Machine learning interpretability-oriented credit default prediction method and system

A technology of machine learning and forecasting methods, which is applied in the direction of machine learning, forecasting, error detection of redundant data in calculations, etc., can solve problems such as inaccurate evaluation of credit, and achieve high efficiency, accurate results, and accurate predictions high rate effect
CN112686446APending Publication Date: 2021-04-20BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
0 Cites 2 Cited by

Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
Publication Date
2021-04-20

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention relates to the technical field of credit default prediction, in particular to a machine learning interpretability-oriented credit default prediction method, which comprises the following steps of S1, acquiring data; s2, preprocessing the data; s3, dividing and training data; s4, verifying the model. The invention further discloses a system of the credit default prediction method oriented to machine learning interpretability, the system comprises a data acquisition module, the data acquisition module is connected with a cleaning and screening module through a signal line, the cleaning and screening module cleans the input data, and if a certain variable of the data is missing, a few non-core data is deleted; if the deletion amount is large, the data is filled by an overall distribution sampling method and a method of performing maximum likelihood estimation according to other information, and the cleaning and screening module is connected with a data division module through a signal, so that default prediction can be performed efficiently and accurately.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to the field of credit default prediction, in particular to a credit default prediction method and system oriented to machine learning interpretability. Background technique

[0002] With the maturity of the financial lending market, small and micro enterprises have an increasing demand for loans. At the same time, the requirements for loan approval efficiency, loan issuance time, and loan issuance management continue to increase. Under the current conditions, how to save audits? Time, improvement of audit accuracy, and loan pool optimization management have become huge challenges. How to scientifically and reasonably price various risks is the key to bank credit departments to achieve efficient operation management, reduce operating costs, and ensure customer service quality and level. important link. At present, there is no good evaluation standard for customer credit review, and misjudgment is prone to occur. Contents of the...

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