This application belongs to the field of financial technology and is applied to the field of insurance pricing guidance in financial business. It relates to a method and related equipment for recommending call leads in auto insurance business based on NLP. The method includes: recognizing recorded human-computer dialogue; performing text-to-
text processing to dynamically acquire dialogue text data in real time; using NLP (
Natural Language Processing) to process the dialogue text data; obtaining customer intent clustering results; recognizing the dialogue intent of the calling customer; and selecting the corresponding call lead based on the dialogue intent and assigning it to the next agent after the current human-computer dialogue, thus completing the call lead recommendation for the agent. This application uses an ASR+Kafka+
dynamic data stream acquisition framework+NLP approach, enabling human customer service representatives to quickly locate the dialogue intent of customers previously served by the AI voice service assistant when faced with lengthy AI intelligent outbound call
data records. This improves the efficiency of human agents and ensures a good call experience for customers.