The Reserve Bank of Australia (RBA) publishes large amounts of data to its website as Excel Spreadsheets, but this method makes advanced queries and analytics difficult to query. For this reason, we synchronise our own systems with every available RBA data source, and we've built an API that return insightful information on current and historical trends that are suitable for graphing and broad reporting or analysis.
The API itself was built several years ago, while the direct integration to our Comparison, Lender, Metals, Census, and Stock API made in mid 2025. The API is available to all clients by virtue of their personal API Key, and given the licencing of RBA data, keys are generally issued to anybody that requires access.
AI API: A good finance API will always access up-to-date information, but a better AI will retrieve terabytes of fabricated data every day. Every morning at 4am we manufacture millions of text files full of calculated comparison data, policy information, and product variations. The RBA API plays a part in this process. We'll introduce BeNet in another article.
Febuary 2026 Update: If you're familiar with the API, the most recent updates includes the 'labels', 'label', and 'notes' responses in standard queries. Additionally, the returned chart code when querying graphs now supports Version 4.X of Chart JS.
The RBA API
Accessing Reserve Bank of Australia data is straightforward in theory, but in practice it’s slow, fragmented, and difficult to integrate into real-world analysis. That's why we built our RBA API = the only service of its kind in the industry. It’s a comprehensive suite of tools that lets you pull, process, and analyse RBA data in ways that aren't possible with pedestrian tools.
Clients have used the API for years to automate reporting, track lending and household trends, and model financial scenarios with precision. Every function in the API is designed to turn raw RBA figures into usable insights quickly, reliably, and at scale. The result: faster decision-making, more accurate forecasting, and, ultimately, better outcomes for businesses that rely on these insights.
In this article, we’ll look at selected API endpoints, and how you can use our API to return flat official data into actionable intelligence or website graphs.
The API provides for literally hundreds of permeations across virtually all our data source, so detailing all options isn't feasible or reasonable, so we'll look at limited basic queries that are more closely aligned with website graphs. We'll provide details on how to join the data with current lender data in another article.
The Marketing Relevance
The RBA API and associated graphing is another tool that contributes to your funnel expertise and authoritativeness. The concept of 'follow-up' is often touted by the clueless Facebook brigade as a sales opportunity... but they're completely oblivious to the differentiation between spam and 'everything else' (with their experience stinking of the former), with 'everything else' being the high-value and page-turning education and entertainment necessary to qualify you as a broker before building the required trust necessary for contact. Industry data, insights, analytes, and informed commentary, serves as funnel fuel - in company with our hundreds of other tools - that truly 'gamifies' and educates your potential clients. Real funnels remain the single most important organic conversion tool in your toolkit... and what you're doing now probably doesn't work.
RBA Cash Rate Graph: Probably the most essential graph required for regular inclusion in articles and pages, as well as a standalone page, the graph is managed via shortcode or an Elementor Widget. The graph may be customised in a large number of ways. The current cash rate figure can always be returned individually, such as 4.35%.
From an engagement perspective, the data provided via the API will support your content creation and social programs by way of what translates to millions of possible chart permiations. We'll share just a few charts only because the length of this article is a little nuts.
API Endpoint
The API Endpoints are made via our standard RESTful API URL followed by rba/json or rba/csv, with the latter returning flat CSV data. A number of paramaters are applied, with the action and apikey required for each request.
Standard API parameters that may be used with any request are start, end, and number, with other parameters listed below when required. The start and end date may be a UNIX timestamp, standard 6 figure date (20260223 or 2026-02-23), or a 10-figure date. Whenever values of any type are provided that are invalid, they are discarded and ignored. The number of results returned when 'number' is not provided is always 1000.
For ease of use, pagination is ignored, so all results are returned in a single payload, and no limits are applied to usage.
General API Examples
We'll look at the top-10 simple examples, and only 15 examples of slightly more complex queries - covering most general usage. At some point in the future, we'll build out some documentation that describes the hundreds of options that marries up official RBA data with Census and Lender data.
For brevity, we'll provide just one CSV example, but output is universal across all data. When data is shown it will be truncated for space, and the [ ... SNIP ... ] marker indicates where data was snipped.
RBA Cash Rate [ rba_cash_rate ]
The RBA Cash Rate simply returns cash rate determinations. Alternate actions are rba-cash-rate and f01d. Querying rba/json?apikey=your-api-key&action=rba-cash-rate&start=20250101&end=20260223 returns the following:
Querying rba/csv?apikey=your-api-key&action=rba-cash-rate&start=20250101&end=20260223&number=7 returns CSV without any headers.
1
date,cash_rate_target,change_cash_rate,interbank_overnight_cash_rate,interbank_highest_overnight,interbank_lowest_overnight,interbank_volume_overnight,interbank_number_overnight,cash_rate_return_index,bank_bills_negotiables_one_month,bank_bills_negotiables_one_three,bank_bills_negotiables_one_six,overnight_swap_index_one,overnight_swap_index_three,overnight_swap_index_six,treasury_note_one,treasury_note_three,treasury_note_six 2026-02-18,3.85,0,3.85,3.85,3.85,1143,10,142.868690,3.81,3.99,4.26,0,0,0,,,
2
2026-02-17,3.85,0,3.85,3.85,3.85,972,9,142.853622,3.79,3.97,4.23,0,0,0,,,
3
2026-02-16,3.85,0,3.85,3.85,3.85,796,3,142.838555,3.78,3.95,4.21,0,0,0,,,
4
2026-02-15,3.85,0,3.85,3.85,3.85,896,6,142.823490,3.80,3.96,4.22,0,0,0,,,
5
2026-02-12,3.85,0,3.85,3.85,3.85,725,7,142.778309,3.80,3.97,4.23,0,0,0,,,
6
2026-02-11,3.85,0,3.85,3.85,3.85,1487,14,142.763250,3.80,3.96,4.23,0,0,0,,,
7
2026-02-10,3.85,0,3.85,3.85,3.85,1492,9,142.748193,3.79,3.95,4.22,0,0,0,,,
The json extension in the URL may be replaced with csv for any response.
RBA Inflation [ rba_inflation & rba_inflation_month ]
The RBA Cash Rate simply returns cash rate determinations. Alternate actions are rba-inflation and g01hist. Querying rba/json?apikey=your-api-key&action=rba_inflation&number=2 returns the following:
1
Array
2
(
3
[status] => 200
4
[message] => Array
5
(
6
[0] => Success
7
[1] => 2 Results
8
[2] => Source: Reserve Bank of Australia (RBA)
9
)
10
11
[code] => 200
12
[data] => Array
13
(
14
[2001-06-30] => Array
15
(
16
[cpi] => 74.5
17
[year_inflation] => 6.1
18
[year_inflation_exclude_interest_tax] => 6.1
19
[year_inflation_exclude_volatile_terms] => 3
20
[year_tradables_inflation] => 2.8
21
[year_tradables_exclude_volatile_terms_tobacco] => 4.5
22
[year_non_tradables_inflation] => 3.4
23
[year_non_tradable_exclude_interest_deposit_loan] => 1.7
24
[year_weighted_median_inflation] => 1.7
25
[year_trimmed_mean_inflation] => 2.6
26
[quarterly_inflation_original] => 3
27
[quarterly_inflation] => 0.8
28
[quarterly_inflation_exlude_interest_tax] => 0.8
29
[quarterly_inflation_exclude_volatile_terms] => 0.8
30
[quarterly_tradables_inflation] => 0.9
31
[quarterly_tradables_exclude_volatile_tobacco] => 0.9
32
[quarterly_non_tradables_inflation] => 1.1
33
[quarterly_non_tradables_inflation_exclude_deposit_loans] => 0.7
34
[quarterly_weighted_median_inflation] => 0.7
35
[quarterly_trimmed_mean_inflation] => 0.8
36
)
37
38
[2001-03-31] => Array
39
(
40
[cpi] => 73.9
41
[year_inflation] => 6
42
[year_inflation_exclude_interest_tax] => 6
43
[year_inflation_exclude_volatile_terms] => 2.9
44
[year_tradables_inflation] => 2.3
45
[year_tradables_exclude_volatile_terms_tobacco] => 4
46
[year_non_tradables_inflation] => 2.3
47
[year_non_tradable_exclude_interest_deposit_loan] => 1.8
48
[year_weighted_median_inflation] => 1.8
49
[year_trimmed_mean_inflation] => 2.4
50
[quarterly_inflation_original] => 2.7
51
[quarterly_inflation] => 1.1
52
[quarterly_inflation_exlude_interest_tax] => 1.1
53
[quarterly_inflation_exclude_volatile_terms] => 1.1
54
[quarterly_tradables_inflation] => 0.9
55
[quarterly_tradables_exclude_volatile_tobacco] => 1.6
56
[quarterly_non_tradables_inflation] => 1.4
57
[quarterly_non_tradables_inflation_exclude_deposit_loans] => 0.5
58
[quarterly_weighted_median_inflation] => 0.5
59
[quarterly_trimmed_mean_inflation] => 0.9
60
)
61
62
)
63
64
[source] => Array
65
(
66
[source] => Reserve Bank of Australia (RBA)
67
[ link ] => https://www.rba.gov.au/statistics/tables/xls/g01hist.xlsx
68
)
69
70
)
The volatility of these numbers, or how they correlate to other published data is arguably more important from an analytics point-of-view, and we'll address this shortly.
