attention to the study of the main types of risks, effective methods of evaluation, monitoring, analysis of banking risks. One of the main approaches to quantitatively assessing the creditworthiness of borrowers is credit scoring. The objective of credit scoring is to optimize management decisions regarding the possibility of providing bank loans. In the article, the scientific and methodological provisions concerning the formation of a regression model for assessing bank risks in the process of granting loans to borrowers has been proposed. The proposed model is based on the use of logistic regression tools, discriminant analysis with the use of expert evaluation. During the formation of a regression model, the relationship between risk factors and probable magnitude of loan risk has been established. In the course of calculations, the coefficient of the individual's solvency has been calculated. Direct computer data preparation, including the calculation of the indicators selected in the process of discriminant analysis, has been carried out in the Excel package environment, followed by their import into the STATISTICA package for analysis in the “Logistic regression” sub-module of the “Nonlinear evaluation” module. The adequacy of the constructed model has been determined using the Macfaden's likelihood ratio index. The calculated value of the Macfaden's likelihood ratio index indicates the adequacy of the constructed model. The ability to issue loans to new clients has been evaluated using a regression model. The conducted calculations show the possibility of granting a loan exclusively to the second and third clients. The offered method allows to conduct assessment of client's solvency and risk prevention at different stages of lending, facilitates the possibility to independently make informed decisions on credit servicing of clients and management of a loan portfolio, optimization of management decisions in banks. In order for a loan-based model to continue to perform its functions, it must be periodically adjusted.

Assessment of Urban Road Traffic Safety Based on Bayes Discriminant Analysis Method

2013 ◽  
Vol 639-640 ◽  
pp. 544-547
Author(s):  
Chang Ping Wen ◽  
Qing Qing Tian
Keyword(s):  
Discriminant Analysis ◽  
Traffic Safety ◽  
Evaluation Method ◽  
Road Traffic ◽  
Urban Road ◽  
Discriminant Model ◽  
Road Traffic Safety ◽  
Normal Populations ◽  
Proposed Model ◽  
Bayes Discriminant Analysis

Bayes discriminant analysis theory (BDAT) is used to create an evaluation method to determine the condition of urban road traffic safety. The resulting Bayes discriminant model (BDM) is designed to strictly adhere to BDAT. Three indexes including death ratio per ten thousand vehicles, death ratio per hundred thousand bicycles and death ratio per hundred thousand citizens are selected as the factors in the analysis of urban road traffic safety. The grade of condition of urban road traffic safety is divided into three grades that are regarded as three normal populations in Bayes discriminant analysis. Bayes discriminant functions rigorously constructed through training a set of samples are employed to compute the Bayes function values of the evaluating samples, and the maximal function value is used to judge which population the evaluating sample belongs to. The optimality of the proposed model is verified by back-substitution method. The study shows that the prediction accuracy of the proposed model is 100% and could be used in practice.

A comparison between Bayes discriminant analysis and logistic regression for prediction of debris flow in southwest Sichuan, China

Geomorphology ◽  
2013 ◽  
Vol 201 ◽  
pp. 45-51 ◽  
Author(s):  
Wenbo Xu ◽  
Shaocai Jing ◽  
Wenjuan Yu ◽  
Zhaoxian Wang ◽  
Guoping Zhang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Debris Flow ◽  
Bayes Discriminant Analysis

scholarly journals A Comparison Study on the Era of Internet Finance China Construction of Credit Scoring System Model

2020 ◽  
Vol 2 (1) ◽  
pp. 1-22
Author(s):  
Hongjun Zeng
Keyword(s):  
Discriminant Analysis ◽  
Scoring System ◽  
Business Models ◽  
Financial Institution ◽  
Credit Scoring ◽  
Explanatory Power ◽  
Internet Technology ◽  
System Model ◽  
Analysis Model ◽  
Internet Finance

At present, China's Internet finance has flourished, showing a variety of business models and operating mechanisms. Through Internet technology, financial institutions can speed up business processing and bring users a better service experience. However, there are also problems such as credit risk and user fraud, and it is urgent to improve the level of risk control through credit scoring models. Because of this, this article uses the borrower data of a Chinese financial institution from January 2017 to June 2017 as the original data, and then uses the Spearman rank correlation test to screen out the variables with reliable explanatory power from the many variables of the sample data, and then Based on the variables selected, R 3.4.3 and SPSS 23.0 were used to construct a random forest model, discriminant analysis model, and logistic regression model. In general, different models perform differently under different sample characteristics, but the discriminant analysis has been better applicable. This paper compares the judgment accuracy of these three types of models and tries to establish a more effective financial credit scoring method, to solve the problem of constructing China's credit scoring system model under the current Internet financial background.

Study on Chinese Retired Athletes Job Placement Countermeasure Based on Bayes Discriminant Analysis Classification Method

2017 ◽  
Vol 14 (1) ◽  
pp. 119-123
Author(s):  
Lingli Li
Keyword(s):  
Discriminant Analysis ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Vulnerable Groups ◽  
Chinese Society ◽  
Learning Capacity ◽  
Evaluation Approach ◽  
Senior Athletes ◽  
Very High ◽  
Bayes Discriminant Analysis

As Chinese Olympic Games, National Games these large-scale sports meetings are now behind us; retirement situation of a group of senior athletes also becomes prevalent. Therefore, the paper carries out specific research on employment situation of Chinese retired athletes. The paper investigates retired athletes’ current situations, and makes comparative analysis, finds that though Chinese retired athletes has acquired some subsidies materially, their life demands cannot be fully satisfied; evaluate on Chinese retired athletes comprehensive quality by discriminant analysis and comprehensive evaluation approach, think that Chinese athletes professional levels are very high but social skills and learning capacity in comprehensive quality are still to be improved, therefore suggest to arrange athletes of rather excellent techniques to participate in cultivation of teenager athlete; present relative opinions on Chinese future retired athletes’ allocation, which is the protection of Chinese vulnerable groups in the background of harmonious development of Chinese socialism so that Chinese society can balanced, coordinated and sustainable move forward.

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