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

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

Tatu Laine (Bank of Finland, Finland), Kasperi Korpinen (Bank of Finland, Finland) and Matti Hellqvist (Bank of Finland, Finland)
DOI: 10.4018/978-1-4666-2011-7.ch004


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.
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Liquidity is a central concept in the analysis of payment systems. We define it as the capacity of a payment system to settle payments. Such liquidity may come from various sources, including balances at the central bank account, incoming payments, and intraday credit. The lack of liquidity can delay settling of payments between parties, so sophisticated algorithms have been developed for managing payment systems during episodes of low liquidity. The practice of netting (i.e. offsetting incoming and outgoing payments within a certain time period), for example, allows a payment system operate at lowered liquidity levels. Here, we use intraday liquidity as defined by the Bank for International Settlements (BIS, 2001).

Efficiency and adequate safety margins are key in defining an appropriate level of liquidity in a payment system (BIS, 2001). An efficient payment system is typically seen as one with low liquidity requirements and settlement costs. Efficiencies in this respect can often be gained by adopting straightforward practices such as netting of payments (BIS, 1990). A safe payment system, in contrast, must be sufficiently robust to overcome events where a share of system participants is temporarily affected by low liquidity or breakdowns occur in the settlement process.

Speed of settlement is affecting the efficiency and risks in two ways. Faster final settlement may decrease the accumulation of risks. It will also directly decrease the delays of settlement and enhance the circulation of money. Thus with improved speed, the payment system can be seen more efficient in its basic task. However, increased speed of settlement typically decreases the efficiency of liquidity use. As an example, RTGS (Real-Time Gross Settlement) payment systems are geared to minimizing credit and settlement risk but participants in RTGS system must provide more liquidity for the settlement and thus sacrifice liquidity efficiency for the sake of safety and decreased delays. Optimizing the efficiency of systems creates tradeoffs between risks, liquidity consumption and delays and the policymaker must decide where to place the emphasis in the design of the payment system (Leinonen & Soramäki, 2003).

Not surprisingly, much of current payment system modeling aspires to optimal satisfaction of safety and efficiency requirements (Chiu & Lai, 2007). A popular theme, exemplified in Europe’s TARGET2 system (Kokkola, 2010), is integration of multiple payment systems into a single platform to take advantage of economies of scale. Like RTGS, the emphasis remains on robustness and safety. Given that modern financial markets constantly seek to increase efficiency, new payment/settlement platforms intended to boost efficiency are rolled out on a regular basis. Modeling these new platforms and their interdependencies with existing systems adds to the ever-growing challenges facing the payment systems analyst (BIS, 2008).

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