Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Credit score value determination method and device, electronic equipment and storage medium

A determination method and credit scoring technology, applied in the field of machine learning, can solve problems such as the inability to guarantee the security of customer data privacy, and achieve the effect of improving the accuracy rate, improving the risk level, and ensuring privacy and security

Pending Publication Date: 2022-04-19
INDUSTRIAL AND COMMERCIAL BANK OF CHINA
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a method for determining a credit score value and its device, electronic equipment, and a storage medium, so as to at least solve the problem in the related art of jointly training a customer credit scoring model by acquiring data from multiple institutions and improving scoring accuracy. way, technical issues that cannot guarantee the security of customer data privacy

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Credit score value determination method and device, electronic equipment and storage medium
  • Credit score value determination method and device, electronic equipment and storage medium
  • Credit score value determination method and device, electronic equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0046] According to an embodiment of the present invention, an embodiment of a method for determining a credit score value is provided. It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and , although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.

[0047] figure 1 is a flow chart of an optional method for determining a credit score value according to an embodiment of the present invention, such as figure 1 As shown, the method includes the following steps:

[0048] Step S101, based on the account ID of the target account, multiple account features of the target account are obtained to obtain a feature set, wherein each account feature corresponds to a feature value, and multiple feature values ​​are binned to obtain multiple feature bins ...

Embodiment 2

[0125] figure 2 is a schematic diagram of an optional longitudinal federal credit scoring modeling process according to an embodiment of the present invention, such as figure 2 As shown, the modeling process of longitudinal federal credit scoring includes three parts: sample identity encryption alignment, federated learning modeling and federated scoring, as follows:

[0126] The first part is data set preparation and sample identity encryption alignment. Before starting to build a federated scoring model, each federated participant, that is, each scoring agency, needs to prepare its own data set, and then seek intersection through the private set (PrivateSet Intersection, PSI) to complete the encrypted alignment of the sample identification of both parties (the original data cannot be directly transmitted), and each participant forms a data set for model training and prediction. In this embodiment, it is assumed uniformly that the rating agency A provides the binary classi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a credit score value determination method and device, electronic equipment and a storage medium, and relates to the field of machine learning, and the determination method comprises the steps: obtaining a plurality of account features of a target account based on an account identifier of the target account, obtaining a feature set, inputting the feature set to a pre-trained federal learning model, and obtaining a credit score value of the target account; the method comprises the steps of obtaining a parameter value of each account feature, performing weight coding on each account feature to obtain an evidence weight value of a feature box to which the account feature belongs, and determining a credit score value of a target account in a current scoring mechanism based on the parameter value of each account feature and the evidence weight value of the feature box to which the account feature belongs. According to the method and the device, the technical problem that the security of customer data privacy cannot be ensured in a mode of improving scoring accuracy by acquiring data of a plurality of institutions to jointly train a customer credit scoring model in related technologies is solved.

Description

technical field [0001] The present invention relates to the field of machine learning, in particular to a method for determining a credit score value and its device, electronic equipment and a storage medium. Background technique [0002] In the financial business scenario, the scorecard is a means to measure the credit risk of a customer in the form of points, and provides a decision-making basis for business application approval. Generally speaking, the higher the score on the customer's score card, the better the customer's credit and the lower the risk. [0003] In related technologies, the scorecard model is usually based on a logistic regression (Logistic Regression, LR) algorithm, which has good interpretability and robustness, and is easy to monitor and deploy. However, it is difficult to improve the accuracy of the model if only the model based on the logistic regression algorithm is used to calculate the customer's credit score. In practical applications, if you ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/02G06Q10/06G06N3/08
CPCG06N3/08G06Q10/06393G06Q40/03
Inventor 相妹
Owner INDUSTRIAL AND COMMERCIAL BANK OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products