Blockchain-Driven Transparent Supply Chain Governance Model for Real-Time Fraud Prevention in Global Trade

Abstract

The world trading system is highly vulnerable to fraud, counterfeiting and governance failures with losses of billions of dollars each year. For the purpose of this study, a unique model of governance for the supply chain based on blockchain is proposed, which aims to achieve a transparent supply chain and allow for real-time fraud prevention in multinational trade networks. The research is built on distributed ledger technology (DLT), smart contract automation and a new trust evaluation paradigm, Governance Trust Score (Gt) with quantitative statistical validation using Chi-Square and ANOVA analyses. Empirical evidence shows that, when it comes to fraud incidence, blockchain can cut it by up to 87%, and when it comes to transparency, blockchain can raise transactions to 94%, while cost efficiency is a significant benefit. The results of the statistical analysis, based on the hypothesis tests, confirmed that there is a significant association between blockchain integration and fraud reduction (χ² = 18.74, p < 0.01); and there are significant differences between the means of governance efficiency (F = 22.31, p < 0.001). Finally, the paper presents policy recommendations to align regulations and support AI-driven fraud detection in global trade.