Automated decisions and your privacy policy: what the 10 December 2026 rule means for Australian credit funds.
Important takeaways.
- From 10 December 2026, APP 1.7 to 1.9 of the Privacy Act require an APP entity to disclose in its privacy policy where a computer program is used to make, or to do something substantially and directly related to making, a decision that could reasonably be expected to significantly affect an individual's rights or interests.
- It is a transparency obligation, not a prohibition. Nothing in it stops a fund using AI in credit work; it requires the fund to be able to say where AI sits.
- Human sign-off does not automatically put a system out of scope. The OAIC's May 2026 issues paper proposes that a program is caught where it is a key factor in facilitating the human decision-maker's decision, which reaches scoring, ranking and recommendation steps that a person then approves.
- Whether a credit fund is caught turns on individuals rather than on borrowers. Corporate lending can still involve decisions about directors, guarantors and beneficial owners, while a non-bank lender assessing consumer or small business applications should assume it is in scope.
- The obligation applies regardless of when the system was built, so legacy scorecards and rule-based spreadsheets are caught on the same terms as recent AI workflows.
- The preparation is a map of decisions rather than an inventory of tools: which decisions significantly affect an individual, what personal information feeds each one, and whether a program decides or contributes.
On 10 December 2026 a new transparency obligation commences in Australian Privacy Principle 1. Where an APP entity has arranged for a computer program to make a decision, or to do something substantially and directly related to making one, and personal information about an individual is used in that program, the entity must say so in its privacy policy.
It is a disclosure rule, not a ban, and it is narrower than the headlines suggest. It is also wider than most credit funds assume in one specific respect: a person signing the final decision does not automatically take the system out of scope.
What actually commences on 10 December 2026.
The obligation was inserted into the Privacy Act 1988 by the Privacy and Other Legislation Amendment Act 2024, which received assent on 10 December 2024. The relevant provisions, APP 1.7 to 1.9, take effect two years later.
APP 1.7 sets the trigger: a computer program, personal information about an individual used in its operation, and a decision that could reasonably be expected to significantly affect that individual's rights or interests. APP 1.8 sets the content: the kinds of personal information used, the kinds of decisions made solely by the program, and the kinds of decisions where the program does something substantially and directly related to making them. APP 1.9 closes the obvious gaps, confirming that a decision includes refusing or failing to decide, and that an effect counts whether it is adverse or beneficial.
"Computer program" carries its ordinary meaning. It covers a machine learning model, but it equally covers a pre-programmed rule set or a scoring spreadsheet. The obligation also applies regardless of when the arrangement was made, so a scorecard built in 2019 is caught on the same terms as an AI workflow deployed last month.
Whether a credit fund is caught at all.
Two thresholds sit in front of the substantive question, and plenty of funds stop at one of them.
- Are you an APP entity? The Privacy Act generally applies to organisations with annual turnover above $3 million, measured as income from all sources. Separately, credit providers and credit reporting bodies carry Privacy Act obligations under the credit reporting rules irrespective of that threshold, so a lender should confirm its own status rather than assume the small business exemption covers it.
- Is personal information used in the program? The obligation attaches to individuals, not to borrowers as such. A fund lending to corporates may still be handling personal information about directors, guarantors and beneficial owners, and a guarantee declined is a decision about a person.
That produces a real split across the sector. A fund making credit decisions about individuals, sole traders or guarantors, and any non-bank lender assessing consumer or small business applications, should assume it is in scope and work out what to disclose. A wholesale fund whose decisions run entirely to corporate counterparties, with no automated step touching personal information, may have nothing to add to its privacy policy. Both answers are legitimate. What is not legitimate is arriving at the second one without doing the analysis.
On significance, the OAIC has signalled that access to financial products and credit services sits in the territory the obligation is aimed at. A declined application is the paradigm case, and APP 1.9 makes clear an approval on worse terms counts too.
The clause that catches AI you are already running.
