Bank intelligent question-answering system based on natural language processing and using method thereof

Abstract

The invention discloses a bank intelligent question-answering system based on natural language processing and a using method thereof. The method comprises the following steps: S1, collecting data information; S2, importing data information: encoding the collected business scene content information and non-business scene content information and importing the encoded information into a database module, wherein the database module stores the information; S3, judging the business scene content and the non-business scene content: discriminating whether the question of the customer belongs to the business scene content or not, matching a corresponding answer to the question belonging to the business scene content through a database module, and informing the customers. Based on specific information of products such as bank financing and funds, encyclopedic question and answer contents of banks and a daily communication corpus, through expert rule matching, natural language processing and a machine learning algorithm, questions of customers are accurately classified and matched, and corresponding answers are given.

Description

technical field [0001] The invention relates to the technical field of intelligent question answering systems, in particular to a bank intelligent question answering system based on natural language processing and a method for using the same. Background technique [0002] With the development of mobile Internet, big data and artificial intelligence, the Internet has entered a new era. This new era is rapidly changing the traditional human society, and it is also giving the traditional banking industry, especially the traditional banking industry centered on tellers and managers. The banking service model has brought a great impact. The application of artificial intelligence is becoming more and more widespread. Artificial intelligence technologies such as speech recognition and natural language processing have begun to be widely used in banking customer service, marketing and customer acquisition, which has greatly improved customer experience and improved work efficiency. ...

AI Technical Summary

Problems solved by technology

[0003] However, first of all, the business of traditional bank outlets is mainly concentrated on the counter. Due to the large business volume, the main energy of the tellers is limited to the counter business. They cannot understand the deep-seated needs of customers in a timely and accurate manner, and it is difficult to provide professional consultation. There are some shortcomings. Secondly, the traditional bank branch business needs to call customer service and wait in line. The steps are cumbersome and the operation is troublesome, which causes customers to queue up and reduces work efficiency.

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