Title | A Novel Blockchain-Driven Framework for Deterring Fraud in Supply Chain Finance |
Publication Type | Conference Paper |
Year of Publication | 2022 |
Authors | Xu, Ruiyun, Wang, Zhanbo, Zhao, J. Leon |
Conference Name | 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) |
Keywords | Agent-based modeling, airflow, blockchain, deterrence, Fabrics, finance, fraud, fraud detection, Human Behavior, Hyperledger Fabric, Licenses, pubcrawl, Real-time Systems, resilience, Resiliency, Scalability, supply chain finance, Supply chains |
Abstract | Frauds in supply chain finance not only result in substantial loss for financial institutions (e.g., banks, trust company, private funds), but also are detrimental to the reputation of the ecosystem. However, such frauds are hard to detect due to the complexity of the operating environment in supply chain finance such as involvement of multiple parties under different agreements. Traditional instruments of financial institutions are time-consuming yet insufficient in countering fraudulent supply chain financing. In this study, we propose a novel blockchain-driven framework for deterring fraud in supply chain finance. Specifically, we use inventory financing in jewelry supply chain as an illustrative scenario. The blockchain technology enables secure and trusted data sharing among multiple parties due to its characteristics of immutability and traceability. Consequently, information on manufacturing, brand license, and warehouse status are available to financial institutions in real time. Moreover, we develop a novel rule-based fraud check module to automatically detect suspicious fraud cases by auditing documents shared by multiple parties through a blockchain network. To validate the effectiveness of the proposed framework, we employ agent-based modeling and simulation. Experimental results show that our proposed framework can effectively deter fraudulent supply chain financing as well as improve operational efficiency. |
Notes | ISSN: 2577-1655 |
DOI | 10.1109/SMC53654.2022.9945470 |
Citation Key | xu_novel_2022 |