RDP 2018-01: A Density-based Estimator of Core/Periphery Network Structures: Analysing the Australian Interbank Market 2. The Interbank Overnight Cash Market

Banks use the market for unsecured overnight interbank loans (IBOC market) to manage their liquidity.[4] Specifically, banks' deposit accounts with the RBA, which are used to settle the financial obligations arising from interbank payments, must remain in credit at all times. Banks borrow in the IBOC market to ensure they satisfy this requirement (as the cost of overnight borrowing from the RBA is higher than the typical IBOC market rate). The RBA also remunerates surplus balances in banks' deposit accounts at a rate below the typical IBOC market rate; banks, therefore, have an incentive to lend their surplus balances in the IBOC market.

The IBOC market also plays a role in disseminating private information. Loans in the IBOC market are transacted bilaterally and over-the-counter. Failure to raise sufficient liquidity through banks' usual relationships – due to liquidity hoarding, for example – could lead to increased counterparty searching, potentially signalling to the RBA and other banks an increase in idiosyncratic or market risk.

The RBA, and many other central banks, have historically relied on surveys to collect information about overnight interbank markets. But these survey data are typically highly aggregated. For example, until May 2016, the RBA's IBOC Survey only provided the aggregate gross value of each survey participant's IBOC lending and borrowing during each trading session of the day, and the average interest rate at which these loans occurred (importantly, no information on counterparties was collected).[5]

To overcome this deficiency, Brassil, Hughson and McManus (2016) developed an algorithm to extract loan-level information from Australia's real-time gross settlement system (all IBOC loans, and many other interbank payments, are settled through this system). This algorithm is based on the seminal work of Furfine (1999), but incorporates novel features to identify IBOC loans that are rolled over multiple days, including those that exhibit features similar to a credit facility (e.g. drawdowns and partial repayments).

The algorithm output provides us with a loan-level database of IBOC loans between 2005 and 2016 (the algorithm identifies close to 90 per cent of all loans during this period, see Brassil et al (2016)). This database consists of 62 banks and 147,380 IBOC loans. Banks are split into three categories: the four major Australian banks, other Australian-owned banks, and foreign-owned banks.[6] We use this database to construct the networks analysed in this paper.

Using a loan-level database to conduct a network analysis has several advantages. Unlike networks constructed from regulatory databases of banks' large exposures, a loan-level database allows us to consider the role played by small banks. This is particularly relevant when estimating core/periphery structures, as the omission of exposures to smaller banks could prevent some highly connected banks from being identified as such. A loan-level database also allows us to conduct our network analysis using all loans during a particular period (not just those at the end of each quarter), and at different frequencies (quarterly, monthly, weekly, etc). That said, loan-level databases do not typically cover as wide an array of markets as regulatory databases.


Although some non-banks are able to participate in the IBOC market, the majority of participants are banks. For simplicity, this paper refers to all participants as ‘banks’. [4]

From May 2016, the RBA has required banks to identify every IBOC loan when it is entered into the RBA's settlement system. [5]

The four major Australian banks are Australia and New Zealand Banking Group Limited, Commonwealth Bank of Australia, National Australia Bank Limited and Westpac Banking Corporation. Confidentiality requirements prevent us from identifying individual banks. [6]