Simulation Approaches to Risk, Efficiency, and Liquidity Usage in Payment Systems

Abstract

Payment systems constitute a critical aspect of modern economic infrastructure; yet understanding the payment system mechanisms remains elusive in the face of rapidly evolving financial markets and intricate institutional linkages. Computer simulations of payment systems have proven useful in determining optimal balances of risk, efficiency, and liquidity usage. Constructs such as gridlock-resolution algorithms and liquidity-saving mechanisms are now routinely applied in such areas as optimization of liquidity and payment delay, but can also be used to assess potential impacts of changes in policy or system setups. In addition, simulations can be extended to incorporate behavioral elements of participants by modeling their behavior with Agent-Based Modeling (ABM). The 2008 global financial crisis has increased interest in simulations to identify and quantify risk, particularly where new channels of contagion and complex interlinkages of markets and payment systems are involved. Payment system simulations offer central bank authorities broad possibilities to improve their risk monitoring and should be incorporated as a standard part of financial stability analysis.