Enterprise financing demand intensity evaluation method and system

By conducting significance analysis and regression model prediction on the company's multi-dimensional data, the intensity of financing demand is determined, which solves the problem of difficulty in quantifying financing demand in existing technologies, achieves accurate quantification and personalized evaluation, and improves the accuracy and efficiency of financial services.

CN120654928APending Publication Date: 2025-09-16CHENGDU JIAOZI SHUQI TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202510640982.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-19
Publication Date
2025-09-16

AI Technical Summary

Technical Problem

Existing technologies make it difficult to accurately quantify the intensity of a company's financing needs, resulting in inaccurate matching of financial products, serious waste of marketing resources, and a lack of modeling mechanisms for identifying financing intentions.

Method used

By obtaining the company's multi-dimensional basic data and historical financing demand data, conducting significance analysis, determining the field weight factors of key fields, using the trained regression model to predict the company's demand intensity, and obtaining an accurate financing demand intensity score through weighted correction.

Benefits of technology

It achieves accurate quantification of the intensity of corporate financing needs, provides a reliable basis for the intelligent recommendation system, supports dynamic optimization and continuous iteration, and improves marketing efficiency and financial resource allocation capabilities.

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Abstract

The invention discloses an enterprise financing demand intensity evaluation method and system, and the method comprises the steps: firstly obtaining the multi-dimensional basic data and historical financing demand data of a to-be-evaluated enterprise; secondly, performing significance analysis on feature fields in the historical financing demand data, and determining field weight factors of key fields related to the financing demand according to an analysis result; afterwards, multi-dimensional basic data corresponding to a to-be-evaluated enterprise is input into various trained regression models, prediction results of all the regression models are fused to accurately quantify the demand intensity of the to-be-evaluated enterprise, and an initial demand intensity score corresponding to the to-be-evaluated enterprise is obtained. And finally, correcting the initial demand intensity score through the field weight factor of each key field of the enterprise, so that the obtained financing demand intensity has objectivity and can reflect the individual difference of the enterprise, thereby accurately quantifying the financing demand intensity degree of the enterprise and providing a reliable recommendation basis for an intelligent recommendation system.
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