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Tail Risk in a Retail Payments System

  • Leonard Sabetti , David T. Jacho-Chávez , Robert Petrunia and Marcel C. Voia EMAIL logo


In this paper, we study a credit risk (collateral) management scheme for the Canadian retail payment system designed to cover the exposure of a defaulting member. We estimate ex ante the size of a collateral pool large enough to cover exposure for a historical worst-case default scenario. The parameters of the distribution of the maxima are estimated using two main statistical approaches based on extreme value models: Block-Maxima for different window lengths (daily, weekly and monthly) and Peak-over-Threshold. Our statistical model implies that the largest daily net debit position across participants exceeds roughly $1.5 billion once a year. Despite relying on extreme-value theory, the out of sample forecasts may still underestimate an actual exposure given the absence of observed data on defaults and financial stress in Canada. Our results are informative for optimal collateral management and system design of pre-funded retail-payment schemes.


The views expressed in this paper are those of the authors, and do not represent an official position of Payments Canada. We would like to thank Neville Arjani, Brendan Carley and Walter Engert for helpful comments as well as seminar participants at the 2017 Canadian Economics Association conference and the 2017 Canadian Stata Users Group meetings. Jacho-Chávez, Petrunia, and Voia thank Payments Canada for financial support to undertake this research.


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Article note

This article is part of the special issue “Big Data” published in the Journal of Economics and Statistics. Access to further articles of this special issue can be obtained at

Received: 2016-11-24
Revised: 2017-04-30
Accepted: 2018-01-31
Published Online: 2018-06-27
Published in Print: 2018-07-26

© 2018 Oldenbourg Wissenschaftsverlag GmbH, Published by De Gruyter Oldenbourg, Berlin/Boston

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