Real-time recommendation system and method of financial products of banks based on Naive Bayesian classification

Abstract

The invention discloses a real-time recommendation system and method of financial products of banks based on Naive Bayesian classification wherein the method comprises: acquiring the data of a bank business system, a peripheral system, and an internet / mobile internet; processing and storing the data in a basic database; conducting characteristic processing to the data attributes of the customers in a certain area; converting for data characteristics to develop a characteristic database; classifying the data in the characteristic database as a training data set and a verification data set which are used respectively for the training and estimating of a Naive Bayesian classification algorithm model; obtaining a model base after several times of iteration; identifying the characteristics of customers and in combination with the Naive Bayesian classification algorithm model base, matching the customers with the financial products they are mostly likely to purchase in real time; and recommending to the customers the financial products that are forecasted and matched by the models. The recommendation system and method of the invention are capable of helping customers to find out suitable products, therefore, increasing the user experience and the bonding effect of the customers to the financial products, lifting up the transferring rate of the products and making the bank more competitive.

Description

technical field [0001] The invention relates to a real-time recommendation system and method for bank financial products, in particular to a real-time recommendation system and method for bank financial products based on naive Bayesian classification. Background technique [0002] The development of technologies such as the Internet, big data, and artificial intelligence has changed the competitive landscape of the banking industry; the pursuit of the ultimate user experience and the emphasis on data-driven operations have become new features. At present, the financial product marketing of most banks is based on the traditional operational marketing system. The general business process is to first conduct statistical analysis on customer, product, transaction and other data, and then combine business rules to select a group of customers, and then pass Call or SMS to promote a product designated by the bank. This marketing model can no longer quickly adapt to market changes ...

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Problems solved by technology

[0008] The present invention proposes a real-time recommendation system and method for bank financial products based on naive Bayesian classification, which solves the problem of "product information overload", marketing response delay and "long tail products" existing in the bank's traditional marketing system and traditional marketing model defect

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