Inflation Graph: The inflation graph is presented in a few different ways. Monthly data is also available, but as a new addition to RBA's data library we're still relying on quarterly figures. Individual figures may also be printed, such as the current monthly inflation (4.6%).
The monthly figure is derived from a relatively new data source, so results are limited. The monthly data is now used on your website header 'rate bar'.
Lender Rates [ rba_lender_rates ]
The F06 historical file contains long-running data on home loan interest rates in Australia. In simple terms, it shows what borrowers have actually been charged over time, broken down by loan type. clearest ways to understand how monetary policy and banking competition actually affect borrowers. It’s widely used for: Mortgage trend analysis, Housing affordability research, Economic modelling and forecasting, Comparing today’s rates to past cycles. Alternate actions are rba-lender-rates and f06hist. Querying rba/json?apikey=your-api-key&action=rba_lender_rates&number=2 returns the following:
1
Array
2
(
3
[status] => 200
4
[message] => Array
5
(
6
[0] => Success
7
[1] => 2 Results
8
[2] => Source: Reserve Bank of Australia (RBA)
9
)
10
11
[code] => 200
12
[data] => Array
13
(
14
[2025-12-30] => Array
15
(
16
[outstanding_oo_al_li] => 5.5
17
[outstanding_oo_al_ai] => 5.5
18
[outstanding_oo_variable_li] => 5.51
19
[outstanding_oo_variable_ai] => 5.51
20
[outstanding_oo_fixed_residual_fixed_lessequal_3years] => 5.27
21
[outstanding_oo_fixed_residual_fixed_greater_3years] => 6.04
22
[outstanding_oo_repayment_io] => 6.15
23
[outstanding_oo_repaymen_pi] => 5.48
24
[new_loans_oo_al_li] => 5.5
25
[new_loans_oo_al_ai] => 5.48
26
[new_loans_oo_variable_li] => 5.51
27
[new_loans_oo_variable_ai] => 5.5
28
[new_loans_oo_fixed_residual_fixed_lessequal_3years] => 5.17
29
[new_loans_oo_fixed_residual_fixed_greater_3years] => 5.91
30
[new_loans_oo_repayment_io] => 6.22
31
[new_loans_oo_repayment_pi] => 5.42
32
[new_loans_oo_lvr_commitment_less_81_percent] => 5.47
33
[new_loans_oo_lvr_commitment_greater_equal_81_percent] => 5.58
34
[new_loans_oo_value_less_equal_600] => 5.45
35
[new_loans_oo_value_600_1000000] => 5.47
36
[new_loans_oo_value_greater_1000000] => 5.55
37
[investment_all_li] => 5.73
38
[investment_all_ai] => 5.74
39
[investment_variable_li] => 5.74
40
[investment_variable_ai] => 5.75
41
[investment_fixed_residual_fixed_lessequal_3years] => 5.26
42
[investment_fixed_residual_fixed_greater_3years] => 6.6
43
[investment_repayment_io] => 5.87
44
[investment_repayment_pi] => 5.68
45
[investment_new_all_li] => 5.63
46
[investment_new_all_ai] => 5.67
47
[investment_new_variable_li] => 5.63
48
[investment_new_fixed_residual_fixed_lessequal_3years] => 5.43
49
[investment_new_fixed_residual_fixed_greater_3years] => 6.09
50
[investment_new_repayment_io] => 5.77
51
[investment_new_repayment_pi] => 5.59
52
[investment_new_lvr_commitment_less_81_percent] => 5.63
53
[investment_new_lvr_commitment_greater_equal_81_percent] => 5.98
54
[investment_new_value_less_equal_600] => 5.69
55
[investment_new_value_600_1000000] => 5.67
56
[investment_new_value_greater_1000000] => 5.65
57
)
58
59
[2025-11-29] => Array
60
(
61
[outstanding_oo_al_li] => 5.51
62
[outstanding_oo_al_ai] => 5.51
63
[outstanding_oo_variable_li] => 5.51
64
[outstanding_oo_variable_ai] => 5.52
65
[outstanding_oo_fixed_residual_fixed_lessequal_3years] => 5.26
66
[outstanding_oo_fixed_residual_fixed_greater_3years] => 6.11
67
[outstanding_oo_repayment_io] => 6.17
68
[outstanding_oo_repaymen_pi] => 5.48
69
[new_loans_oo_al_li] => 5.49
70
[new_loans_oo_al_ai] => 5.48
71
[new_loans_oo_variable_li] => 5.5
72
[new_loans_oo_variable_ai] => 5.49
73
[new_loans_oo_fixed_residual_fixed_lessequal_3years] => 5.08
74
[new_loans_oo_fixed_residual_fixed_greater_3years] => 6.24
75
[new_loans_oo_repayment_io] => 6.18
76
[new_loans_oo_repayment_pi] => 5.42
77
[new_loans_oo_lvr_commitment_less_81_percent] => 5.46
78
[new_loans_oo_lvr_commitment_greater_equal_81_percent] => 5.58
79
[new_loans_oo_value_less_equal_600] => 5.44
80
[new_loans_oo_value_600_1000000] => 5.47
81
[new_loans_oo_value_greater_1000000] => 5.53
82
[investment_all_li] => 5.74
83
[investment_all_ai] => 5.75
84
[investment_variable_li] => 5.75
85
[investment_variable_ai] => 5.76
86
[investment_fixed_residual_fixed_lessequal_3years] => 5.26
87
[investment_fixed_residual_fixed_greater_3years] => 6.82
88
[investment_repayment_io] => 5.88
89
[investment_repayment_pi] => 5.69
90
[investment_new_all_li] => 5.64
91
[investment_new_all_ai] => 5.66
92
[investment_new_variable_li] => 5.64
93
[investment_new_fixed_residual_fixed_lessequal_3years] => 5.38
94
[investment_new_fixed_residual_fixed_greater_3years] => 6.55
95
[investment_new_repayment_io] => 5.77
96
[investment_new_repayment_pi] => 5.59
97
[investment_new_lvr_commitment_less_81_percent] => 5.63
98
[investment_new_lvr_commitment_greater_equal_81_percent] => 5.97
99
[investment_new_value_less_equal_600] => 5.68
100
[investment_new_value_600_1000000] => 5.67
101
[investment_new_value_greater_1000000] => 5.64
102
)
103
104
)
105
106
[source] => Array
107
(
108
[source] => Reserve Bank of Australia (RBA)
109
[ link ] => https://www.rba.gov.au/statistics/tables/xls/f06hist.xlsx
110
)
111
112
)
The keys of the array are described in the helper action shown shortly.
Business & Personal Rates [ rba_lender_rates_business & rba_lender_rates_personal ]
The f07hist and f08hist files extend interest-rate coverage beyond housing into the broader economy. The f07hist file tracks historical interest rates charged on business lending, including variable and fixed-rate loans used by companies to fund operations, investment, and expansion. It reflects the average rates businesses actually pay, capturing changes in bank pricing, competition, and credit conditions over time. The f08hist file focuses on personal lending, covering products such as personal loans and credit card interest rates, providing a clear view of borrowing costs faced by households outside of mortgages. Together, these datasets allow analysis of how financial conditions affect businesses and consumers differently across economic cycles, and how changes in monetary policy flow through the wider credit market.
Data is returned in a format similar to rba_lender_rates (not shown for space). Alternative enaction parameters are rba-lender-rates-business, rba-lender-rates-personal, f07hist, and f08hist. The source is best paired with some of the more advanced combination queries.
Rate Indictors [ rba_lender_rates_indicators ]
The f05hist file contains historical lender rate indicators which shows how banks set and adjust their benchmark lending rates over time. It includes measures such as standard variable housing rates and other key reference rates used by lenders when pricing loans. Rather than reflecting what individual borrowers actually pay, this dataset captures the underlying rate signals from banks, making it useful for tracking pricing intent, competitive behaviour, and how quickly (or slowly) lenders respond to changes in monetary policy. Analysts often use f05hist to compare advertised or benchmark rates against realised borrowing costs in other datasets, helping to identify discounting trends and shifts in lender strategy across interest-rate cycles.
Data is returned in a format similar to rba_lender_rates_indicators. Alternative action parameters are rba-lender-rates-indicators and f05hist. The source is best paired with some of the more advanced combination queries.
Deposit Rates [ rba_advertised_deposit_rates & rba_paid_deposit_rates ]
The f04hist and f04-1-hist data sets cover the deposit side of the banking system, showing how households are rewarded for saving rather than borrowing. The f04hist file contains advertised deposit rates—the headline rates banks promote on products such as savings accounts and term deposits—making it a useful indicator of pricing intent and competitive signalling. By contrast, the f04-1-hist file tracks paid deposit rates, which reflect the average interest actually received by depositors after conditions, tiers, and bonuses are taken into account. Comparing the two provides a clear view of the gap between marketing rates and real outcomes, and how banks adjust their funding strategies and saver incentives across different interest-rate environments.
Data is returned in a standard format. Alternative action parameters are rba-advertised-deposit-rates, rba_paid_deposit_rates, f04hist. and f04-1-hist. The source is best paired with some of the more advanced combination queries.
