A Successful Transaction-Level Simulation Model of the US Securities Marketplace

In 2004, following the Livewire Cyber Exercise,(1) subject-matter experts from the financial services industry, academic researchers and experts in developing simulation models and running exercises met to discuss the gap that then existed between the standard mode of exercises and how decisions are actually made at banks and securities firms, clearing firms and exchanges, and other key players within financial services. The group discussed how that gap might be addressed and decided upon a closed-loop, transaction-level simulation model as being the best approach. A team of simulation experts built DECIDE-FS (TM) (Distributed Environment for Critical Infrastructure Decision-Making Exercises-Financial Services) with extensive guidance from financial services professionals provided via the SMART program of the Financial Services Sector Coordinating Council R&D Committee. DECIDE-FS (TM) has evolved into a realistic transaction-level simulation of the U. S. securities industry. It is used for exercises, particularly those involving cyber disruption scenarios, which engage broker-dealers, stock exchanges, and other entities such as government agencies and industry associations. In this paper, the authors describe how the DECIDE-FS (TM) model was conceived and evolved, and how it has been used as the basis for numerous exercises and training sessions. The unique approach to managing exercises, direct player involvement throughout an exercise, the use of virtual artificial-intelligence players and advanced communications support are particular features of the DECIDE-FS (TM) model that have made for a realistic representation of the industry and its members. These features result in a realistic interchange among participants and role-based decision-making in real time throughout the exercise. The authors also discuss how the DECIDE-FS (TM) model might be readily adapted to other critical infrastructure sectors, such as electric power, telecommunications and transportation, as well as to supply-chain risk management for critical manufacturing, and emergency management. The feasibility of making the model operational is also discussed.