RDP 2012-06: The Impact of Payment System Design on Tiering Incentives 7. Weighing the Benefits and Costs of Tiering

The liquidity savings from tiering come at the cost of increased credit and concentration risk. It follows that, in theory at least, these benefits and costs identified in Sections 5 and 6 can be weighed against each other in order to find a socially optimal level of tiering. This section briefly outlines the considerations and challenges involved in such an exercise. To do this precisely would require an expression of benefits and costs that are comparable on a dollar-for-dollar basis, which is beyond the scope of this paper.

One measure of the benefit of liquidity savings is the opportunity cost of the collateral used to obtain liquidity. For the United Kingdom, James and Willison (2004) suggest that this is equal to the value of the collateral used, multiplied by the spread between the (unsecured) London Interbank Offered Rate (LIBOR) and the secured-lending repo rate. The intuition behind this calculation is that an institution in possession of collateral-eligible securities could use those securities to obtain funds in the secured lending market, and then lend those funds out at LIBOR.

In the Australian context, however, there is evidence to suggest that the opportunity cost of collateral is low. The range of collateral accepted by the RBA for intraday repos is significantly broader than that used in secured market trades. Moreover, Commonwealth Government securities (CGS) are the most commonly used collateral in intraday repos, and many participants already hold CGS under prudential regulatory requirements. Instead, RBA liaison with RITS participants suggests that the benefit of liquidity savings might be more closely associated with savings in the operational costs (both direct and indirect) of accessing the repo facility. Placing a dollar value on these savings is difficult given that they are likely to vary across institutions.

Risk in this context relates to losses that might be realised if a particular event occurs, such as the default of, or an operational disruption at, a settlement bank. Estimating the expected loss due to credit exposures is, in theory, relatively easy. Section 6.1 provides estimates of the loss that a settlement bank faces if a particular client fails, and vice versa. Multiplying this potential loss by the relevant probability of failure would yield a measure of expected loss, comparable on a dollar-for-dollar basis with the benefit of liquidity savings. While probabilities of failure can be inferred roughly from credit ratings, this approach is subject to a number of caveats. Moreover, account should also be taken of the potential second-round effects of the default of the settlement bank's clients or the clients' inability to access the RTGS system, which could affect other participants in a tiered system.

Placing a dollar value on the loss resulting from an operational disruption at a direct participant is also quite difficult. For example, the incremental social cost of an operational disruption at a settlement bank in a tiered system should take into account the delay and operational costs incurred by:

• the settlement bank itself;
• clients of the settlement bank;
• other participants in the system; and
• the operator of the payments system.