Credit risk control model generation method, credit evaluation method and system, machine readable medium and equipment

A technology for model generation and credit, applied in the field of credit risk control, which can solve the problems of lower-than-expected model effect, improved prediction ability, and tedious manual parameter adjustment.

Pending Publication Date: 2020-08-21
北京云从科技有限公司
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Problems solved by technology

Therefore, the scorecard model has strong requirements for the individual predictive ability of each input feature, and cannot make full use of the combination of some weak features to improve the predictive ability
[0006] These two defects have led to th

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  • Credit risk control model generation method, credit evaluation method and system, machine readable medium and equipment
  • Credit risk control model generation method, credit evaluation method and system, machine readable medium and equipment
  • Credit risk control model generation method, credit evaluation method and system, machine readable medium and equipment

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[0059] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

[0060]It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic ideas of the present invention, and only the components related to the present invention are shown in the diagrams rather than the number, shape and shape of components...

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Abstract

The invention provides a credit risk control model generation method. The method comprises the steps of obtaining one or more combined features corresponding to original attribute data of a credit business object; determining segmentation points and segmentation intervals according to the feature conditions of the combined features; determining a new feature condition according to the segmentationpoint and the segmentation interval; and performing training according to the combined features and new feature conditions corresponding to the combined features to obtain a credit risk control model. According to the credit risk control model for generating the second-order feature combination score card based on the gradient boosting tree, business personnel can clearly master details in the decision process of the model and can introduce business knowledge to check and finely adjust each detail, so that the requirement of credit risk control business for model interpretability is met.

Description

technical field [0001] The present invention relates to the field of credit risk control, in particular to a method for generating a credit risk control model, a credit evaluation method, a system, a machine-readable medium and equipment. Background technique [0002] In the field of credit risk control, the traditional scorecard model based on logistic regression is traditionally adopted due to business requirements for model interpretation. In the training phase, each feature column of the input data is binned, and the score of each binning interval is calculated through the training data to obtain a score card. In the prediction stage, the scores will be calculated by comparing each column of the input data against the scorecard, and finally summed to obtain the predicted credit score. [0003] However, since logistic regression is a linear model, the traditional scorecard model suffers from two major flaws. [0004] First of all, the impact of certain variables on cred...

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Application Information

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IPC IPC(8): G06Q40/02G06K9/62
CPCG06Q40/03G06F18/24323
Inventor 周曦姚志强陈琳卢智聪赵礼悦曹文飞张博宣翁谦张旭
Owner 北京云从科技有限公司
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