The application relates to an insurance product intelligent matching and dynamic optimization recommendation method and
system, which comprises the following steps: constructing a user panoramic portrait by integrating user static attributes, existing insurance policies and dynamic life cycle data; calculating the current guarantee value of each
risk category based on the existing insurance policies in the portrait, calling a predefined
risk model to generate a guarantee gap in combination with
dynamic data; simultaneously, analyzing insurance product clauses by using
natural language processing to form structured
feature data and build a product
knowledge graph; according to the guarantee gap, the user static attributes and the
knowledge graph, calculating the matching
score of candidate products by a multi-objective matching
algorithm to generate a ranked recommendation
list; collecting user interaction behavior data, dynamically adjusting the matching
algorithm weight and feeding back optimization. The application realizes personalized intelligent matching and dynamic optimization of insurance products, and improves the recommendation accuracy and
user satisfaction through data driving and real-time feedback.