Abstract
Abstract 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.
Highlights
The ability to accurately estimate the extent to which the failure of a bank disrupts the financial system is very valuable for financial regulators
This paper develops a robust measure based on absorbing Markov chains, SinkRank, that accurately predicts the magnitude of disruption caused by the failure of a bank in an interbank payment system and identifies the banks most affected by a failure
This paper developed the new metric SinkRank based on absorbing Markov chains and evaluated its accuracy by comparing it with results from simulated failure scenarios in payment systems modeled after the Fedwire system
Summary
The ability to accurately estimate the extent to which the failure of a bank disrupts the financial system is very valuable for financial regulators. This paper develops a robust measure based on absorbing Markov chains, SinkRank, that accurately predicts the magnitude of disruption caused by the failure of a bank in an interbank payment system and identifies the banks most affected by a failure. All economic activity is facilitated by transfers of claims by financial institutions These claim transfers generate payments between banks whenever they are not settled across the books of a single bank. These payments are settled in interbank payment systems. We use network methods to develop a metric that identifies systemically important banks but can predict the banks most affected by a failure, and validate the metric using simulated payment systems. Interactive versions of the charts are available at www.fna.fi/sinkrank
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
