Insurance Product Recommendation Based on Neural Network

The development of modern insurance industry is more and more closely related to artificial intelligence, but the update of basic insurance technology is slightly slow. The existing insurance recommendation technology is often "acclimatized" in offline insurance promotion due to falling off the actual environment. In this paper, the neural network is trained to predict the possible purchase of insurance. Then based on the analytic hierarchy process (AHP), the scoring model of the insurance scheme is established according to the index parameters of the product, and users are recommended according to the scoring of the scheme. Based on this recommendation technology, insurance companies can make a balance between profitability and recommendation accuracy, and predict and recommend insurance products that are suitable for users and meet the company's profitability.