Financial lending demand prediction method and system based on network big data

Abstract

The embodiment of the invention provides a financial lending demand prediction method and system based on network big data, and the method comprises the steps: obtaining the identification informationof a to-be-predicted target, wherein the identification information at least comprises the name and identity recognition number of a lending applicant; according to the identification information, obtaining a borrowing record of the to-be-predicted target from a preset network big database; inputting the borrowing and lending record of the to-be-predicted target into a trained borrowing and lending demand prediction model to obtain a borrowing and lending demand prediction result of the to-be-predicted target, wherein the trained borrowing and lending demand prediction model is obtained by training a plurality of borrowing and lending records with borrowing and lending probability marks. A borrowing and lending record of the to-be-predicted object is obtained through the network big database, and a prediction result of the to-be-predicted object is output by using the trained borrowing and lending demand prediction model with the borrowing and lending record as input. The prediction result is objective and accurate, clear guidance can be provided for precise marketing of the borrowing and lending platform, and the conversion rate is greatly increased.

Description

technical field [0001] The present invention relates to the technical field of big data prediction, and more specifically, to a method and system for predicting financial loan demand based on network big data. Background technique [0002] With the development of modern network technology and financial lending, various lending businesses are gradually shifting from offline to online. The same is true for person-to-person (P2P) lending business, and many online P2P lending platforms have emerged as the times require. In order to accurately invest funds, each lending platform needs to place various advertisements on various channels in order to achieve a higher conversion rate. [0003] At present, the advertising and marketing of financial lending platforms are generally placed through various popular software and embedded in the content they operate, such as text, pictures or videos. However, this method cannot accurately obtain the clicks of potential customers, and the c...

AI Technical Summary

Problems solved by technology

However, this method cannot accurately obtain the clicks of potential customers, and the conversion rate is often low

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