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APPLICATION OF NEURAL NETWORKS TO ASSESS THE CREDITWOR THINESS INDIVIDUALS
Lomakin Nikolay Ivanovich1, Starikova Julia Viktorovna2
1Volzhsky Polytechnic Institute (branch) of Volgograd State Technical University, Associate Professor of "Economics and Management"
2Volzhsky Polytechnic Institute (branch) of Volgograd State Technical University, Student of the Department of "Economics and Management"
1Volzhsky Polytechnic Institute (branch) of Volgograd State Technical University, Associate Professor of "Economics and Management"
2Volzhsky Polytechnic Institute (branch) of Volgograd State Technical University, Student of the Department of "Economics and Management"
Abstract
Investigates the theoretical basis for assessing the creditworthiness of borrowers using neural networks. The evaluation process is based on the creditworthiness of the borrower selection and analysis of parameters that influence the amount of credit risk. Successful application of neural networks based on their ability to carry out the processes of prediction and classification. Banks are important properties of neural networks such as the possibility of nonlinear modeling and ease of implementation.
Keywords: Neural Network Toolbox
Category: Economics
Article reference:
Application of neural networks to assess the creditwor thiness individuals // Humanities scientific researches. 2014. № 7 [Electronic journal]. URL: https://human.snauka.ru/en/2014/07/7297
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