Method and device for training prediction model for predicting customer transaction behavior

Abstract

The invention provides a method and device for training a prediction model used for predicting customer transaction behaviors, relates to the technical field of artificial intelligence, and can be applied to the technical field of finance. The method comprises the following steps: determining a plurality of pre-selected feature types according to a customer sample data set, wherein the customer sample data set comprises customer basic information data and telephone consultation information data of a customer for a target product; determining a plurality of target feature types from the plurality of pre-selected feature types, wherein the target feature types are data types of which the contribution degree to the customer purchase behavior result is greater than a preset contribution degree threshold value and the correlation between every two target feature types is smaller than a preset correlation threshold value; screening out data related to the target feature type from the customer sample data set to generate a target training set; and training a preset algorithm by using the target training set to generate a prediction model.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, and more specifically, to a method and device for training a prediction model for predicting customer transaction behaviors, electronic equipment, computer-readable storage media, and computer program products. Background technique [0002] Data mining can dig out the information they need from a large amount of customer historical data. [0003] In the process of realizing the disclosed concept, the inventors found that there are at least the following problems in related technologies: most financial professionals have different defects when actually analyzing and mining these customer historical data; When promoting a product, it only considers the market share of the product in a certain region, and does not analyze the economic development status of the region, the income status of the people, and the differences in the basic characteristics of the customers who purch...

AI Technical Summary

Problems solved by technology

[0003] In the process of realizing the disclosed concept, the inventors found that there are at least the following problems in related technologies: most financial professionals have different defects when actually analyzing and mining these customer historical data; When promoting a product, it only considers the market share of the product in a certain region, and does not analyze the economic development status of the region, the income status of the people, and the differences in the basic characteristics of the customers who purchase the product; at the same time, when doing These data analysis and mining work are not performed by data mining professionals, but mainly rely on the subjective judgment of some financial professionals

Even if some financial institutions introduce data mining systems, they only do some simple data analysis work and do not conduct in-depth mining of customer historical data, making it difficult to achieve precise marketing

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