RBA Expenditure Groups [ rba_cpi_expenditure_groups ]
The g02hist file breaks inflation down into what households actually spend money on. Instead of a single headline CPI figure, it shows how prices change across major expenditure groups such as housing, food, transport, health, education, recreation, and household services. This makes it possible to see where inflation is really coming from—for example, whether rising prices are being driven by rents and utilities, fuel and transport costs, or everyday essentials like groceries. The historical coverage allows analysts to track how different cost pressures behave over time and across economic cycles, providing far more insight than headline inflation alone and making it easier to link inflation trends to household behaviour and living costs.
Data is returned in a standard format. Alternative action parameters are rba_cpi_expenditure_groups and g02hist. The source is best paired with some of the more advanced combination queries.
Querying rba/json?apikey=your-api-key&action=rba_cpi_expenditure_groups&number=1 returns the following:
Advanced usage will usually pair this response with the 'basket of goods' assessment, CPI, and inflation.
Exchange Rates [ rba_exchange_rates ]
Daily exchange rates are obtained via the rba_exchange_rates or 2023-current action. This isn't our primary source of exchange data, but it is the sourced used for calculating local pricing for other services, such as the Metals API (Gold, Platinum, Silver etc). The currency parameter may be used to return only selected currencies, otherwise all are returned.
We can return 'notes' with the response that gives us additional information, and - as with all basic responses (discussed next) - the 'labels'. If notes=1 and labels=1 is included in the query, the following is returned:
1
Array
2
(
3
[status] => 200
4
[message] => Array
5
(
6
[0] => Success
7
[1] => 1 Results
8
[2] => Source: Reserve Bank of Australia (RBA)
9
)
10
11
[code] => 200
12
[data] => Array
13
(
14
[2026-02-20] => Array
15
(
16
[usd] => 0.7033
17
[twi] => 64.90
18
[cny] => 4.8562
19
[jpy] => 109.16
20
[eur] => 0.5984
21
[krw] => 1019.43
22
[gbp] => 0.5233
23
[sgd] => 0.8928
24
[inr] => 63.98
25
[thb] => 21.97
26
[nzd] => 1.183
27
[twd] => 22.16
28
[myr] => 2.7492
29
[idr] => 11873
30
[vnd] => 18264
31
[aed] =>
32
[pgk] => 3.0198
33
[hkd] => 5.4958
34
[cad] => 0.9631
35
[zar] =>
36
[sar] =>
37
[chf] => 0.5457
38
[sek] =>
39
[ php ] => 40.89
40
[sdr] => 0.5119
41
[dem] =>
42
[frf] =>
43
[esp] =>
44
[itl] =>
45
[nlg] =>
46
[bef] =>
47
[ats] =>
48
[fim] =>
49
[pte] =>
50
[iep] =>
51
[grd] =>
52
)
53
54
)
55
56
[source] => Array
57
(
58
[source] => Reserve Bank of Australia (RBA)
59
[ link ] => https://www.rba.gov.au/statistics/tables/xls-hist/2023-current.xls
60
)
61
62
[labels] => Array
63
(
64
[usd] => Array
65
(
66
[title] => A$1=USD
67
[description] => AUD/USD Exchange Rate; see notes for further detail.
68
[frequency] => Daily
69
[type] => Indicative
70
[units] => USD
71
[source] => WM/Reuters
72
[publication_date] => 19-Feb-2026
73
[series_id] => FXRUSD
74
[label] => USD
75
)
76
77
[twi] => Array
78
(
79
[title] => Trade-weighted Index May 1970 = 100
80
[description] => Australian Dollar Trade-weighted Index
81
[frequency] => Daily
82
[type] => Indicative
83
[units] => Index
84
[source] => RBA
85
[publication_date] => 19-Feb-2026
86
[series_id] => FXRTWI
87
[label] => TWI
88
)
89
90
[cny] => Array
91
(
92
[title] => A$1=CNY
93
[description] => AUD/CNY Exchange Rate
94
[frequency] => Daily
95
[type] => Indicative
96
[units] => CNY
97
[source] => RBA
98
[publication_date] => 19-Feb-2026
99
[series_id] => FXRCR
100
[label] => CNY
101
)
102
103
[jpy] => Array
104
(
105
[title] => A$1=JPY
106
[description] => AUD/JPY Exchange Rate
107
[frequency] => Daily
108
[type] => Indicative
109
[units] => JPY
110
[source] => RBA
111
[publication_date] => 19-Feb-2026
112
[series_id] => FXRJY
113
[label] => JPY
114
)
115
116
[eur] => Array
117
(
118
[title] => A$1=EUR
119
[description] => AUD/EUR Exchange Rate
120
[frequency] => Daily
121
[type] => Indicative
122
[units] => EUR
123
[source] => RBA
124
[publication_date] => 19-Feb-2026
125
[series_id] => FXREUR
126
[label] => EUR
127
)
128
129
[krw] => Array
130
(
131
[title] => A$1=KRW
132
[description] => AUD/KRW Exchange Rate
133
[frequency] => Daily
134
[type] => Indicative
135
[units] => KRW
136
[source] => RBA
137
[publication_date] => 19-Feb-2026
138
[series_id] => FXRSKW
139
[label] => KRW
140
)
141
142
[gbp] => Array
143
(
144
[title] => A$1=GBP
145
[description] => AUD/GBP Exchange Rate
146
[frequency] => Daily
147
[type] => Indicative
148
[units] => GBP
149
[source] => RBA
150
[publication_date] => 19-Feb-2026
151
[series_id] => FXRUKPS
152
[label] => GBP
153
)
154
155
[sgd] => Array
156
(
157
[title] => A$1=SGD
158
[description] => AUD/SGD Exchange Rate
159
[frequency] => Daily
160
[type] => Indicative
161
[units] => SGD
162
[source] => RBA
163
[publication_date] => 19-Feb-2026
164
[series_id] => FXRSD
165
[label] => SGD
166
)
167
168
[inr] => Array
169
(
170
[title] => A$1=INR
171
[description] => AUD/INR Exchange Rate
172
[frequency] => Daily
173
[type] => Indicative
174
[units] => INR
175
[source] => RBA
176
[publication_date] => 19-Feb-2026
177
[series_id] => FXRIRE
178
[label] => INR
179
)
180
181
[thb] => Array
182
(
183
[title] => A$1=THB
184
[description] => AUD/THB Exchange Rate
185
[frequency] => Daily
186
[type] => Indicative
187
[units] => THB
188
[source] => RBA
189
[publication_date] => 19-Feb-2026
190
[series_id] => FXRTB
191
[label] => THB
192
)
193
194
[nzd] => Array
195
(
196
[title] => A$1=NZD
197
[description] => AUD/NZD Exchange Rate
198
[frequency] => Daily
199
[type] => Indicative
200
[units] => NZD
201
[source] => RBA
202
[publication_date] => 19-Feb-2026
203
[series_id] => FXRNZD
204
[label] => NZD
205
)
206
207
[twd] => Array
208
(
209
[title] => A$1=TWD
210
[description] => AUD/TWD Exchange Rate
211
[frequency] => Daily
212
[type] => Indicative
213
[units] => TWD
214
[source] => RBA
215
[publication_date] => 19-Feb-2026
216
[series_id] => FXRNTD
217
[label] => TWD
218
)
219
220
[myr] => Array
221
(
222
[title] => A$1=MYR
223
[description] => AUD/MYR Exchange Rate
224
[frequency] => Daily
225
[type] => Indicative
226
[units] => MYR
227
[source] => RBA
228
[publication_date] => 19-Feb-2026
229
[series_id] => FXRMR
230
[label] => MYR
231
)
232
233
[idr] => Array
234
(
235
[title] => A$1=IDR
236
[description] => AUD/IDR Exchange Rate
237
[frequency] => Daily
238
[type] => Indicative
239
[units] => IDR
240
[source] => RBA
241
[publication_date] => 19-Feb-2026
242
[series_id] => FXRIR
243
[label] => IDR
244
)
245
246
[vnd] => Array
247
(
248
[title] => A$1=VND
249
[description] => AUD/VND Exchange Rate
250
[frequency] => Daily
251
[type] => Indicative
252
[units] => VND
253
[source] => RBA
254
[publication_date] => 19-Feb-2026
255
[series_id] => FXRVD
256
[label] => VND
257
)
258
259
[aed] => Array
260
(
261
[title] => A$1=AED
262
[description] => AUD/AED Exchange Rate
263
[frequency] => Daily
264
[type] => Indicative
265
[units] => AED
266
[source] => RBA
267
[publication_date] => 19-Feb-2026
268
[series_id] => FXRUAED
269
