22 Apr 2026
Hire vehicle rates vary by location, vehicle class, provider and date. That variation is entirely normal. The real difficulty is that, in the absence of any published standard, parties to a dispute are left to search the market for the figure that best supports their position.
Standard Rates™ is intended to address that problem.
At its core, Standard Rates™ is an open standard for calculating a reference rate using a defined and published methodology. It is not a black box. It does not depend on a hidden formula, an undisclosed weighting system, or an artificial intelligence model that cannot be properly explained. The methodology is intended to be transparent, reviewable and capable of improvement over time.
That matters. A standard that cannot be inspected will always invite suspicion. A standard that can be read, tested and challenged stands a far better chance of earning industry confidence.
Hire Rates has operated since 2016. Over that time, we have worked extensively with market rate data and with participants across the credit hire ecosystem, including credit hire providers, insurers and legal representatives. One lesson has remained constant: where there is no agreed reference point, disputes naturally gravitate toward selective market evidence. That is not necessarily improper. It is simply the predictable consequence of a system without a common standard.
The idea behind Standard Rates™ draws on a principle long understood in the technology world: open standards tend to produce better outcomes than closed ones. When a methodology is visible, it can be scrutinised. Weaknesses can be identified. Assumptions can be tested. Sensible improvements can be proposed. Over time, that process strengthens both the standard itself and confidence in its use.
Our intention is for Standard Rates™ to be impartial in design and practical in operation. It is not intended to favour claimants over defendants, or insurers over credit hire providers. It is intended to provide a consistent, explainable and auditable reference point grounded in observable market data.
Just as importantly, openness requires humility. Data will not always produce the answer a particular party hopes to see. That is the nature of evidence. Where there are additional relevant data sources that ought properly to be considered, they should be identified, assessed and, where appropriate, incorporated through a transparent process. A credible standard must be capable of improvement, but not manipulation.
Without a common reference point, each side is encouraged to locate the rate most favourable to its position. That is an inefficient way to resolve disputes, and it does little to promote consistency or confidence in outcomes.
A published standard will not eliminate disagreement altogether, nor will it produce a perfect figure in every case. What it can do is provide a neutral starting point that reduces the scope for selective use of market data and helps shift the discussion from advocacy to methodology.
There will be occasions where a party could have obtained a more favourable figure by searching elsewhere. Equally, there will be occasions where the standard protects that same party from a less favourable market position. Over time, the discipline of using a common standard is likely to produce a fairer and more efficient overall result than the current practice of competing cherry-picked comparisons.
A rate should not have to be accepted on trust alone. If Standard Rates™ is to be relied upon in negotiations, litigation or expert analysis, the basis for the figure must be capable of being explained clearly and checked independently.
That is why the methodology should be published openly. Openness does not weaken a standard; it strengthens it. A transparent methodology allows the industry to test its logic, identify errors, challenge assumptions and suggest refinements. It also makes the resulting figure easier to defend, because the calculation process can be examined rather than merely asserted.
In practical terms, auditability matters as much as transparency. It should be possible to identify the inputs used, the methodology applied, the version of the standard relied upon, and the reasoning behind any future amendments. That is how confidence is built.
A standard only serves its purpose if it is used consistently. It should not become another figure to be adopted when convenient and ignored when inconvenient.
The value of a standard lies not only in whether it is theoretically optimal in every instance, but in whether it is applied in a disciplined and even-handed way across cases. In commercial and legal settings, consistency is often more valuable than a perpetual search for a supposedly perfect answer.
From a statistical and practical standpoint, a consistently applied standard is likely to produce better long-term outcomes than an environment in which every matter becomes a fresh contest over which market rate should be preferred. The objective is not perfection in the abstract. It is a fair, workable and repeatable approach that the industry can understand and rely upon.
Standard Rates™ is intended to evolve. The methodology should improve as the industry engages with it, tests it and contributes to it.
Constructive input is welcome from all parts of the credit hire community, including providers, insurers, solicitors, barristers and other professionals working in the field. The aim is not to entrench a fixed position for its own sake. The aim is to develop a standard that is methodologically sound, commercially sensible and robust enough to withstand scrutiny.
That is the central question: not whether a first version is flawless, but whether the standard can be built, reviewed and improved in a way that ultimately serves the industry better than the absence of any standard at all.
Hire Rates has a database which, at the time of writing, contains more than 130 million rates across Australia and New Zealand. The following describes the logic used to generate Standard Rates™.
Standard Rates™ are generated for the 7 Australian capital cities and selected regional centres.
