The COVID-19 pandemic and the resulting public health mitigation have caused large-scale economic disruptions globally. During this time, there is an increased need to predict the macroeconomy's short-term dynamics to ensure the effective implementation of fiscal and monetary policy. However,...

We propose a flexible machine learning (ML) framework for real-time transaction monitoring in high-value payment systems (HVPS), which are a central piece of a country's financial infrastructure. This framework can be used by system operators and overseers to detect anomalous transactions,...

Predicting the economy's short-term dynamics-a vital input to economic agents' decisionmaking process-often uses lagged indicators in linear models. This is typically sufficient during normal times but could prove inadequate during crisis periods such as COVID-19. This paper demonstrates: (a)...

Modernizing Canada's wholesale payments system to Lynx from the Large Value Transfer System (LVTS) brings two key changes: (1) the settlement model shifts from a hybrid system that combined components of both real-time gross settlement (RTGS) and deferred net settlement (DNS) to an RTGS system;...

High-value payment systems (HVPSs) are typically liquidity-intensive because the payment requests are indivisible and settled on a gross basis. Finding the right order in which payments should be processed to maximize the liquidity efficiency of these systems is an NP-hard combinatorial...