[label] => AED
270
)
271
272
[pgk] => Array
273
(
274
[title] => A$1=PGK
275
[description] => AUD/PGK Exchange Rate
276
[frequency] => Daily
277
[type] => Indicative
278
[units] => PGK
279
[source] => RBA
280
[publication_date] => 01-Oct-2024
281
[series_id] => FXRPNGK
282
[label] => PGK
283
)
284
285
[hkd] => Array
286
(
287
[title] => A$1=HKD
288
[description] => AUD/HKD Exchange Rate
289
[frequency] => Daily
290
[type] => Indicative
291
[units] => HKD
292
[source] => RBA
293
[publication_date] => 19-Feb-2026
294
[series_id] => FXRHKD
295
[label] => HKD
296
)
297
298
[cad] => Array
299
(
300
[title] => A$1=CAD
301
[description] => AUD/CAD Exchange Rate
302
[frequency] => Daily
303
[type] => Indicative
304
[units] => CAD
305
[source] => RBA
306
[publication_date] => 19-Feb-2026
307
[series_id] => FXRCD
308
[label] => CAD
309
)
310
311
[zar] => Array
312
(
313
[title] => A$1=ZAR
314
[description] => AUD/ZAR Exchange Rate
315
[frequency] => Daily
316
[type] => Indicative
317
[units] => ZAR
318
[source] => RBA
319
[publication_date] => 19-Feb-2026
320
[series_id] => FXRSARD
321
[label] => ZAR
322
)
323
324
[sar] => Array
325
(
326
[title] => A$1=SAR
327
[description] => AUD/SAR Exchange Rate
328
[frequency] => Daily
329
[type] => Indicative
330
[units] => SAR
331
[source] => RBA
332
[publication_date] => 01-Oct-2024
333
[series_id] => FXRSF
334
[label] => SAR
335
)
336
337
[chf] => Array
338
(
339
[title] => A$1=CHF
340
[description] => AUD/CHF Exchange Rate
341
[frequency] => Daily
342
[type] => Indicative
343
[units] => CHF
344
[source] => RBA
345
[publication_date] => 19-Feb-2026
346
[series_id] => FXRSF
347
[label] => CHF
348
)
349
350
[sek] => Array
351
(
352
[title] => A$1=SEK
353
[description] => AUD/SEK Exchange Rate
354
[frequency] => Daily
355
[type] => Indicative
356
[units] => SEK
357
[source] => RBA
358
[publication_date] => 19-Feb-2026
359
[series_id] => FXRSF
360
[label] => SEK
361
)
362
363
[ php ] => Array
364
(
365
[title] => A$1=PHP
366
[description] => AUD/PHP Exchange Rate
367
[frequency] => Daily
368
[type] => Indicative
369
[units] => PHP
370
[source] => RBA
371
[publication_date] => 19-Feb-2026
372
[series_id] => FXRPHP
373
[label] => PHP
374
)
375
376
[sdr] => Array
377
(
378
[title] => A$1=SDR
379
[description] => AUD/SDR Exchange Rate
380
[frequency] => Daily
381
[type] => Indicative
382
[units] => SDR
383
[source] => IMF
384
[publication_date] => 19-Feb-2026
385
[series_id] => FXRSDR
386
[label] => SDR
387
)
388
389
)
390
391
[label] => Array
392
(
393
[usd] => USD
394
[twi] => TWI
395
[cny] => CNY
396
[jpy] => JPY
397
[eur] => EUR
398
[krw] => KRW
399
[gbp] => GBP
400
[sgd] => SGD
401
[inr] => INR
402
[thb] => THB
403
[nzd] => NZD
404
[twd] => TWD
405
[myr] => MYR
406
[idr] => IDR
407
[vnd] => VND
408
[aed] => AED
409
[pgk] => PGK
410
[hkd] => HKD
411
[cad] => CAD
412
[zar] => ZAR
413
[sar] => SAR
414
[chf] => CHF
415
[sek] => SEK
416
[ php ] => PHP
417
[sdr] => SDR
418
)
419
420
[ notes ] => Array
421
(
422
[euro_conversion_rates] => Array
423
(
424
[BEF] => Array
425
(
426
[currency] => Belgian francs
427
[conversion] => 40.3399
428
)
429
430
[DEM] => Array
431
(
432
[currency] => Deutsche Mark
433
[conversion] => 1.95583
434
)
435
436
[EEK] => Array
437
(
438
[currency] => Estonian kroon
439
[conversion] => 15.6466
440
)
441
442
[IEP] => Array
443
(
444
[currency] => Irish pound
445
[conversion] => 0.787564
446
)
447
448
[GRD] => Array
449
(
450
[currency] => Greek drachmas
451
[conversion] => 340.75
452
)
453
454
[ESP] => Array
455
(
456
[currency] => Spanish pesetas
457
[conversion] => 166.386
458
)
459
460
[CYP] => Array
461
(
462
[currency] => Cyprus pound
463
[conversion] => 0.585274
464
)
465
466
[FRF] => Array
467
(
468
[currency] => French francs
469
[conversion] => 6.55957
470
)
471
472
[ITL] => Array
473
(
474
[currency] => Italian lire
475
[conversion] => 1936.27
476
)
477
478
[LVL] => Array
479
(
480
[currency] => Latvian lats
481
[conversion] => 0.702804
482
)
483
484
[LUF] => Array
485
(
486
[currency] => Luxembourg francs
487
[conversion] => 40.3399
488
)
489
490
[MTL] => Array
491
(
492
[currency] => Maltese lira
493
[conversion] => 0.4293
494
)
495
496
[NLG] => Array
497
(
498
[currency] => Dutch guilders
499
[conversion] => 2.20371
500
)
501
502
[ATS] => Array
503
(
504
[currency] => Austrian schillings
505
[conversion] => 13.7603
506
)
507
508
[PTE] => Array
509
(
510
[currency] => Portuguese escudos
511
[conversion] => 200.482
512
)
513
514
[SIT] => Array
515
(
516
[currency] => Slovenian tolars
517
[conversion] => 239.64
518
)
519
520
[SKK] => Array
521
(
522
[currency] => Slovak koruna
523
[conversion] => 30.126
524
)
525
526
[FIM] => Array
527
(
528
[currency] => Finnish markkas
529
[conversion] => 5.94573
530
)
531
532
)
533
534
[exchange_rates] => Array
535
(
536
[0] => Since 1 July 2008, the rate shown for the US dollar is the WM/Reuters Australian Dollar Fix at 4.00 pm (Sydney) on the day concerned, sourced from page AUDFIX on Thomson Reuters and rounded to four decimals. Prior to that, the rate shown for the US dollar was the Reserve Bank's observation of mid-points of buying and selling rates quoted at 4.00 pm (Sydney) on the day concerned. Rates shown for most other currencies are calculated by crossing the rate for the US dollar with the Reserve Bank’s observations of mid-points of buying and selling rates quoted around the same time. These rates are indications of market value only and may differ from those quoted by foreign exchange dealers and other market sources.
537
[1] => The trade-weighted index is calculated on the basis of the rates for the US dollar and other currencies. Details of the method of calculation of the trade-weighted index are set out in the Bulletin for October 2002 and current weights are on the Bank's website.
538
[2] => The value of the Special Drawing Right is calculated by the International Monetary Fund on the basis of a weighted basket of four currencies – US dollar, European euro, Japanese yen and UK pound. The Fund publishes the value of the SDR each day in terms of US dollars; the latest available rate is crossed with the 4.00 pm A$/US$ rate.
539
[3] => In January 1999, 11 countries that were members of the European Economic and Monetary Union (EMU) replaced their national currencies with the euro. These countries were Austria, Belgium, Finland, France, Germany, Ireland, Italy, Luxembourg, the Netherlands, Portugal and Spain. In subsequent years, additional countries have adopted the euro. Please refer to the table below for conversion rates.
540
)
541
542
)
543
544
)
You would only query the complete data periodically to update any significant changes.
Currency Graph: The currency conversion graph is used on our client websites only because we want them to consider our website to be a resource worth coming back to. Any asset that attracts customs has the capacity to convert them! Individual convesions may also be made. For example, One Australian Dollar currency buys $0.65 USD.
Basic Query Labels
Each 'basic' query may include the optional labels=1 parameter to return field descriptions and other data. For a single example, we'll query the RBA Cash Rate endpoint and include labels.
