Enterprise scoring model construction method, enterprise scoring method and device

Abstract

The invention provides an enterprise scoring model construction method, an enterprise scoring method and an enterprise scoring device, and the enterprise scoring model construction method comprises the following steps: obtaining portrait data and operation data of the same kind of enterprises, carrying out dimension reduction processing on the portrait data and the operation data, and selecting anin-mold index from a dimension reduction result; Classifying the in-mold indexes, and constructing class indexes; For the class indexes, executing the following steps: determining a judgment matrix according to an important relationship among the in-mold indexes contained in the class indexes; Performing normalization processing on the judgment matrix, and determining a judgment matrix weight data set corresponding to the judgment matrix; Calculating a variance weight data set corresponding to the class index by using a variance method; And calculating an in-mold index weight according to thejudgment matrix weight data set and the variance weight data set. According to the scheme provided by the invention, the influence of human interference or subjective factors is greatly reduced, so that the scoring accuracy is effectively improved.

Description

technical field [0001] The present invention relates to the technical field of big data analysis, in particular to a method for constructing an enterprise scoring model, an enterprise scoring method and a device. Background technique [0002] Enterprises are a very important front-end customer acquisition channel for financial institutions such as banks. Using big data technology to comprehensively score enterprises can help financial institutions select excellent enterprises, and can also help financial institutions establish high-quality risk in the process of lending to enterprises. control system. [0003] At present, the way to comprehensively score enterprises is mainly to collect several indicators of enterprises, assign corresponding weights and scoring rules to these indicators artificially, and calculate enterprise scores according to the artificially assigned weights and scoring rules. The existing comprehensive scoring method often results in low scoring accurac...

AI Technical Summary

Problems solved by technology

The existing comprehensive scoring method often results in low scoring accuracy due to human interference or subjective factors.

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