Application of Machine Learning and Blockchain Technology in Improving Supply Chain Financial Risk Management

Abstract

The database used by blockchain innovation is run by numerous components and creates a network pattern using hash indexes. The blockchain employs numerous nodes and transmits numerous data access points, decreasing reliance on the primary Internet server and preventing the danger of data destruction and server breakdown. The data files saved in the blockchain are protected using encryption techniques to maintain their authenticity and prevent illegally added or discarded data files. With technological characteristics like non-tampering, distributed ledger, and reliability, blockchain innovations and machine learning have innate benefits in supply chain finance. They also have great prospects to construct faith in order to overcome the major issues in supply chain finance, which is helpful for fostering economic advancement in the Tonkin Gulf region. This paper focuses on introducing the study on using blockchain innovation in supply chain finance in the Tonkin Gulf region and aims to offer suggestions on how supply chain finance could evolve there using blockchain innovation. This paper suggests supply chain finance game applications for pertinent investigations as well as blockchain innovation, supply chain banking threats assessment on the blockchain and machine learning, and supply chain finance implementation study methodologies in the Tonkin Gulf region. The empirical findings presented in this paper demonstrate that the built blockchain supply chain finance platform has an algorithm with an overall processing time of 4.10 seconds, a computational efficiency that is quicker, and the ability to more accurately analyse the pertinent concerns.