Enterprise Digital Twins in Financial Services: Convergence of Architecture, Operations, and Engineering
Year: 2025
Type: preprint
Abstract: The Enterprise Digital Twin (EDT) represents the convergence of decades-long parallel innovations in enterprise architecture (Zachman, TOGAF, ArchiMate), systems engineering (Agile, DevOps), and operational management (ITIL, SRE, observability). This paper demonstrates that EDTs are not an abrupt invention but the culmination of six decades of theory and practice-from 1960s socio-technical systems to contemporary AI-enabled, graph-driven models. Recent advances in graph databases, semantic modeling, and AI-augmented engineering now make implementation feasible, with EDTs providing the context that is so important for agentic AI. The paper examines EDT foundations in ontology, taxonomy, and graph theory; reviews enabling standards and technologies; outlines socio-technical implementation methodology; and analyzes real-world applications including ING's capability transformation, Lloyds' observability model, and Singapore's national digital twin. FSIs can adopt EDTs with confidence, applying proven frameworks through modern technologies. The purpose of an EDT is to help FSIs to address one of their key challenges-accelerating innovation without compromising compliance and security-but the principles apply equally to healthcare and government. Starting to build an EDT presents an opportunity for architecture, engineering and operations teams to pool their strengths around a common business problem. We discuss the rise of an Autonomous Agentic Twin: orchestrated agentic swarms that cooperate with the EDT to autonomously execute business processes, make governance-compliant decisions, and adapt to changing conditions. This evolution represents the rapidly approaching future of autonomous enterprises.
Source: SSRN Electronic Journal
DOI: 10.2139/ssrn.6077926
Author: Glen Stokes
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4413638561