AI-Enabled Smart Contracts for Financial Transactions in Supply Chains

Abstract

Introduction: The quick digitization of supply chain finance has underlined the importance of automated, transparent, and efficient financial transactions. Conventional supplier payment systems are plagued by delays, human mistakes, and lack of transparency, thereby generally resulting in disputes and inefficiencies.

Objectives: The present paper discusses the use of Artificial Intelligence (AI) and smart contracts to automate supplier payments on the basis of specified performance parameters. Artificial intelligence technologies like machine learning (ML), natural language processing (NLP), and predictive analytics support instant evaluation of the suppliers, and blockchain-enabled smart contracts guarantee safe, immutable, and automatic payment realization.

Methods: Additionally, AI-driven business intelligence (BI) insights enhance supply chain optimization by offering predictive analytics, real-time financial monitoring, and risk assessment, leading to improved decision-making.

Results: The considered AI-empowered smart contract platform is formed by three levels: data collection, AI processing, and execution of a smart contract. In this article, there is given a conceptual model, anticipated improvements in performance, and comparison analysis between the old way and the use of AI-based financial transactions.

Conclusions: The results indicate that AI-based smart contracts increase efficiency, minimize payment disputes,

and increase transparency. Nevertheless, the issues of scalability, regulatory compliance, and security threats need to be overcome to facilitate mass adoption. This work adds to the existing debate regarding AI-driven automated financial transactions and presents a framework for future empirical investigation and real-world application.