Simulation of automated real‐time gross interbank settlement
Abstract The aim of this paper is to analyze algorithms for the automated real‐time gross inter‐bank settlement (RTGS). One can change the efficiency of settlement systems by perfecting the processing of settlements and/or implementing rules for solving the gridlocks, or by applying the tools of refinancing and reservation. We focus on the settlement simulation of the Trans‐European Automated Real‐time Gross Settlement Express Transfer system (TARGET2). The system of modelling, simulation, and optimization of settlements (Baksys and Sakalauskas 2007b) is applied in the simulation of TARGET2, estimating the parameters of simulation according to the real data.
A Comparison of Alternative Interbank Settlement Systems
This paper presents a model to analyse alternative interbank settlement systems. Intraday credit exposures in netting systems generate systemic risk (the failure by one bank to settle at the end of the day may cause a chain of bank failures). To prevent this, mutual loss-sharing is implemented. Following Merton (1977), we develop a methodology to measure the cost of loss-sharing. Alternatively, banks can move to gross settlement. Since each payment is immediately settled, systemic risk is eliminated. But banks need collateral or reserves before making payments. Facing costly collateral holdings, banks will economise on them, which may generate delays. The trade-off between the cost of collateral and delay is incorporated in our model. Finally, we estimate the total cost of net and gross settlement. It is found that the extra cost of gross settlement exceeds the reduction in systemic risk.
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