rba/json?apikey=api-key&action=rba_cash_rate&number=1&labels=1 returns the following:
1
Array
2
(
3
[status] => 200
4
[message] => Array
5
(
6
[0] => Success
7
[1] => 1 Results
8
[2] => Source: Reserve Bank of Australia (RBA)
9
)
10
11
[code] => 200
12
[data] => Array
13
(
14
[2026-02-18] => Array
15
(
16
[cash_rate_target] => 3.85
17
[change_cash_rate] => 0
18
[interbank_overnight_cash_rate] => 3.85
19
[interbank_highest_overnight] => 3.85
20
[interbank_lowest_overnight] => 3.85
21
[interbank_volume_overnight] => 1143
22
[interbank_number_overnight] => 10
23
[cash_rate_return_index] => 142.868690
24
[bank_bills_negotiables_one_month] => 3.81
25
[bank_bills_negotiables_one_three] => 3.99
26
[bank_bills_negotiables_one_six] => 4.26
27
[overnight_swap_index_one] => 0
28
[overnight_swap_index_three] => 0
29
[overnight_swap_index_six] => 0
30
[treasury_note_one] =>
31
[treasury_note_three] =>
32
[treasury_note_six] =>
33
)
34
35
)
36
37
[source] => Array
38
(
39
[source] => Reserve Bank of Australia (RBA)
40
[ link ] => https://www.rba.gov.au/statistics/tables/xls/f01d.xlsx
41
)
42
43
[labels] => Array
44
(
45
[cash_rate_target] => Array
46
(
47
[title] => Cash Rate Target
48
[description] => Cash Rate Target on date
49
[resolved] => Cash rate target
50
[frequency] => Daily
51
[type] => Original
52
[units] => Per cent
53
[source] => RBA
54
[publication_date] => 20-Feb-2026
55
[series_id] => FIRMMCRTD
56
)
57
58
[change_cash_rate] => Array
59
(
60
[title] => Change in the Cash Rate Target
61
[description] => Change in the Cash Rate Target (in percentage points)
62
[resolved] => Cash rate change
63
[frequency] => As announced
64
[type] => Original
65
[units] => Per cent
66
[source] => RBA
67
[publication_date] => 20-Feb-2026
68
[series_id] => FIRMMCCRT
69
)
70
71
[interbank_overnight_cash_rate] => Array
72
(
73
[title] => Interbank Overnight Cash Rate
74
[description] => Interbank Overnight Cash Rate on date
75
[resolved] => Overnight cash rate
76
[frequency] => Daily
77
[type] => Original
78
[units] => Per cent
79
[source] => RBA
80
[publication_date] => 20-Feb-2026
81
[series_id] => FIRMMCRID
82
)
83
84
[interbank_highest_overnight] => Array
85
(
86
[title] => Highest Interbank Overnight Cash Rate
87
[description] => Highest Interbank Overnight Cash Rate on date
88
[resolved] => Overnight cash high
89
[frequency] => Daily
90
[type] => Original
91
[units] => Per cent
92
[source] => RBA
93
[publication_date] => 20-Feb-2026
94
[series_id] => FIRMMCRIH
95
)
96
97
[interbank_lowest_overnight] => Array
98
(
99
[title] => Lowest Interbank Overnight Cash Rate
100
[description] => Lowest Interbank Overnight Cash Rate on date
101
[resolved] => Overnight cash low
102
[frequency] => Daily
103
[type] => Original
104
[units] => Per cent
105
[source] => RBA
106
[publication_date] => 20-Feb-2026
107
[series_id] => FIRMMCRIL
108
)
109
110
[interbank_volume_overnight] => Array
111
(
112
[title] => Volume of Cash Market Transactions
113
[description] => Volume of Interbank Overnight Cash Market Transactions on date
114
[resolved] => Cash market volume
115
[frequency] => Daily
116
[type] => Original
117
[units] => $m
118
[source] => RBA
119
[publication_date] => 20-Feb-2026
120
[series_id] => FIRMMCRIV
121
)
122
123
[interbank_number_overnight] => Array
124
(
125
[title] => Number of Cash Market Transactions
126
[description] => Number of Interbank Overnight Cash Market Transactions on date
127
[resolved] => Cash market trades
128
[frequency] => Daily
129
[type] => Original
130
[units] => Number
131
[source] => RBA
132
[publication_date] => 20-Feb-2026
133
[series_id] => FIRMMCRIN
134
)
135
136
[cash_rate_return_index] => Array
137
(
138
[title] => Total Return Index
139
[description] => Cash Rate Total Return Index on date
140
[resolved] => Cash rate TRI
141
[frequency] => Daily
142
[type] => Original
143
[units] => Index (04-Jan-2011=100)
144
[source] => RBA
145
[publication_date] => 20-Feb-2026
146
[series_id] => FIRMMCTRI
147
)
148
149
[bank_bills_negotiables_one_month] => Array
150
(
151
[title] => EOD 1-month BABs/NCDs
152
[description] => Bank Accepted Bills/Negotiable Certificates of Deposit – 1 month
153
[resolved] => BAB/NCD 1M
154
[frequency] => Daily
155
[type] => Original
156
[units] => Per cent
157
[source] => ASX
158
[publication_date] => 20-Feb-2026
159
[series_id] => FIRMMBAB30D
160
)
161
162
[bank_bills_negotiables_one_three] => Array
163
(
164
[title] => EOD 3-month BABs/NCDs
165
[description] => Bank Accepted Bills/Negotiable Certificates of Deposit – 3 months
166
[resolved] => BAB/NCD 3M
167
[frequency] => Daily
168
[type] => Original
169
[units] => Per cent
170
[source] => ASX
171
[publication_date] => 20-Feb-2026
172
[series_id] => FIRMMBAB90D
173
)
174
175
[bank_bills_negotiables_one_six] => Array
176
(
177
[title] => EOD 6-month BABs/NCDs
178
[description] => Bank Accepted Bills/Negotiable Certificates of Deposit – 6 months
179
[resolved] => BAB/NCD 6M
180
[frequency] => Daily
181
[type] => Original
182
[units] => Per cent
183
[source] => ASX
184
[publication_date] => 20-Feb-2026
185
[series_id] => FIRMMBAB180D
186
)
187
188
[overnight_swap_index_one] => Array
189
(
190
[title] => 1-month OIS
191
[description] => Overnight Indexed Swaps – 1 month
192
[resolved] => OIS 1M
193
[frequency] => Daily
194
[type] => Original
195
[units] => Per cent
196
[source] => FENICS
197
[publication_date] => 20-Feb-2026
198
[series_id] => FIRMMOIS1D
199
)
200
201
[overnight_swap_index_three] => Array
202
(
203
[title] => 3-month OIS
204
[description] => Overnight Indexed Swaps – 3 months
205
[resolved] => OIS 3M
206
[frequency] => Daily
207
[type] => Original
208
[units] => Per cent
209
[source] => FENICS
210
[publication_date] => 20-Feb-2026
211
[series_id] => FIRMMOIS3D
212
)
213
214
[overnight_swap_index_six] => Array
215
(
216
[title] => 6-month OIS
217
[description] => Overnight Indexed Swaps – 6 months
218
[resolved] => OIS 6M
219
[frequency] => Daily
220
[type] => Original
221
[units] => Per cent
222
[source] => FENICS
223
[publication_date] => 20-Feb-2026
224
[series_id] => FIRMMOIS6D
225
)
226
227
[treasury_note_one] => Array
228
(
229
[title] => 1-month Treasury Note
230
[description] => Treasury Note – 1 month
231
[resolved] => Treasury 1M
232
[frequency] => Daily
233
[type] => Original
234
[units] => Per cent
235
[source] => RBA
236
[publication_date] => 20-Feb-2026
237
[series_id] => FIRMMTN1D
238
)
239
240
[treasury_note_three] => Array
241
(
242
[title] => 3-month Treasury Note
243
[description] => Treasury Note – 3 month
244
[resolved] => Treasury 3M
245
[frequency] => Daily
246
[type] => Original
247
[units] => Per cent
248
[source] => RBA
249
[publication_date] => 20-Feb-2026
250
[series_id] => FIRMMTN3D
251
)
252
253
[treasury_note_six] => Array
254
(
255
[title] => 6-month Treasury Note
256
[description] => Treasury Note – 6 month
257
[resolved] => Treasury 6M
258
[frequency] => Daily
259
[type] => Original
260
[units] => Per cent
261
[source] => RBA
262
[publication_date] => 20-Feb-2026
263
[series_id] => FIRMMTN6D
264
)
265
266
)
267
268
[label] => Array
269
(
270
[cash_rate_target] => Cash Rate Target
271
[change_cash_rate] => Change in the Cash Rate Target
272
[interbank_overnight_cash_rate] => Interbank Overnight Cash Rate
273
[interbank_highest_overnight] => Highest Interbank Overnight Cash Rate
274
[interbank_lowest_overnight] => Lowest Interbank Overnight Cash Rate
275
[interbank_volume_overnight] => Volume of Cash Market Transactions
276
[interbank_number_overnight] => Number of Cash Market Transactions
277
[cash_rate_return_index] => Total Return Index
278
[bank_bills_negotiables_one_month] => EOD 1-month BABs/NCDs
279
[bank_bills_negotiables_one_three] => EOD 3-month BABs/NCDs
280
[bank_bills_negotiables_one_six] => EOD 6-month BABs/NCDs
281
[overnight_swap_index_one] => 1-month OIS
282
[overnight_swap_index_three] => 3-month OIS
283
[overnight_swap_index_six] => 6-month OIS
284
[treasury_note_one] => 1-month Treasury Note
285
[treasury_note_three] => 3-month Treasury Note
286
[treasury_note_six] => 6-month Treasury Note
287
)
288
289
)
In almost all cases, the 'labels' array includes the 'label' key which includes a truncated field suitable for graphing, and the 'labels' array returns that label in a simple plug-and-play 'Chart JS' array.
The API Helper
For advanced queries, and to a lesser extent the basic queries shown above, you'll need to know the 'RBA or other' Source, and the available fields associated with that source. The helper function returns all source data assigned to your account with the fields available for advanced queries.
The data is truncated to a fraction of its length for readability, so you should simply query the endpoint for a more comprehensive understanding. Each source assigned to your account is returned.
