Nellie Zhang is a senior economist in the Banking and Payments Department (BAP) at the Bank of Canada. Her primary research interests include financial market infrastructures such as liquidity risk and credit risk in large-value payment systems as well as the efficiency issues. Recently Nellie’s research focus has evolved to include research on topics related to retail payment systems. These topics include measuring intraday counter-party credit risk in Canada's retail batch payment system (ACSS) and implications of potential payment migration from ACSS to other parts of payments ecosystem.
We study the impact of the Bank of Canada’s choice of settlement mechanism in Lynx on participant behaviors, liquidity usage, payment delays and the overall operational efficiency of the new system.
As part of modernizing its core payments infrastructure, Canada will replace the Large Value Transfer System (LVTS) with a new Real-Time Gross Settlement (RTGS) system called Lynx. An important question for policy-makers is how Lynx should be designed.
The Large Value Transfer System (LVTS) loss-sharing mechanism was designed to ensure that, in the event of a one-participant default, the collateral pledged by direct members of the system would be sufficient to cover the largest possible net debit position of a defaulting participant. However, the situation may not hold if the indirect effects of the defaults are taken into consideration, or if two participants default during the same payment cycle.
We quantitatively assess the changes in participants’ payment behaviour from modernizing Canada's high-value payments system to Lynx. Our analysis suggests that Lynx's liquidity-saving mechanism encourages liquidity pooling and early payments submission, resulting in improved efficiency for participants but with slightly increased payment delays.
This paper proposes a unique approach to simulate intraday transactions in the Canadian retail payments batch system when such transactions are unobtainable. The simulation procedure has potential for helping with data-deficient problems where only high-level aggregate information is available.
This paper uncovers trends in payment timing in Canada’s Large Value Transfer System (LVTS) from 2003 to 2011. Descriptive analysis shows that LVTS payment activity has not been peaking in the late afternoon since 2008, and the improvement was most significant in 2009.
This paper applies a static model of an interest rate corridor to the Canadian data, and estimates the aggregate demand for central-bank settlement balances in the Large Value Transfer System (LVTS).
In the Canadian large value payment system an important goal is to understand how liquidity is transferred through the system and hence how efficient the system is in settling payments. Understanding the structure of the underlying network of relationships between participants in the payment system is a crucial step in achieving the goal.
In this article, the authors review work done at the Bank of Canada and at other central banks with the relatively new application of network analysis to the study of payments systems.
Zhang, "Estimating the demand for settlement balances in the Canadian Large Value Transfer System: How much is too much?," Canadian Journal of Economics 52, no.2 (May 2019): 735-762
Rivadeneyra and N. Zhang, "Payment coordination and liquidity efficiency in wholesale payments systems", Journal of Financial Market Infrastructures 10, no. 3 (March 2022): 31-68
Desai and Z. Lu and H. Rodrigo and J. Sharples and P. Tian and N. Zhang, "From LVTS to Lynx: Quantitative assessment of payment system transition in Canada", Journal of Payments Strategy & Systems 17, no. 3 (September 2023): 291-314
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