One System, Different Banks: DCV, Network Timing, and Uneven Effects

The CUD mechanism does not operate on an average bank. This chapter focuses on the differences among small, medium-sized, and large credit institutions, and on the infrastructure and calendar conditions that change the same liquidity trade-off. The practical judgment is that aggregate reserves cannot tell us who can pay early, who depends on incoming funds, or whether concentration improves coordination or increases exposure.

Size changes who feels a reserve release

The BIS study groups credit institutions into three size categories using terciles of average daily payment value. Institutions in the lowest third are classified as small, those in the middle third as medium-sized, and those in the highest third as large. This is a measure of payment activity, not a complete description of balance-sheet size, profitability, or business model. Its value is that it provides a consistent way to ask whether institutions with different roles in the CUD network respond differently to the same reserve-policy change.

The answer is yes. Additional liquidity from the reserve reductions shortens settlement times for small institutions at lower percentiles of the payment-value distribution. Medium-sized and large institutions, by contrast, show more systematic increases in settlement times at upper percentiles, with the effect more pronounced after the 2024 reserve change. Small institutions are more dependent on marginal liquidity and incoming payments, so a modest change in available funds can determine whether an early obligation is feasible. Larger institutions handle a greater share of payment value and may have more ways to manage the timing of a large obligation.

The tercile method is useful because it creates a visible contrast, but it should not be mistaken for a complete behavioral classification. Two banks in the same payment-value group may have different deposit bases, collateral, counterparties, or internal payment practices. A bank’s average daily value also does not tell us whether it pays early or waits on a particular day. The study itself points toward future behavioral clustering—distinguishing early payers from participants that wait for incoming funds—as a more refined way to understand heterogeneity. For the present evidence, payment activity is a disciplined proxy for network role, not a claim that size alone causes the timing response.

This does not mean that small institutions simply pay early and large institutions simply wait. The result is distributional and conditional. A small participant may settle a lower-value obligation sooner when a reserve release makes its immediate balance less restrictive, yet still depend on a payment from a larger counterparty for another obligation. A large institution may settle many routine transfers quickly while delaying the high-value part of its schedule because it is managing a money-market position, a securities transaction, or a larger set of funding contingencies. “Large” and “small” describe different exposures to the network, not fixed personality types.

The distinction matters because reserve requirements apply directly to credit institutions, while other participants can be affected indirectly through their counterparties. A securities-related entity or another participant that relies on a bank for settlement liquidity may experience a delay even if it is not itself subject to the reserve rule.