Limit model training method and device, limit assessment method and device, equipment and medium

A model training and quota technology, which is applied in the fields of instruments, finance, and data processing applications, can solve problems such as low integrity of user data, difficulty in obtaining users, and one-sided asset status

Pending Publication Date: 2019-07-26
PING AN TECH (SHENZHEN) CO LTD
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AI Technical Summary

Problems solved by technology

Among them, the pre-credit line model is usually modeled based on the basic information of the user and the user's asset situation. However, it is difficult to obtain the asset situation

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  • Limit model training method and device, limit assessment method and device, equipment and medium
  • Limit model training method and device, limit assessment method and device, equipment and medium

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Embodiment Construction

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative work all belong to the protection scope of the present invention.

[0044] The quota model training method provided by the embodiment of the present invention can be applied in such as figure 1 In the application environment, the quota model training method is applied in the server, by obtaining the original user data of authorized users in the database, and determining the life stage category, repayment ability level and consumption ability level through the original user data, and marking and Training to obtain the pre-credit ...

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Abstract

The invention discloses a limit model model training method, a limiting assessment method and device, equipment and a medium. The limit model training method comprises the following steps: screening original user data, and obtaining basic user data meeting a training standard, wherein the basic user data comprises a credit line, basic information data, basic asset data and basic consumption data;preprocessing the basic information data to obtain a corresponding life stage category; preprocessing the basic asset data to obtain a repayment capability level corresponding to the basic user data;preprocessing the basic consumption data to obtain a consumption capability level corresponding to the basic user data; marking the credit line, the life stage category, the repayment capability leveland the consumption capability level of the basic user data to obtain training data; training the training data by adopting a GBDT algorithm to obtain a pre-granted credit line model, and solving theproblem that the pre-granted credit line obtained through the pre-granted credit line model is inaccurate.

Description

technical field [0001] The present invention relates to the field of intelligent decision-making, in particular to a quota model training method, quota evaluation method, device, equipment and medium. Background technique [0002] At present, major banks conduct evaluations based on personal information, obtain a pre-credit line (that is, the maximum credit line) and give feedback to users, and users can apply for business based on the pre-credit line. At present, the industry usually evaluates personal information through a pre-credit model to obtain a pre-credit line for users' micro-loan pre-credit lines. Among them, the pre-credit line model is usually modeled based on the basic information of the user and the user's asset situation. However, it is difficult to obtain the asset situation of most users, or the obtained asset situation is relatively one-sided, resulting in low user data integrity. The pre-credit line obtained by the pre-credit line model is not accurate. ...

Claims

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Application Information

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IPC IPC(8): G06Q40/02
CPCG06Q40/03
Inventor 王睿之
Owner PING AN TECH (SHENZHEN) CO LTD
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