The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The parameters of support vector machine (SVM) are crucial to the model’s classification performance. Aiming at the randomicity of selecting the parameters in SVM, this paper constructed a PSO-SVM model by using particle swarm optimization (PSO) to search the parameters of SVM. The model was used for personal credit scoring in commercial banks and particles’ fitness function was used to control the...
In the background of huge information integration and connection in information science, understanding of the whole world has become one of the most important requirements. In order to gain a comprehensive understanding of individuals, this paper proposed person-oriented modeling methodology to construct personal virtual image which consists of personal comprehensive information, event, task and interactive...
With the rapid development of China's consumer credit market, personal credit scoring has attracted more and more attention. And a variety of statistical and artificial intelligence methods have been used in personal credit scoring. This paper presents a multiple classifier fusion method, namely using relevant theory and methods to combine single classifiers. This is for making full use of the complementary...
We propose Fuzzy ART in personal credit area to the problem which can't handle discrete variables and continuous variables together and compared the outputs with logistic regression, linear programming and the BP neural network model results. The empirical result indicates that the model of Fuzzy ART category has less error II and possesses better applicable for commercial banks.
In order to improve the robustness and accuracy of the credit evaluation model, we study on individual credit risk, select a statistical method of Logistic regression and a non-statistical method of neural network BP algorithm, which are most frequently used methods by domestic and foreign banks. Furthermore, we separately improve these two methods to some degrees, using Clementine tools to build...
Personal Credit Scoring is of great significance for commercial banks to circumvent credit consumption, the original BP algorithm's convergence rate is slow, learning precision is low, the training process is easy to fall into local minimum, this paper presents an improved algorithm with variable learning rate based on BP algorithm, and applied to simulate personal credit scoring. After comparing...
Aiming at the insufficiencies of BP neural network, this paper established a hybrid neural network based on the combination of GA and BP algorithms. The hybrid algorithm made fully use of GA's global searching to improve the learning ability of neural network with the combination of BP. The model was used in personal credit scoring in commercial banks. Compared with single BP neural network, the training...
Personal credit scoring plays an important role for commercial banks to keep away from consumer credit risks. This paper used neural networks for personal credit scoring and used two evolutional algorithms of genetic algorithm (GA) and particle swarm optimization (PSO) to train the networks to construct a GA neural network and a PSO neural network respectively. The two neural networks were used to...
In order to fulfill the commitment that the Chinese government promised when China joined the WTO, the banking industry of China will allow foreign capital to begin having a share in all banking business at the end of 2006. It is significant for Chinese banks to develop credit card services to compete with foreign capitals. On the other hand, it is urgent for them to improve their ability to control...
The parameters of support vector machine (SVM) are crucial to the model's classification performance. Aiming at the randomicity of selecting the parameters in SVM, this paper presents a method to optimize the parameters of SVM by using genetic algorithm (GA). Using GA's global search to optimize the parameters of SVM and using the chromosome's fitness function to control the type II error rate in...
With the idea of combining forecasts, this paper presents a new approach by combining multi-linear regression and logistic with RBF network, and applies it in the area of personal credit scoring. The results indicate that the new technique is more accurate than either of the individual technique, especially in avoiding recognizing the bad applicants as good ones.
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.