For each location, we use the epicentre of that city or town and apply a search radius of:
The purpose of this search radius is to capture the practical local hire market for that location, rather than a narrow subset of branches.
Using Melbourne as an example, a 30 km radius from the CBD captures a substantial portion of the metropolitan area. It extends well beyond the inner city and includes the bulk of suburban branch locations. Supporting Google Maps images can be provided to show the relevant capital city, the applicable radius, and the branch locations within it. Viewed this way, it is clear that the bulk of locations are included within the search area.
Airport and CBD locations are included within Standard Rates™ where they fall within the applicable search radius.
Airport and CBD locations are often more expensive than suburban locations. That is unsurprising. They commonly include concession fees, premium site costs and similar location-based charges, which can materially increase the hire price.
Some take the view, based on their interpretation of Miller v McKnight, that airport or CBD locations should be excluded altogether. Others take the view that those locations can remain in scope, but that premium location surcharges should somehow be stripped out.
From a practical and data-driven perspective, I take a different view.
The better approach is to include both airport/CBD and non-airport/non-CBD locations, and let the market distribution speak for itself.
Take a simple example.
Assume there is one airport near a capital city, with 5 airport branches or kiosks. Assume those branches produce 10 rates each for a particular day. That gives 50 relatively expensive airport rates.
Now assume that, within the wider search radius, there are 50 suburban or general branch locations. If each of those also produces 10 rates, that gives 500 relatively cheaper non-airport rates. Combined, there are now 550 rates in the dataset. The median will sit within the much larger body of non-airport rates, not within the smaller pool of airport rates. In that scenario, the premium location charges do not distort the result because they do not control the middle of the market.
Now take the opposite scenario. Assume there are no hires available outside the airport. In real life, if the only available cars are at the airport, that is the market. A consumer cannot say, “I will hire this airport vehicle, but I refuse to pay the airport-related charges.” If the airport is the only available source, then the airport price is the real available market price. In that case, if only airport rates exist, the median will properly reflect those airport rates.
For that reason, I consider it more realistic to include both airport and non-airport rates, rather than excluding parts of the market in advance. Where there is broad suburban availability, premium locations will usually be outweighed in the median. Where there is not, the airport price may be the real market price. Including both better reflects the reality of hiring a car in the market as it actually exists on that day.
Standard Rates™ are generated for each day. We only include rates for hires starting on the same date as the hire start date being assessed.
This ensures the output is tied to the actual commencement date of the hire, rather than mixing in rates for different start dates which may reflect different market conditions.
We first include rates harvested on the same day that the hire starts.
If fewer than 10 rates are found, we then include rates harvested up to 7 days in advance of the hire start date, provided those rates still relate to hires commencing on that same hire start date.
If no rates are found, we use the median of the rates from 7 days before and 7 days after.
In our experience, rates harvested in advance are not systematically cheaper or more expensive than rates harvested on the day itself. Where same-day data is limited, including advance-harvested rates for the same hire start date gives a larger and more workable sample without changing the underlying hire commencement date being measured.
We use the FCAI classification system.
There are arguments that the FCAI system is not always perfect. In my experience, it works well in the smaller and cheaper vehicle categories. It becomes less precise in the higher-end categories, particularly where a single class may contain vehicles with very large differences in value. As one example, a large passenger vehicle category may include vehicles worth around $120,000 as well as vehicles worth several hundred thousand dollars. That is a genuine classification issue.
This can sound counterintuitive, but smaller classification differences often do not materially affect outcomes in the long run if the same standard is applied consistently.
For example:
For the purpose of illustration, assume the Corolla rates are cheaper and the BMW and Mercedes rates are more expensive.
Now assume, for the sake of argument, that the Corolla were reclassified into the same category as the BMW and Mercedes vehicles. At first glance, one might say that this is unfair because the Corolla would now be associated with higher-value vehicles. But the opposite effect also occurs: the inclusion of the Corolla would reduce the rates across that more expensive category. In other words, there may be a gain on one side of the category and a loss on the other.
So while classification is important, it is not always critical to the final outcome in every category, provided the standard is applied consistently. The larger concern is not minor boundary questions. It is the genuinely broad classifications at the top end of the market, where underlying vehicle values and market positions differ materially.
The following link is to the Hire Rates Standards repository on GitHub. It shows the logic of the database query used to generate the above methodology. I appreciate that the code will not run without access to the underlying database. Even so, if any part of the query logic appears incorrect, I welcome that feedback. We can test suggested changes and share the high-level outcomes.