1
Array
2
(
3
[status] => 200
4
[message] => Array
5
(
6
[0] => Success
7
[1] => 10 Results
8
[2] => Source: Reserve Bank of Australia (RBA)
9
)
10
11
[code] => 200
12
[data] => Array
13
(
14
[rba_cash_rate] => Array
15
(
16
[fields] => Array
17
(
18
[0] => cash_rate_target
19
[1] => change_cash_rate
20
[2] => interbank_overnight_cash_rate
21
[3] => interbank_highest_overnight
22
[4] => interbank_lowest_overnight
23
[5] => interbank_volume_overnight
24
[6] => interbank_number_overnight
25
[7] => cash_rate_return_index
26
[8] => bank_bills_negotiables_one_month
27
[9] => bank_bills_negotiables_one_three
28
[10] => bank_bills_negotiables_one_six
29
[11] => overnight_swap_index_one
30
[12] => overnight_swap_index_three
31
[13] => overnight_swap_index_six
32
[14] => treasury_note_one
33
[15] => treasury_note_three
34
[16] => treasury_note_six
35
)
36
37
[labels] => Array
38
(
39
[cash_rate_target] => Array
40
(
41
[title] => Cash Rate Target
42
[description] => Cash Rate Target on date
43
[resolved] => Cash rate target
44
[frequency] => Daily
45
[type] => Original
46
[units] => Per cent
47
[source] => RBA
48
[publication_date] => 20-Feb-2026
49
[series_id] => FIRMMCRTD
50
)
51
52
[change_cash_rate] => Array
53
(
54
[title] => Change in the Cash Rate Target
55
[description] => Change in the Cash Rate Target (in percentage points)
56
[resolved] => Cash rate change
57
[frequency] => As announced
58
[type] => Original
59
[units] => Per cent
60
[source] => RBA
61
[publication_date] => 20-Feb-2026
62
[series_id] => FIRMMCCRT
63
)
64
65
[interbank_overnight_cash_rate] => Array
66
(
67
[title] => Interbank Overnight Cash Rate
68
[description] => Interbank Overnight Cash Rate on date
69
[resolved] => Overnight cash rate
70
[frequency] => Daily
71
[type] => Original
72
[units] => Per cent
73
[source] => RBA
74
[publication_date] => 20-Feb-2026
75
[series_id] => FIRMMCRID
76
)
77
78
[interbank_highest_overnight] => Array
79
(
80
[title] => Highest Interbank Overnight Cash Rate
81
[description] => Highest Interbank Overnight Cash Rate on date
82
[resolved] => Overnight cash high
83
[frequency] => Daily
84
[type] => Original
85
[units] => Per cent
86
[source] => RBA
87
[publication_date] => 20-Feb-2026
88
[series_id] => FIRMMCRIH
89
)
90
91
[interbank_lowest_overnight] => Array
92
(
93
[title] => Lowest Interbank Overnight Cash Rate
94
[description] => Lowest Interbank Overnight Cash Rate on date
95
[resolved] => Overnight cash low
96
[frequency] => Daily
97
[type] => Original
98
[units] => Per cent
99
[source] => RBA
100
[publication_date] => 20-Feb-2026
101
[series_id] => FIRMMCRIL
102
)
103
104
[interbank_volume_overnight] => Array
105
(
106
[title] => Volume of Cash Market Transactions
107
[description] => Volume of Interbank Overnight Cash Market Transactions on date
108
[resolved] => Cash market volume
109
[frequency] => Daily
110
[type] => Original
111
[units] => $m
112
[source] => RBA
113
[publication_date] => 20-Feb-2026
114
[series_id] => FIRMMCRIV
115
)
116
117
[interbank_number_overnight] => Array
118
(
119
[title] => Number of Cash Market Transactions
120
[description] => Number of Interbank Overnight Cash Market Transactions on date
121
[resolved] => Cash market trades
122
[frequency] => Daily
123
[type] => Original
124
[units] => Number
125
[source] => RBA
126
[publication_date] => 20-Feb-2026
127
[series_id] => FIRMMCRIN
128
)
129
130
[cash_rate_return_index] => Array
131
(
132
[title] => Total Return Index
133
[description] => Cash Rate Total Return Index on date
134
[resolved] => Cash rate TRI
135
[frequency] => Daily
136
[type] => Original
137
[units] => Index (04-Jan-2011=100)
138
[source] => RBA
139
[publication_date] => 20-Feb-2026
140
[series_id] => FIRMMCTRI
141
)
142
143
[bank_bills_negotiables_one_month] => Array
144
(
145
[title] => EOD 1-month BABs/NCDs
146
[description] => Bank Accepted Bills/Negotiable Certificates of Deposit – 1 month
147
[resolved] => BAB/NCD 1M
148
[frequency] => Daily
149
[type] => Original
150
[units] => Per cent
151
[source] => ASX
152
[publication_date] => 20-Feb-2026
153
[series_id] => FIRMMBAB30D
154
)
155
156
[bank_bills_negotiables_one_three] => Array
157
(
158
[title] => EOD 3-month BABs/NCDs
159
[description] => Bank Accepted Bills/Negotiable Certificates of Deposit – 3 months
160
[resolved] => BAB/NCD 3M
161
[frequency] => Daily
162
[type] => Original
163
[units] => Per cent
164
[source] => ASX
165
[publication_date] => 20-Feb-2026
166
[series_id] => FIRMMBAB90D
167
)
168
169
[bank_bills_negotiables_one_six] => Array
170
(
171
[title] => EOD 6-month BABs/NCDs
172
[description] => Bank Accepted Bills/Negotiable Certificates of Deposit – 6 months
173
[resolved] => BAB/NCD 6M
174
[frequency] => Daily
175
[type] => Original
176
[units] => Per cent
177
[source] => ASX
178
[publication_date] => 20-Feb-2026
179
[series_id] => FIRMMBAB180D
180
)
181
182
[overnight_swap_index_one] => Array
183
(
184
[title] => 1-month OIS
185
[description] => Overnight Indexed Swaps – 1 month
186
[resolved] => OIS 1M
187
[frequency] => Daily
188
[type] => Original
189
[units] => Per cent
190
[source] => FENICS
191
[publication_date] => 20-Feb-2026
192
[series_id] => FIRMMOIS1D
193
)
194
195
[overnight_swap_index_three] => Array
196
(
197
[title] => 3-month OIS
198
[description] => Overnight Indexed Swaps – 3 months
199
[resolved] => OIS 3M
200
[frequency] => Daily
201
[type] => Original
202
[units] => Per cent
203
[source] => FENICS
204
[publication_date] => 20-Feb-2026
205
[series_id] => FIRMMOIS3D
206
)
207
208
[overnight_swap_index_six] => Array
209
(
210
[title] => 6-month OIS
211
[description] => Overnight Indexed Swaps – 6 months
212
[resolved] => OIS 6M
213
[frequency] => Daily
214
[type] => Original
215
[units] => Per cent
216
[source] => FENICS
217
[publication_date] => 20-Feb-2026
218
[series_id] => FIRMMOIS6D
219
)
220
221
[treasury_note_one] => Array
222
(
223
[title] => 1-month Treasury Note
224
[description] => Treasury Note – 1 month
225
[resolved] => Treasury 1M
226
[frequency] => Daily
227
[type] => Original
228
[units] => Per cent
229
[source] => RBA
230
[publication_date] => 20-Feb-2026
231
[series_id] => FIRMMTN1D
232
)
233
234
[treasury_note_three] => Array
235
(
236
[title] => 3-month Treasury Note
237
[description] => Treasury Note – 3 month
238
[resolved] => Treasury 3M
239
[frequency] => Daily
240
[type] => Original
241
[units] => Per cent
242
[source] => RBA
243
[publication_date] => 20-Feb-2026
244
[series_id] => FIRMMTN3D
245
)
246
247
[treasury_note_six] => Array
248
(
249
[title] => 6-month Treasury Note
250
[description] => Treasury Note – 6 month
251
[resolved] => Treasury 6M
252
[frequency] => Daily
253
[type] => Original
254
[units] => Per cent
255
[source] => RBA
256
[publication_date] => 20-Feb-2026
257
[series_id] => FIRMMTN6D
258
)
259
260
)
261
262
[label] => Array
263
(
264
[cash_rate_target] => Cash Rate Target
265
[change_cash_rate] => Change in the Cash Rate Target
266
[interbank_overnight_cash_rate] => Interbank Overnight Cash Rate
267
[interbank_highest_overnight] => Highest Interbank Overnight Cash Rate
268
[interbank_lowest_overnight] => Lowest Interbank Overnight Cash Rate
269
[interbank_volume_overnight] => Volume of Cash Market Transactions
270
[interbank_number_overnight] => Number of Cash Market Transactions
271
[cash_rate_return_index] => Total Return Index
272
[bank_bills_negotiables_one_month] => EOD 1-month BABs/NCDs
273
[bank_bills_negotiables_one_three] => EOD 3-month BABs/NCDs
274
[bank_bills_negotiables_one_six] => EOD 6-month BABs/NCDs
275
[overnight_swap_index_one] => 1-month OIS
276
[overnight_swap_index_three] => 3-month OIS
277
[overnight_swap_index_six] => 6-month OIS
278
[treasury_note_one] => 1-month Treasury Note
279
[treasury_note_three] => 3-month Treasury Note
280
[treasury_note_six] => 6-month Treasury Note
281
)
282
283
)
284
285
[rba_inflation] => Array
286
(
287
[fields] => Array
288
(
289
[0] => cpi
290
[1] => year_inflation
291
[2] => year_inflation_exclude_interest_tax
292
[3] => year_inflation_exclude_volatile_terms
293
[4] => year_tradables_inflation
294
[5] => year_tradables_exclude_volatile_terms_tobacco
295
[6] => year_non_tradables_inflation
296
[7] => year_non_tradable_exclude_interest_deposit_loan
297
[8] => year_weighted_median_inflation
298
[9] => year_trimmed_mean_inflation
299
[10] => quarterly_inflation_original
300
[11] => quarterly_inflation
301
[12] => quarterly_inflation_exlude_interest_tax
302
[13] => quarterly_inflation_exclude_volatile_terms
303
[14] => quarterly_tradables_inflation
304
[15] => quarterly_tradables_exclude_volatile_tobacco
305
[16] => quarterly_non_tradables_inflation
306
[17] => quarterly_non_tradables_inflation_exclude_deposit_loans
307
[18] => quarterly_weighted_median_inflation
308
[19] => quarterly_trimmed_mean_inflation
309
)
310
311
[labels] => Array
312
(
313
[cpi] => Array
314
(
315
[title] => Consumer price index
316
[description] => Consumer price index; All groups
317
[label] => CPI
318
[frequency] => Quarterly
319
[type] => Original
320
321
[ ... SNIP ... ]
322
323
[frequency] => Monthly
324
[units] => Per cent per annum
325
[series_id] => PDRNTT
326
)
327
328
[deposit_new_term_households] => Array
329
(
330
[title] => Deposit rates; New; Term Deposits; Households
331
[description] => Weighted average interest rate paid to households on all new term deposits
332
[label] => New Term Households
333
[frequency] => Monthly
334
[units] => Per cent per annum
335
[series_id] => PDRNTH
