Joint credit scoring method and device based on privacy protection calculation and cross-organization

Abstract

The invention provides a joint credit scoring method and device based on privacy protection calculation and cross-organization, and the method comprises the steps: constructing local data resources in a plurality of edge nodes, and synchronizing the basic information and metadata information of the local data resources to a central node; constructing a data model in the central node through the synchronized information to carry out association analysis, and constructing a data index; performing association mapping on the data index and the metadata information of the plurality of edge nodes; on the basis of the multiple updated local data resources, a public sample is determined through privacy protection set intersection; calculating a weight parameter of the data index system through a multi-party data mining algorithm, and assigning the weight parameter to each feature of the index system of the scoring system; and carrying out credit scoring through the constructed joint scoring system model. According to the method, a cross-organization joint scoring card system architecture is generated under a security privacy adding mechanism, and a high-dimensional complex scoring system can be constructed by effectively utilizing multi-dimensional data.

Description

technical field [0001] The present application relates to the technical field of credit scoring, and in particular to a method and device for joint credit scoring based on privacy protection calculation and cross-organization. Background technique [0002] With the successful popularization of big data and artificial intelligence technology in many fields, big data-driven models are also expected to be applied to risk management in various fields such as construction and Internet finance. In the fierce competition environment, due to the influence of practical factors such as their own technical level and management, many institutions may have a credit crisis at any time. Therefore, in related technologies, various credit evaluation methods are usually used to achieve risk control, and the evaluation results are determined by means of credit scoring and credit rating, and then relevant strategies are formulated according to the evaluation results to reduce the adverse effect...

AI Technical Summary

Problems solved by technology

[0003] However, credit scoring methods in related technologies usually collect data independently for scoring by institutions with private big data platforms, resulting in limited data collection and limited collection indicators, thus lacking effective analysis methods and quantitative standards

Moreover, as people pay more and more attention to privacy and security, many data with sensitive information cannot be obtained, and the data cannot be effectively used.

Therefore, the credit scoring methods in related technologies cannot reasonably and effectively score and rate individuals or institutions

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