Financial early warning of non–life insurance company based on RBF neural network optimized by genetic algorithm. (29th September 2017)

• Record Type: Journal Article
• Authors: Yan, Chun; Wang, Lin; Liu, Wei; Qi, Man
• Other Names: Barbosa Jorge G. guestEditor.; Jeannot Emmanuel guestEditor.; Li Maozhen guestEditor.
• Is Part Of: Concurrency and computation. Volume 30:Number 23(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-09-29
• Subjects: entropy method -- genetic algorithm -- RBF neural network -- risk early warning; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4343
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Due to the characteristic of risk diversification in non–life insurance industry, the company's financial risk early warning is very important. In order to reasonably predict the financial status of non–life insurance company, the evaluation system of financial risk indicator is constructed from the aspects of solvency, profitability, and growth ability. Taking data of non–life insurance companies in past years as sample, the evaluation indicators are weighted objectively using the entropy method. The RBF neural network model is improved with the genetic algorithm, and the early warning model is established. The empirical results show that the prediction accurate rate of RBF neural network model based on genetic algorithm is increased.