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Financial product real time recommendation method based on random forest algorithm

A technology of random forest algorithm and financial products, applied in finance, computing, instruments, etc., can solve problems such as low success rate, time-consuming and laborious, manual establishment, etc., and achieve high timeliness, high data availability, and high prediction hit rate Effect

Inactive Publication Date: 2017-12-22
广东奡风科技股份有限公司
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Problems solved by technology

The traditional method of screening and marketing customers through hard indicators usually requires manual establishment of a large and complex rule base, which is time-consuming and laborious, and the success rate is not high

Method used

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  • Financial product real time recommendation method based on random forest algorithm

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Embodiment Construction

[0018] The embodiments of the present invention will be described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and the scope of protection of the present invention is not limited to the following embodiments.

[0019] This embodiment includes the following steps:

[0020] S1) Analyze and organize the user's historical transaction data;

[0021] S2) Analyze and organize the basic characteristic data of users;

[0022] S3) Integrate the user's historical transaction data and basic feature data into a wide feature table;

[0023] S4) Use the random forest algorithm to establish a prediction model for the user characteristics obtained in S3);

[0024] S5) For new customers or existing customers, input their attributes into the model, and the model can predict the products they are most likely to buy in real time.

[0025] The method of S3) integrating the user's historical transaction data and basic feature d...

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Abstract

The invention discloses a financial product real time recommendation method based on a random forest algorithm. The financial product real time recommendation method based on the random forest algorithm comprises steps of analyzing user history transaction data and user characteristic data, constructing a training set and a testing set for the history transaction data and user characteristic data, using the random forest algorithm to set up a prediction model related to the financial product and performing prediction on the financial product that a user interests in. The financial product real time recommendation method based on the random forest algorithm uses a random forest to perform financial product recommendation, and compared with the prior art, the financial product real time recommendation method is fast in speed, less in parameters and good in effect and effectively improves sales efficiency and accuracy.

Description

technical field [0001] The invention relates to the field of prediction and recommendation, in particular to a real-time recommendation method for financial products. Background technique [0002] With the rapid growth of the types and quantities of bank financial wealth management products, bank sales tasks have become arduous and complicated. How to effectively recommend financial products to potential users is one of the main goals of improving marketing effectiveness. The traditional method of screening and marketing customers through hard indicators usually requires manual establishment of a large and complex rule base, which is time-consuming and laborious, and the success rate is not high. The invention uses the random forest method to model the user's transaction history and characteristics, and then recommends financial products for the user. The recommendation method constructed by the new technology has the characteristics of fast speed, few parameters, and good...

Claims

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Application Information

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IPC IPC(8): G06Q30/06G06Q40/04
CPCG06Q30/0631G06Q40/04
Inventor 陈涛黄卓凡张志聪李笋林志广
Owner 广东奡风科技股份有限公司
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