Design and Implementation of a Multi-Chain Lending Model in Blockchain

To address issues such as heterogeneous data volumes, slow approval processes, significant human risk, and inadequate supervision in the various stages of the lending process, this paper constructs a blockchain multi-chain traceability system for the tobacco industry using Hyperledger Fabric technology. It designs and implements a blockchain multi-chain lending model, leveraging the multi-chain structure to achieve data sharing and personal privacy data isolation in loan traceability. The Raft consensus algorithm is applied to formulate transaction endorsement policies, and smart contracts are designed to trace loan data and supervise the lending process. To verify the feasibility of the model, key performance tests were conducted using Tape. In terms of network performance, the main chain throughput can reach up to 412 transactions per second (tps), with latency sharply increasing when the number of requests per second reaches around 550, averaging 16ms before this point. The blockchain transaction success rate stands at 100%. Results demonstrate that the system meets the performance requirements for practical applications, achieving simplified loan processes and ensuring secure and reliable data.