The advent of Blockchain technology (BT) revolutionised the way remittance transactions are recorded. Banks and remittance organisations have shown a growing interest in exploring blockchain's potential advantages over traditional practices. This paper presents a data-driven predictive decision support approach as an innovative artefact designed for the blockchain-oriented remittance industry. Employing a theory-generating Design Science Research (DSR) approach, we have uncovered the emergence of predictive capabilities driven by transactional big data. The artefact integrates predictive analytics and Machine Learning (ML) to enable real-time remittance monitoring, empowering management decision-makers to address challenges in the uncertain digitised landscape of blockchain-oriented remittance companies. Bridging the gap between theory and practice, this research not only enhances the security of the remittance ecosystem but also lays the foundation for future predictive decision support solutions, extending the potential of predictive analytics to other domains. Additionally, the generated theory from the artifact's implementation enriches the DSR approach and fosters grounded and stakeholder theory development in the information systems domain.

翻译：区块链技术的出现彻底改变了汇款交易的记录方式。银行和汇款机构对探索区块链相对于传统实践的潜在优势表现出日益浓厚的兴趣。本文提出了一种数据驱动的预测性决策支持方法，作为面向区块链汇款行业的创新设计产物。通过采用理论生成的设计科学研究方法，我们发现了由交易大数据驱动的预测能力的涌现。该产物整合了预测分析和机器学习技术，实现了实时汇款监控，使管理决策者能够应对区块链导向汇款公司在不确定数字化环境中的挑战。这项研究弥合了理论与实践之间的鸿沟，不仅增强了汇款生态系统的安全性，还为未来的预测性决策支持解决方案奠定了基础，并将预测分析的潜力扩展到其他领域。此外，该产物实施过程中生成的理论丰富了设计科学研究方法，促进了信息系统领域扎根理论和利益相关者理论的发展。