The Technical Support and Decision-Making Role of Digital Twins

Abstract

In the wave of digital transformation, large enterprises increasingly face challenges in financial management, particularly in balancing efficiency improvement, cost optimization, and data-driven decision-making. The traditional financial model needs of innovation urgently, which provides an important context for applying digital twins in financial scenarios. This research examines Yunnan Investment Group’s (YIG) use of digital twin technology, focusing on the technical support and decision-making role in financial scenarios. Digital twin technology builds data decision-making models at different enterprise levels and create a real-time, detailed and multidimensional data foundation for accounting measurement. Empirical results reveal that YIG’s implementation reduced manual data processing workloads by 35%, accelerated financial statement preparation from weeks to days (47% efficiency gain), and enhanced predictive accuracy by 26% through machine learning-enhanced anomaly detection. These outcomes underscore digital twin technology’s dual role as both a technical enabler and a strategic advisor, demonstrating its capacity to drive intelligent financial ecosystems while mitigating systemic risks in large-scale enterprises.