336
)
337
338
[deposit_new_term_institutions] => Array
339
(
340
[title] => Deposit rates; New; Term Deposits; Institutions
341
[description] => Weighted average interest rate paid to institutions on all new term deposits
342
[label] => New Term Institutions
343
[frequency] => Monthly
344
[units] => Per cent per annum
345
[series_id] => PDRNTI
346
)
347
348
)
349
350
[label] => Array
351
(
352
[deposit_outstanding_total] => Outstanding Total
353
[deposit_outstanding_households] => Outstanding Households
354
[deposit_outstanding_institutions] => Outstanding Institutions
355
[deposit_outstanding_atcall_total] => Outstanding At-call Total
356
[deposit_outstanding_atcall_households] => Outstanding At-call Households
357
[deposit_outstanding_atcall_institutions] => Outstanding At-call Institutions
358
[deposit_outstanding_term_total] => Outstanding Term Total
359
[deposit_outstanding_term_households] => Outstanding Term Households
360
[deposit_outstanding_term_institutions] => Outstanding Term Institutions
361
[deposit_new_term_total] => New Term Total
362
[deposit_new_term_households] => New Term Households
363
[deposit_new_term_institutions] => New Term Institutions
364
)
365
366
)
367
368
)
369
370
)
The labels array includes all data provided by the RBA for compliance and completeness.
Avdanced Queries
Advanced queries will allow you to compare once source of data against another, and more meaningful trends can be extracted for clear analytical use. The use of the helper query is necessary before most of the advanced queries can be used.
It get complex. You may also join onto the comparison table, rates (lender data) tables, and other data sources in order to build a much higher level of understanding. We've only returned what we consider to be the 'top-20' endpoints, although we'll get to formal documentation at some point in the future.
Note that labels, notes, and other peripheral information is not available via advanced queries.
RBA Queries [ rba ]
The rba action is mostly a catch-all query that extracts most basic data via a single and more manageable endpoint.
For example, rba/json?apikey=your-api-key&action=rba&rba=rba_cash_rate&fields=cash_rate_target,interbank_overnight_cash_rate&number=2 returns the following:
The rba parameter is the primary source of data, while the fields are 'children' of the source (all listed in the helper package). All the basic queries may be actioned via this common endpoint.
Data Date Ranges [ first_last ]
Data date ranges are actioned via the action of first_last. The helper simply returns the earliest and most recent record. You'll be required to provide a source ('rba') and a child field ('fields'). Querying rba/json?apikey=api=key&action=first_last&rba=rba_inflation&fields=year_inflation returns:
Daily Delta [ daily_delta ]
The daily_delta action calculates day-to-day changes in RBA data for a given field. It first retrieves the full dataset for the requested table and field, then loops through each date in order, comparing the current value to the previous day’s value. For each day, it records both the actual value and the difference from the previous day, rounded to two decimal places. The result is a simple, structured dataset that makes it easy to see how interest rates, deposit rates, or other RBA metrics move day by day, helping analysts and developers quickly identify trends, spikes, or drops over time without manually calculating differences.
Querying rba/json?apikey=api-key&action=daily_delta&rba=rba_inflation&fields=cpi returns:
The change indicates the delta from (in this case) one quarter to the next.
Data Rolling Averages [ rolling_averages ]
The rolling_averages action calculates a moving (or rolling) average for a given RBA data series. It first fetches the full dataset for the requested source and field, then steps through each date in order. For each date, it keeps a running “window” of the most recent N values (default is 3), calculates the average of those values, and stores it alongside the actual value for that date. The function returns an associative array keyed by date, where each entry contains two items: 'value' – the actual data point from the RBA dataset for that date, and 'rolling_avg' – the average of that data point and the preceding N−1 points. For example, if the window is 3, the rolling average for March would be the mean of January, February, and March.
This matters because it smooths short-term fluctuations, making trends and patterns easier to see. Analysts can quickly identify whether interest rates, deposit rates, or other metrics are generally rising, falling, or stable over a defined period, rather than reacting to individual spikes or drops in the raw data. The API provides a more meaningful view of trends, which can be directly applied to reports or automated decision-making tools.
This query introduces the parameter of 'window' (in this case, defaults to 3). Querying rba/json?apikey=api-key&action=rolling_averages&rba=rba_inflation&fields=cpi&window=3. Like all advanced function, the trend may be applied to any source and field. The result:
Field Spread [ field_spread ]
The field_spread response tells you how two related RBA metrics compare on any given date. For each date, it shows the values of both fields and the difference between them, so you can immediately see where one is higher or lower than the other. For example, you could track the spread between owner-occupier and investor mortgage rates, or see how advertised deposit rates compare to what people actually earn. This is useful for spotting trends, understanding lender behaviour, and making decisions based on relative costs—so instead of just seeing raw numbers, you can quickly interpret what the gap between these metrics means for borrowers, investors, or savers.
While not monetary policy related, we'll look at the spread of term deposits (across a single source). Querying rba/json?apikey=api=key&action=field_spread&rba=rba_advertised_deposit_rates&fields=term_deposits_3m,term_deposits_1y returns the following:
The spread is most often applied to cash rates and consumer rates, or cash rates and interbank variables.
RBA Comparisons [ rba_compare ]
The rba_compare action permits you to combine data from two different RBA sources on the same dates, so you can see multiple metrics side by side. For each date, it returns a single record containing values from both tables, aligned by the date. For users, this is valuable because it allows direct comparison across datasets. For example, you could compare investor mortgage rates with owner-occupier rates, or track lending rates alongside household debt levels, without manually matching dates. By seeing the numbers together, you can quickly identify relationships, trends, or divergences that would be hard to spot when looking at each dataset separately. This makes the data more actionable, letting you analyse how different parts of the financial system move together, spot anomalies, or build models that rely on multiple indicators at once.
When querying, we provide two sources with the 'rba' parameter, and any number of child fields associated with each source. Reference to the helper package will be required. For our example, we'll query: rba/json?apikey=api-key&action=rba_compare&rba=rba_cash_rate,rba_inflation&fields=cash_rate_target,interbank_overnight_cash_rate&field=cpi,year_inflation (not necessarily a sensible query). The result:
Remember, 1000 results are returned if you don't include a number parameter. It can get messy.
Segment Ranking [ segment_ranking ]
The segment_ranking action ranks multiple data fields for each date, showing which segments are highest to lowest. For example, if you are looking at different types of lending rates, deposit rates, or debt measures, this function produces an array for each date that lists the values in order from largest to smallest. For users, this is valuable because it lets you see at a glance which segments dominate at any point in time. Rather than manually scanning numbers, you can quickly identify trends such as which loan type carries the highest rates, which investment category is growing fastest, or which segment is contributing most to overall change. This makes it easier to compare performance, track relative movement, and make informed decisions based on the hierarchy of values in the data.
Real Lending Rates [ real_lending_rate ]
The real_lending_rate action calculates the real interest rate on loans, which is the borrowing cost after accounting for inflation. It takes the nominal lending rate (the rate banks charge) and subtracts the inflation rate (from the CPI) to show what the loan really costs in terms of purchasing power.
For each date, the function returns:
- 'nominal' – the rate you actually see advertised or charged on loans
- 'cpi' – the inflation rate at that time, showing how prices in the economy are rising
- 'real_rate' – the difference between the two, representing the true cost of borrowing
Why it matters: the nominal rate alone doesn’t tell you how expensive a loan really is, because inflation reduces the value of money over time. For example, a 5% loan in a 3% inflation environment has a real cost of only 2%, meaning money is effectively cheaper than it looks. This data helps users understand the true burden of borrowing over time, compare periods of high or low inflation, and make more informed decisions about loans or investment timing.
