Predicting payment migration in Canada / by Anneke Kosse, Zhentong Lu and Gabriel Xerri
- Author:
- Kosse, Anneke
- Published:
- [Ottawa] : Bank of Canada = Banque du Canada, 2020.
- Copyright Date:
- ©2020
- Physical Description:
- 1 online resource (ii, 43 pages).
- Additional Creators:
- Bank of Canada
Access Online
- epe.lac , Free-to-read
- publications.gc.ca , Free-to-read
- Series:
- Restrictions on Access:
- Free-to-read Unrestricted online access
- Summary:
- 'Canada currently has two core payment systems for processing funds transfers between financial institutions: the Large Value Transfer System (LVTS) and the Automated Clearing Settlement System (ACSS). These systems will be replaced over the next years by three new systems: Lynx, the Settlement Optimization Engine (SOE) and the Real-Time Rail (RTR). We employ historical LVTS and ACSS data to predict the demand for the future systems. The results show that small-value LVTS payments will likely migrate to SOE. Also, in the short run, about CAD 10,000 billion of LVTS and ACSS payments (per year) is anticipated to migrate to the RTR if not subject to maximum transaction values. These migration patterns raise important policy questions, such as whether the future systems should be subject to value caps and/or higher collateral requirements'--Abstract, page ii.
- Report Numbers:
- FB3-5/2020-37E-PDF
- Subject(s):
- Electronic funds transfers—Canada
- Electronic funds transfers—Canada—Econometric models
- Transferts électroniques de fonds
- Transferts électroniques de fonds—Modèles économétriques
- Automated teller machine
- Bank
- Cheque
- Debit card
- Discrete choice
- Errors and residuals
- Finance
- Financial transaction
- Logistic regression
- Market (economics)
- Other Subject(s):
- Genre(s):
- Note:
- Distributed by the Government of Canada Publishing and Depository Services Program (Weekly acquisitions list 2020-38).
"Last updated: September 14, 2020." - Bibliography Note:
- Includes bibliographical references.
- Type of File/Data:
- Electronic monograph in PDF format.
View MARC record | catkey: 32857981