Research on Blockchain Consensus Mechanism and Risk Pricing Methods for Multi-Institution Financial Credit

Abstract

In the field of financial credit, the phenomenon of credit data silos among institutions severely hinders the improvement of risk control effectiveness. This study proposes a multi-institution collaborative credit solution that integrates a consortium blockchain consensus mechanism with an innovative risk pricing model. A distributed credit information sharing platform was constructed based on Hyperledger Fabric, and an analytical dataset comprising 543,217 credit records was established. The risk pricing model developed in this study is based on logistic regression, combined with graph structure relationship modeling, achieving an AUC value of 0.917 on the test set and reducing the prediction error rate by 8.9% compared to traditional centralized models. Furthermore, the credit approval process based on the blockchain consensus mechanism reduced the average approval cycle from T+3 days to T+0.4 days. The study demonstrates that the proposed solution can significantly enhance the accuracy of risk assessment and the efficiency of approval processes in multi-institution financial credit.