Research on Prediction and Optimization of Vehicle Insurance Claim Frequency Based on GA-BP Neural Network
The prediction of the frequency of car insurance claims is of great significance for car insurance pricing.In recent years,with the rise of big data technology,traditional car insurance pricing models can no longer meet the increasing demand for a large amount of customer data from insurance companies.In order to improve the prediction accuracy of car insurance claim frequency,a real data of car insurance customers from a French insurance company is used,and a genetic algorithm is added to the BP neural network to compare the relevant models and select the optimal model.The research results indicate that the prediction accuracy of the genetic algorithm optimization model is significantly better than that of the BP neural net-work,and its performance in predicting the frequency of car insurance claims is better,which can effectively reduce the pricing cost of car insurance.
auto insuranceclaim frequencygenetic algorithmBP neural networkROC curve
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