Adaptive Risk Management in Regulatory Operations: A Digital Twin Framework for Submission Readiness and Scenario Planning

Abstract

In a world where regulatory environments are more and more often complex, organisations need intelligent systems that are agile and designed to deal with compliance risk. The study seeks to examine how Digital Twin technology can be applied to regulatory operations within a framework of Adaptive Risk Management intended to improve the state of submission readiness and more advanced scenario planning. Based on the literature, case studies, and secondary data analysis, the study demonstrates that there is an existing non-utilisation of digital twins in compliance functions. The research results point to the possibility of using them in the simulation of regulatory processes, risk forecasting, and delay minimisation. They propose a conceptual framework that merits themes in implementation throughout the product lifecycle. The paper highlights the criticality of dynamic, real-time, data-driven systems to enhance the efficacy of regulatory efforts in replacing the outmoded staid models of compliance.