Identification of over and under provision of liquidity in real-time payment systems

It can be difficult to tell to what extent the amount of liquidity that an individualbank provides is intentional and to what extent it results from external factors that are beyond its control. In this paper, we describe two methods for evaluating liquidity provision in real-time gross settlement payment systems.We also utilize a recombinant approach to detect instances where observed patterns of liquidity provision are unlikely to have occurred in the absence of some behavioral or structural factors, such as differences in banks'business models.We apply our techniques to crisis-period data from the Clearing House Automated Payment System (CHAPS), the UK large-value payment system. We find that smaller banks provide more liquidity to the system than larger banks relative to their payment flows. Moreover, we observe an increase in the degree of inequality of liquidity provision relative to usage across banks following the collapse of Lehman Brothers. Our results suggest that the instances of over and under provision of liquidity that appear in our data are more frequent than would be expected from random payment flows.