An Agent-Based Model of Payment Systems

Galbiati, Marco; Soramäki, Kimmo

doi:10.2139/ssrn.1280904

Cited by 25 publications

(27 citation statements)

References 11 publications

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“…Also, some works allow behaviour adaptation based on changes in the different scenarios [7]. By this means, ABM is a methodology bringing together verbal descriptions of component systems and equation-based models [8].…”

Section: Related Workmentioning

confidence: 99%

Simulating the Fractional Reserve Banking using Agent-based Modelling with NetLogo

Monett

Navarro-Barrientos

2016

Annals of Computer Science and Information Systems

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Abstract-This work presents a multi-agent-based computational model of an artificial fractional reserve banking system. The model is implemented in NetLogo. The computational experiments and simulations we performed to analyse the proposed model show that different scenarios can lead to bank insolvency. We show that both the minimum reserve rate and the loss of confidence have large contributions to the insolvency of a bank, suggesting them as likely destabilizing economic forces driving the dynamics of the model.Index Terms-agent-based model, agent-based simulation, BDI agents, fractional reserve banking, NetLogo.

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Section: Related Workmentioning

confidence: 99%

Simulating the Fractional Reserve Banking using Agent-based Modelling with NetLogo

Monett

Navarro-Barrientos

2016

Annals of Computer Science and Information Systems

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“…All bank failures cause at least some Liquidity Dislocation, whereas Congestion only occurs in about half (62 / 100) of the bank failures; if all banks affected by a failure have enough liquidity to make their payments, no delay will occur. The relationship between Liquidity Dislocation and Congestion is convex as theoretically shown in Galbiati and Soramäki (2011). As more liquidity is dislocated, more delays occur that dislocate more liquidity.…”

Section: Simulation Model Of Payment Systemmentioning

confidence: 87%

SinkRank: An Algorithm for Identifying Systemically Important Banks in Payment Systems

Soramäki

Cook

2013

Economics

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The ability to accurately estimate the extent to which the failure of a bank disrupts the financial system is very valuable for regulators of the financial system. One important part of the financial system is the interbank payment system. This paper develops a robust measure, SinkRank, that accurately predicts the magnitude of disruption caused by the failure of a bank in a payment system and identifies banks most affected by the failure. SinkRank is based on absorbing Markov chains, which are well-suited to model liquidity dynamics in payment systems. Because actual bank failures are rare and the data is not generally publicly available, the authors test the metric by simulating payment networks and inducing failures in them. They test SinkRank on several types of payment networks, including Barabási-Albert types of scale-free networks modeled on the Fedwire system, and find that the failing bank's SinkRank is highly correlated with the resulting disruption in the system overall; moreover, the SinkRank algorithm can identify which individual banks would be most disrupted by a given failure. Published in Special IssueCoping with Systemic Risk JEL C63 E58 G01 G28

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“…Prior research also has assessed the benefit of payment settlement systems with simulation [24,29] and agent-based methods [18], and examined the network topology of payments, and how payments to and from banks shift in the presence of market shocks [40]. A major limitation in this line of work is that bank behavior is typically viewed as exogenous to the system.…”

Section: Literaturementioning

confidence: 99%

Mechanism Design for Near Real-Time Retail Payment and Settlement Systems

Guo

Kauffman

Lin

et al. 2015

2015 48th Hawaii International Conference on System Sciences

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Abstract"Only at the end of the day were the inter-bank claims settled, on a net basis.[The] system worked well: so long as [the] payments could be made then settlement went ahead.[I]f just one bank could not make its payments, the whole inter-bank settlement process would have been disrupted. This exposed a severe vulnerability -potentially threatening the stability of the entire financial system -if a bank failed."

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An Agent-Based Model of Payment Systems

Cited by 25 publications

References 11 publications

Simulating the Fractional Reserve Banking using Agent-based Modelling with NetLogo

Simulating the Fractional Reserve Banking using Agent-based Modelling with NetLogo

SinkRank: An Algorithm for Identifying Systemically Important Banks in Payment Systems

Mechanism Design for Near Real-Time Retail Payment and Settlement Systems

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