Financial product recommendation device and method and computer readable storage medium

Abstract

The invention discloses a financial product recommendation device. The financial product recommendation device comprises a memory and a processor; a financial product recommendation program which canbe operated on the processor is stored on the memory; and the program is executed by the processor to realize the following steps of: extracting a matter feature corresponding to a target customer from a matter information table; calculating satisfaction degree levels, for held financial products, of the target customer according to the matter feature of the target customer and a preset classification model; selecting to-be-recommended financial products for the target customer according to product data of the held financial products of the target customer and the satisfaction degree levels for the held financial products; obtaining a contact medium corresponding to each matter, in the matter information table, of the target customer, and predicting common contact media of the customer according to the obtained contact media; and recommending the financial products to the target customer through the common contact media. The invention furthermore discloses a financial product recommendation method and a computer readable storage medium. According to the financial product recommendation device and method and the computer readable storage medium, the financial product recommendationsuccess rate is improved.

Description

Technical field [0001] The present invention relates to the field of information processing technology, in particular to a financial product recommendation device, method and computer readable storage medium. Background technique [0002] At present, most of the marketing programs adopted by banks are based on the traditional marketing system, which collects statistics on customer transaction data, screens out a certain number of customers as potential customers, and recommends financial services designated by the bank to these customers through phone calls or text messages. With the development of the financial industry and the Internet industry, there are more and more types of financial products, including funds, wealth management, precious metals, insurance and other products, and each type of product contains several products. As a result, for customers, faced with a large number of financial products, it is difficult to choose products that are suitable for them. For banks,...

AI Technical Summary

Problems solved by technology

[0002] At present, the marketing plan adopted by most banks is based on the traditional marketing system, which counts the transaction data of customers, screens out a certain number of customers as potential customers, and recommends the financial services designated by the bank to these customers by phone or text message. products, and with the development of the financial industry and the Internet industry, there are more and more types of financial products, including funds, wealth management, precious metals, insurance and other products, and each type of product contains several products, which is As a result, for customers, facing a large number of financial products, it is difficult to choose a product that suits them. For banks, due to lack of manpower and other reasons, it is impossible to fully promote products, and generally choose a small number of financial products. The sales of popular financial products. In addition, this sales model is not targeted. It is often based on the business rules of the product to select some customers in batches for batch marketing. There is no in-depth mining of customer transaction behaviors to carry out personalized and precise marketing.

[0003] To sum up, for the existing marketing model, due to the existence of the above-mentioned various defects, the success rate of recommending financial products to customers is low

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