The rba parameter in this case is a lending field (we'll use rba_bank_rates for our example), and we require a child field, in this case outstanding_oo_al_li. We can also assign a specific inflation source, but we've 'hard-coded' it for simplicity.
Querying rba/json?apikey=api-key&action=real_lending_rate&rba=rba_bank_rates&fields=outstanding_oo_al_li returns:
Compute Spread [ compute_spread ]
The compute_spread action calculates the difference between two related rates or values in the same RBA dataset, returning the gap alongside the original numbers for each date. For example, you might compare a term deposit rate (high) to an at-call savings rate (low), or two different loan rates. For each date, the function provides:
- The value of the higher-rate field (field_high)
- The value of the lower-rate field (field_low)
- The spread, which is the difference between them
Why it matters: the spread shows how much extra is being charged or paid above a baseline, giving insight into pricing power, risk premiums, or lender margins. In practical terms, it helps users see how banks reward different products, identify trends in competitiveness, and understand where borrowers or savers may be gaining or losing relative to standard rates. It makes comparisons instant and actionable, without manually subtracting numbers or matching dates.
Querying action=compute_spread&rba=rba_bank_rates&fields=outstanding_oo_repayment_io&field=outstanding_oo_variable_ai (where field - as opposed to fields) - is the second child field. The result:
In short, the data shows the gap between two rates or products over time, letting you quickly see margins, premiums, or competitive spreads without manual calculations.
The Lending Deposit Gap [ lending_deposit_gap ]
The lending_deposit_gap action measures the difference between what banks charge borrowers (lending rates) and what they pay savers (deposit rates) for each date. It returns both the raw values and the spread, showing how much extra banks earn from lending compared to their funding costs. For users, this is effectively a proxy for bank profitability or net interest margin—without needing access to bank financial statements. A wider gap indicates banks are earning more from lending relative to deposits, while a narrower gap shows margins are tighter. This information is useful for investors, analysts, or anyone tracking banking conditions, because it highlights trends in core banking profits and market pricing power over time.
Querying action=lending_deposit_gap&rba=rba_bank_rates&rbax=rba_advertised_deposit_rates&fields=outstanding_oo_variable_ai&field=savings_bonus_banks_10000 returns:
In summary, the action shows the gap between what banks charge borrowers and pay savers, giving a quick view of lending margins and core bank profitability over time.
Read Deposit Versus CPI [ real_deposit_cpi ]
The real_deposit_cpi action calculates the real return on deposits by subtracting inflation (CPI) from the nominal deposit rate. For each date, it shows:
- The actual deposit rate paid by banks
- The inflation rate at that time
- The real deposit rate, which represents the true growth of your savings after accounting for rising prices
For users, this is valuable because a nominal deposit rate alone can be misleading—if inflation is higher than the rate you earn, your money is effectively losing purchasing power. This action makes it easy to see whether your savings are truly keeping pace with inflation, helping investors, savers, or analysts understand the real value of deposits over time.
Querying action=real_deposit_cpi&rba=rba_advertised_deposit_rates&fields=savings_bonus_banks_10000 returns:
Summary: This action shows how deposit returns compare to inflation, giving a clear view of the real growth (or decline) of your savings over time.
Top Movers [ top_movers ]
The top_movers action identifies the largest changes in selected RBA data between periods. For each date, it calculates how much each field has increased or decreased compared to the previous date and ranks the top N movers, either in the upward or downward direction. For users, this is valuable because it highlights the most significant shifts in the data, whether that’s inflation spikes, interest rate changes, or other metrics. Positive numbers indicate increases (e.g., rising inflation), negative numbers indicate decreases (e.g., deflation), and zeros indicate no change or missing data. By showing the fields that move the most, this function helps analysts, investors, or policymakers quickly spot emerging trends, market pressures, or unusual swings without manually comparing numbers across periods.
Querying action=top_movers&rba=rba_inflation&fields=year_inflation,year_tradables_inflation&direction=up returns the following. Note the inclusion of the direction parameter (accepts both 'up' and 'down', and defaults to 'up').
Summary: This function ranks the biggest changes in your selected RBA metrics each period, letting you quickly spot emerging trends, spikes, or declines.
Period Volitility [ volatility ]
The api_rba_volatility_analysis function measures the rolling volatility of a numeric RBA field, showing how much the values fluctuate over a specified window of periods (default is 3). For each date, it computes the sample standard deviation of the most recent values in the rolling window, capturing the short-term variability in the data. The function returns, for each date:
- 'value' – the actual value of the field on that date
- 'volatility' – the calculated standard deviation, showing the degree of fluctuation
- 'percent' – volatility expressed as a decimal percentage
- 'percent_readable' – volatility formatted as a percentage string for easy interpretation
Key points for your use:
- Volatility tells you how consistent or erratic a metric is over time. High volatility means the value is swinging a lot from period to period, while low volatility indicates stability.
- The rolling window ensures you’re always looking at the most recent set of data points, so the measure adapts as conditions change.
- It’s useful for risk assessment, trend analysis, and anomaly detection, letting users identify periods of unusual movement in interest rates, inflation, deposit rates, or other metrics.
- The function automatically handles missing values and zeros, carrying forward previous values when needed, so the results are robust even with incomplete data.
Querying action=volatility&rba=rba_inflation&fields=year_inflation returns the following:
Summary: This function calculates rolling volatility for any RBA metric, showing how much values fluctuate over time so you can spot instability, trends, or unusual swings.
Data Correlation [ correlation ]
The correlation action calculates the relationship between two numeric RBA series over time, showing whether they move together or independently. For each date, it aligns values from two tables and computes a rolling correlation over a defined window (default 12 periods), along with additional context such as the difference between the values, their rolling means, and their volatility. For users, this is valuable because it reveals how strongly two metrics are related:
- A correlation close to +1 means the two series move closely in the same direction.
- A correlation close to -1 means they move in opposite directions.
- A correlation near 0 means there’s little or no consistent relationship.
Alongside correlation, the function provides the raw values, their difference, rolling means, and rolling volatility - allowing users to see both the trend and the variability of each series. This is useful for analysts, investors, or policymakers who want to:
- Compare lending and deposit rates
- Study inflation versus specific loan types
- Understand co-movements in financial indicators without manually aligning datasets
In short, it’s a tool for spotting linked trends, divergences, and risk patterns across multiple RBA metrics, helping users make data-driven decisions or identify leading/lagging relationships in the financial system.
Querying action=correlation&rba=rba_cash_rate&rbax=rba_inflation&fields=cash_rate_target&field=year_inflation returns:
Summary: This function measures how two RBA metrics move together over time, showing correlation, differences, and volatility so you can spot linked trends, divergences, or risk patterns.
Graphing Options
As with the Xena 'Basic API', appending graph=1 to the query URL will return the full graph embed code for Chart JS (the library we use on your website), with the data assigned to the 'graph' key in the returned JSON. You can expect a universal website shortcode function and Elementor widget shortly that'll return one of the millions of graph options with the simple point-and-click method.
Your Website Includes Large Amounts of Graphing Options: Your website includes dozens of default graph options that are controlled by simple shortcode or managed via an Elementor widget. Grpahs makes your website come alive with useful dynamic content that fuels your funnels with relevance and expertise.
Some of the graphing options are detailed in the FAQ Module.
Conclusion
Access to high-quality economic data is no longer a differentiator on its own. What determines performance is how that data is structured, analysed, and applied. The functions described above are designed to turn raw Reserve Bank of Australia datasets into measurable signals changes, spreads, rankings, volatility, real rates, and correlations, that directly support decision-making.
For businesses operating in competitive funnels, on data-driven websites, or delivering insights to customers, this level of analysis is not optional. Users expect context, comparison, and interpretation, not static numbers. Rolling averages smooth noise, spreads reveal margins and pricing power, real rates expose true costs and returns, volatility highlights risk, and correlation shows how indicators interact across the economy. Together, these tools convert historical data into actionable intelligence.
Organisations that can surface these insights clearly through charts, email marketing, general content, and explanations, retain attention longer, communicate authority, and support better outcomes for their customers. In practical terms, this data enables stronger forecasting, clearer storytelling, and more credible recommendations. In a market where most participants rely on headline figures, the ability to quantify relationships and dynamics beneath the surface is what allows businesses to stand out, perform through the funnel, and deliver insight that users can trust and act on.
Featured Image: Sydney's RBA Building, 6 February 1963, this black-and-white negative looks south-west along Macquarie Street toward the Reserve Bank of Australia Building under construction at 215 Macquarie Street. The site is enclosed by hoarding, with a temporary site office perched at first-floor level. Street life continues in the foreground: a Ford Zephyr (registration BYC 154) travels south, while a Holden taxi and a Volkswagen pickup wait at the pedestrian crossing. Construction of the Reserve Bank’s Sydney head office was undertaken by E A Watts Pty Ltd in the early 1960s. The building’s distinctive modernist form rose through 1963–64, with completion achieved in 1964 and official opening in early 1965. This image captures the project during a key phase of construction, just before the façade and interior works were finalised. [
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