Personal credit scoring method and device based on instruction data

Abstract

The embodiment of the invention discloses a personal credit scoring method and device based on instruction data. The method comprises the steps that a sample account group is acquired, and positive samples and negative samples are selected from the sample account group according to preset rules; binning processing is performed on a first preset index group, and a WOE value corresponding to each bin is acquired according to the ratio of the negative samples in each bin; the estimated quantity of parameters of a pre-constructed logistic regression model is acquired according to the WOE value corresponding to each bin; penalty items are configured for the estimated quantity of the parameters of the logistic regression model, wherein the personal items are used for configuring contributions ofsignaling data and other non-signaling data to the logistic regression model; and the personal credit of a user is scored according to the logistic regression model, and a personal credit score of the user is acquired. According to the embodiment, the logistic regression model is improved based on the signaling data to guarantee that the signaling data has a large ratio in the logistic regressionmodel; and compared with the prior art, the personal credit scoring method and device have the advantage that scoring is more accurate.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of credit risk management, and in particular to a personal credit scoring method and device based on instruction data. Background technique [0002] As of the end of September 2015, the credit information system of the central bank has included 870 million natural persons and 21.02 million enterprises and other organizations. Business and communication payment records, etc. In fact, mobile companies have detailed user behavior data, user background information, and can also grasp signaling data of user location information, call communication records, payment and consumption records, and these data have already been incorporated into the national credit system. As the field of credit investigation with the most practical value in the application of big data, mobile companies have been constantly exploring. [0003] In the process of implementing the embodiment of the present inven...

AI Technical Summary

Problems solved by technology

[0004] One purpose of the embodiments of the present invention is to solve the problem of inaccurate scoring results in the prior art due to the lack of emphasis on the factors considered in the scoring

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