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Regional credit prediction method and system based on multiple regression and time sequence

A technology of time series and multiple regression, applied in forecasting, instrumentation, complex mathematical operations, etc., can solve problems such as high cost, unfavorable maintenance, low accuracy, lack of quantitative analysis of influencing factors, etc.

Pending Publication Date: 2021-05-18
CCB FINTECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The embodiment of the present application provides a regional credit forecasting method and system based on multiple regression and time series, which solves the unscientific forecasting, low accuracy rate, complex model structure and high cost of the regional credit forecasting model in the prior art. Maintenance, the technical problem of lack of quantitative analysis of influencing factors, to achieve accurate quantitative analysis of various indicators, scientific and accurate prediction of regional credit, and reduce maintenance costs, further achieve the technical effect of providing scientific decision-making reference

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  • Regional credit prediction method and system based on multiple regression and time sequence
  • Regional credit prediction method and system based on multiple regression and time sequence
  • Regional credit prediction method and system based on multiple regression and time sequence

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Embodiment 1

[0024] Such as figure 1 As shown, the embodiment of the present application provides a regional credit prediction method based on multiple regression and time series, wherein the method includes:

[0025] Step S100: Obtain influencing factor data, said influencing factor data includes industry data and macro data, and store said influencing factor data in a distributed database;

[0026] Furthermore, the obtaining of influencing factor data, said influencing factor data including industry data and macro data, and saving said influencing factor data in a distributed database, step S100 in this embodiment of the present application further includes:

[0027] Step S110: Obtain the information of the industry dispatching platform;

[0028] Step S120: Obtain the data in the industry through the industry scheduling platform;

[0029] Step S130: uniformly place the data in the industry in the distributed database; Step S140: obtain macro data standards;

[0030] Step S150: Obtain a ...

Embodiment 2

[0106] Based on the same inventive concept as the method for forecasting regional credit based on multiple regression and time series in the foregoing embodiments, the present invention also provides a system for forecasting regional credit based on multiple regression and time series, such as figure 2 As shown, the system includes:

[0107] A first obtaining unit 11, the first obtaining unit 11 is used to obtain influencing factor data, the influencing factor data includes industry data and macro data, and stores the influencing factor data in a distributed database;

[0108] A second obtaining unit 12, the second obtaining unit 12 is configured to obtain data processing requirements, process the influencing factor data in the distributed database according to the data processing requirements, and obtain factor processing data;

[0109] A third obtaining unit 13, the third obtaining unit 13 is configured to process data according to the factors, establish a multiple regressi...

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Abstract

The invention discloses a regional credit prediction method and system based on multiple regression and a time sequence. The method comprises the following steps: obtaining influence factor data; obtaining factor processing data; according to the factor processing data, establishing a multiple regression model, and obtaining a first output result of the multiple regression model; determining whether the first output result meets a first preset threshold value or not, and when the first output result does not meet the first preset threshold value, obtaining a step-by-step forward screening instruction; sending the screening output result to an expert screening unit to obtain an expert screening result; substituting the expert screening result into the multiple regression model to obtain a regional factor screening result; establishing a time sequence model; obtaining a second output result of the time sequence model; and obtaining a regional credit prediction result according to the regional factor screening result and the second output result. The technical problems that in the prior art, a regional credit prediction model is unscientific in prediction, low in accuracy, complex in model composition, high in cost, not beneficial to maintenance and lack of quantitative analysis on influence factors are solved.

Description

technical field [0001] The invention relates to the field of financial credit, in particular to a regional credit prediction method and system based on multiple regression and time series. Background technique [0002] Bank lending resources are limited and costly. Therefore, each commercial bank needs to allocate the bank's loan resources through a reasonable mechanism to promote the rational allocation and efficient use of resources. Therefore, measuring the credit demand in the region and then allocating reasonable credit resources can better promote the effective use of bank loan resources. At present, the industry does not have a model that specifically addresses the prediction of regional credit levels. Some of the existing models are mainly personal credit prediction, credit evaluation, loan amount evaluation and other models, and the prediction of the overall credit level of the region is only based on the combination of the region's Historical credit data, then us...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/02G06Q10/04G06Q10/06G06F17/18
CPCG06Q10/04G06Q10/06393G06F17/18G06Q40/03
Inventor 陈宏斌
Owner CCB FINTECH CO LTD
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