Application of Internet of Things and Machine learning in improving supply chain financial risk management System
Kafila, Nalla Bala Kalyan, Kamal Ahmad, Fakhruddin Rahi, Chetan J. Shelke, S. Mahabub Basha
Abstract
The incorporation of the Internet of Things (IoT) and machine learning (ML) methods has attracted significant interest in a variety of sectors in previous years. This article investigates the use of IoT and ML to improve supply chain financial (SCF) threat management. The supply chain is a complicated network with many key players, and financial threat management is important to its sustainability and success. IoT and ML possess inherent advantages in SCF due to their technology properties. They also have significant opportunities to build trust to solve big challenges in SCF, which aids financial development in the Tonkin Gulf area. This paper focuses on introducing the study on using Machine learning innovation in SCF in the Tonkin Gulf area and aims to offer suggestions on how supply chain finance could evolve there using Machine learning. This paper suggests supply chain finance game applications for pertinent investigations as well as blockchain innovation, supply chain banking threats assessment on the IoT and machine learning, and supply chain finance implementation study methodologies in the Tonkin Gulf region.