A credit scoring card development method based on machine learning

A credit scoring and machine learning technology, applied in instruments, data processing applications, finance, etc., can solve problems such as audit difficulties and low labor efficiency

Inactive Publication Date: 2019-04-16
ZHEJIANG UNIV OF TECH
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  • Claims
  • Application Information

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Problems solved by technology

[0003] In order to overcome the deficiencies of the prior art, the present invention proposes a credit score card development method based on machine learning, using machine learning, vintage analysis, and logis

Method used

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  • A credit scoring card development method based on machine learning
  • A credit scoring card development method based on machine learning
  • A credit scoring card development method based on machine learning

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[0093] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0094] Reference figure 1 , A score card development method based on machine learning, which can solve the problem of difficult selection of high-dimensional data features while solving the low efficiency of manual review. The present invention can be applied to the development of Internet financial score cards. Such as figure 1 In the scene shown. The optimization method designed for the problem mainly includes the following steps:

[0095] 1) Definition of target variable

[0096] According to vintage analysis, observe the trend of average overdue in each month and determine the time span of the performance window. Define a user whose overdue days are less than 3 days during the performance period as a "good user", define a user whose overdue days are more than 30 days as a "bad user", and define a user whose overdue days are more than 3 days and less than 30 ...

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Abstract

The invention discloses a scoring card development method based on machine learning. The scoring card development method comprises the following steps: (1) defining a label of a target user accordingto vinage analysis; (2) integrating various data sources to obtain final data; (3) carrying out exploratory analysis and data cleaning on the data; (4) using an optimized chi-square binning method tobind the cleaned data; (5) carrying out variable screening on the box-separated variables; (6) constructing a logistic regression model; (7) evaluating the model; And (8) converting the model output target user default probability into a score. According to the method, machine learning, vinage analysis and a logistic regression model are utilized, and the problem is converted from manual solutionto machine solution according to the difficulties of low manual efficiency, difficulty in auditing and the like in the big data era.

Description

technical field [0001] The present invention relates to a kind of Internet finance, machine learning, vintage analysis, logistics regression model, computer application field, what especially relate to is a kind of credit scoring card development method based on machine learning; Background technique [0002] With the rapid development of credit scoring models and the credit industry, there are various methods for building models, from the traditional statistical regression method at the beginning to the emerging deep learning algorithm today, and the application of the model has gradually shifted from predicting the probability of default to various aspects of credit. Life cycle penetration, such as scoring A card, B card after loan, and subsequent C card. However, the scorecards of general financial companies are still traditional expert-type scorecards, which rely on experienced experts to formulate rules to distinguish good and bad users. This method is still effective w...

Claims

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Application Information

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IPC IPC(8): G06Q40/02
CPCG06Q40/03
Inventor 陈国定徐英浩
Owner ZHEJIANG UNIV OF TECH
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