基于BP神经网络的医保欺诈识别

医疗保险欺诈是指在参加医保的过程中，通过故意捏造、虚构事实等方法骗取医保基金或医保待遇，造成医疗保险基金损失的行为.有效地识别医保欺诈对医保基金的健康使用有重大意义.本文运用BP神经网络实现医保欺诈的主动识别，并利用Logistic回归分析对神经网络模型进行改进，降低弱因子对神经网络识别的干扰.此外，应对欺诈数据的稀缺问题，采用只取正常数据训练神经网络模拟函数曲线的模式.实证表明，该方法对医保欺诈具有较好的识别能力.

Medical Insurance Fraud Identification Based on BP Neural Network

Medical insurance fraud refers to the behavior of medical insurance fund or medical insurance coverage, which causes the loss of medical insurance fund through the method of deliberately fabricating and fictitious facts. Effective identification of health insurance fraud is of great significance to the rational use of health insurance funds. This study uses BP neural network to realize the active identification of health insurance fraud, and uses logistic regression analysis to improve the neural network model and reduce the interference of the weak factor to neural network identification. In addition, to deal with the scarce problem of fraudulent data, the model of neural network simulation function is used to train neural network. The empirical evidence shows that this method has better identification ability for health insurance fraud.