What question did this study set out to answer?

To develop a blockchain-based dynamic credit risk assessment framework that resolves privacy conflicts and captures real-time risk propagation across supply chains.

August 16, 2026Advanced ElectromagneticsOpen Access

Constructing Credit Risk Assessment Model for Blockchain Technology and Supply Chain Finance

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To develop a blockchain-based dynamic credit risk assessment framework that resolves privacy conflicts and captures real-time risk propagation across supply chains.
Integrated Paillier-based homomorphic encryption and zk-SNARKs to facilitate secure, privacy-preserving data sharing and verification.
Coupled smart contracts, long short-term memory (LSTM) networks, and dynamic graph neural networks (DGNN) to monitor temporal and structural risk propagation across enterprises.
Evaluated the computational framework using a textile supply chain dataset.
Achieved approximately 94% credit risk assessment accuracy on the textile supply chain dataset.
Outperformed traditional static risk assessment models by 15% to 20% while maintaining rapid response speed and high transaction throughput.

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Implication

Computational evaluation demonstrates a blockchain-based dynamic risk model achieves 94% accuracy in supply chain networks, highlighting enhanced privacy and risk prediction.

Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/6a817980f2fb91fc834ac9e5 https://doi.org/10.7716/aem.v15i3.3133

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Implication

Computational evaluation demonstrates a blockchain-based dynamic risk model achieves 94% accuracy in supply chain networks, highlighting enhanced privacy and risk prediction.

Constructing Credit Risk Assessment Model for Blockchain Technology and Supply Chain Finance

Key Points

Discussion

Implication

Cite This Study

Constructing Credit Risk Assessment Model for Blockchain Technology and Supply Chain Finance

Key Points

Discussion

Implication

Cite This Study