Smart Contracts

Molten gold ownership transfer holds both historical and economic significance, serving as a crucial aspect of financial and wealth management practices. Traditional systems for transferring ownership of molten gold are often inefficient, susceptible to fraud, and lack transparency. In contrast, blockchain technology, with its decentralized, immutable, and transparent characteristics, presents a promising solution to these challenges. This paper explores the transformative potential of blockchain technology in revolutionizing the transfer of molten gold ownership. Utilizing blockchain for this purpose provides a secure and transparent method to track and verify ownership of gold assets. The proposed model facilitates the creation of digital tokens that represent physical gold, which can then be exchanged on a blockchain platform. By highlighting the transformative potential of blockchain in molten gold ownership transfer, this paper contributes to the ongoing discourse at the intersection of blockchain technology and asset management, paving the way for a more efficient, secure, transparent, and decentralized gold market.

Background: The length and depth of global supply networks have been rising over time, causing permanent problems in visibility, protection, and performance. Blockchain technology has come out as a disruptive technology to tackle all these problems, by providing decentralized, safe and transparent systems.  Objective: This article examines the use of blockchain technology within the context of supply chain and specifically digs deeper into the area of increased transparency, security and subsequent efficient supply chain transactions. The aim is to show that it is possible to transform resource supply chain operations through blockchain and engender trust amongst stakeholders. Methods: Permissioned blockchain system has been design and implemented using proof of Authority (PoA) consensus algorithm. IoT sensors were deployed to obtain data in real-time, and smart contracts were incorporated to perform the tasks of product evaluation, and payment authorization. The performance of the system was assessed depending on the indicators including the number of transactions per time or volume per time, time taken for each transaction, auditability and workability. Results: The combination of high transaction throughput with low latency made the blockchain system scalable as well as operationally stable. Smart contracts were able to minimize the time taken and mistakes, and improve the integration of IoT in relation to tracing transactions in real time. The system also proved that it had the ability to withstand cyber assaults and no data were compromised.  Conclusion: Based on the analysis of supply chain problems, blockchain technology can be used to transform supply chain management. Furthermore, more studies should be done on the future compatibility of the usage of such a system with new technology trends and also its implementation in multiple regions supply chain to harness this valuable system.

Internal Financial Control (IFC) is a critical component of corporate governance, ensuring the accuracy, reliability, and compliance of financial reporting. Traditional IFC systems rely on manual audits, centralized databases, and rule-based checks, which are often inefficient, prone to human error, and vulnerable to fraud. The integration of Blockchain Technology and Machine Learning (ML) has introduced transformative improvements in Internal Financial Control (IFC) systems. This paper explores how Blockchain and machine learning (ML) technologies can strengthen internal financial controls (IFC). By addressing limitations in traditional systems, these technologies introduce transparency, automation, and predictive capability, fostering enhanced compliance and reduced risk. The integration of these technologies offers a paradigm shift for governance, risk management, and auditing practices, enhances fraud detection and regulatory compliance, while addressing challenges such as scalability and data privacy. Through a synthesis of academic literature and industry case studies, Blockchain ensures immutable transaction records, while ML enables predictive anomaly detection. Blockchain and ML are transforming internal financial control by enhancing security, automation, and predictive capabilities. There are still challenges in overcoming scalability, interpretability, Hybrid Blockchain-ML frameworks, and regulatory challenges for widespread adoption.