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Working Paper

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Rapid expansion of e-commerce, along with rising domestic and cross-border payments, has fueled the demand among financial institutions for a cost-effective means to expedite clearing and settlement of low-value retail payments. These are called faster payments settlement systems. Traditionally, retail payments have made extensive use of interbank netting systems, in which payments are accumulated for end-of-day settlement. This approach, known as deferred net settlement (DNS), reduces the liquidity needs of the payment system, but bears inherent operational and financial risks for unsettled intraday payments. As large dollar volumes of retail payments accumulate, real-time gross settlement (RTGS) has been recognized as an attractive option, especially for high-value payments. It permits immediate settlement of transactions during the day, but it brings up other risks and incentives issues that require consideration. This research proposes a hybrid faster payments settlement system involving elements of both DNS and RTGS. We explore a mechanism that supports centralized queuing, permits payment prioritization, reduces payment delays, enhances liquidity, and optimizes the settlement process. We offer a modeling framework and experimental simulations to evaluate the proposed approach. Our evaluation is based on a set of system performance conjectures that support operational performance evaluation and mechanism design-related policy insights. Our results point out the qualities of a cost-effective and value-maximizing mechanism to quickly settle increasingly large volumes of retail payments, while ensuring that the incentives for payment system stakeholders are given careful consideration.


Clearing, faster payments, hybrid mechanism, management science, mechanism design, payment, policy analytics, payment, settlement, systems design


Computer Sciences | E-Commerce | Management Information Systems

Research Areas

Information Systems and Management

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SWIFT Institute, Working Paper No. 2014-004

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Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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