The phrase to read carefully is "substantially and directly related to making the decision". It is the difference between a rule that applies to a handful of fully automated credit engines and a rule that applies to the ordinary way a credit fund now works.
In its May 2026 issues paper, the OAIC proposed reading the two words separately. "Substantially" means the program is a key factor in facilitating the human decision-maker's decision. "Directly" means it has a direct connection with making that decision. On that reading, a human who signs off a machine-generated score, shortlist or recommendation without independently reworking it does not move the decision outside the obligation.
Apply that to the AI most credit funds have actually deployed. A model that extracts figures from a borrower pack into a template is remote from the decision. A model that produces the credit summary the committee reads, or scores an application, or ranks a pipeline before anyone looks at it, is much closer to being a key factor. Our position is that the risky assumption in a credit fund is not "we use AI to decide". It is "a person signs it, so this cannot be automated decision-making".
Note the status of that reading. The consultation closed on 15 June 2026 and the OAIC has said it intends to publish final guidance by September 2026. Treat the issues paper as the regulator's direction of travel, not as settled interpretation.
What to do with the four months.
The instinct is to inventory the tools. That produces the wrong list, because the obligation is indexed to decisions rather than to software.
- Start from the decisions. List the decisions your fund makes that could significantly affect an individual: credit approvals and declines, pricing and limits, guarantee and security calls, hardship and enforcement steps, and anything else that lands on a person rather than a company.
- Trace what feeds each one. Record which programs touch the decision, what personal information they use, and whether each one decides or contributes. Rule-based tools and spreadsheets belong on this list alongside the AI.
- Sort into the three APP 1.8 buckets. Kinds of personal information used, kinds of decisions made solely by a program, and kinds of decisions where a program does something substantially and directly related. The privacy policy wording follows from the sort, and it is a lot easier to write once the sort exists.
- Write down the exclusions and why. A documented judgement that a use case is not substantially and directly related is defensible. Silence is not.
- Draft now, finalise after September. The mapping work does not change when the final guidance lands. The wording might.
The second step is where most funds stall. AI use grew workflow by workflow, and the record of what informed a given credit decision now sits across email, a document store and someone's chat history, so reconstructing it means asking people what they remember. Where AI runs through a single layer that records the systems in use and the material each decision relied on, the same question is answered by reading the fund's own records. That is an operational difference rather than a legal one: it does not change the analysis, it just makes it possible to perform.
This is the second recent case of the same pattern, after the CPS 230 diligence a fund now receives from APRA-regulated investors. Neither asks a fund to stop using AI. Both ask it to know where AI sits and to be able to say so.
Primary sources: the Privacy and Other Legislation Amendment Act 2024, the OAIC's consultation on guidance for transparency in automated decision making and the OAIC's APP 1 guidelines. This guide is general information, not legal advice. Whether a particular fund, program or decision is caught depends on the facts and on the final OAIC guidance.
Questions this guide answers.
Do the new automated decision-making rules apply to a private credit fund?
They apply to APP entities, which generally means organisations with annual turnover above $3 million, and credit providers carry Privacy Act obligations under the credit reporting rules irrespective of turnover. Beyond that the test is whether a computer program uses personal information about an individual to make, or to substantially and directly contribute to, a decision that could reasonably be expected to significantly affect that individual. A non-bank lender assessing individuals or small businesses should assume it is in scope. A fund whose decisions run only to corporate counterparties, with no automated step touching personal information, may have nothing to disclose, but should record how it reached that view.
Does a human reviewer take our AI out of scope?
Not by itself. The obligation covers a program that does a thing substantially and directly related to making the decision, not only a program that decides. In its May 2026 issues paper the OAIC proposed that 'substantially' means the program is a key factor in facilitating the human decision-maker's decision and 'directly' means it has a direct connection with making it. On that reading, approving a machine-generated score, shortlist or recommendation without independently reworking it does not remove the disclosure requirement.
What has to go in the privacy policy?
APP 1.8 requires three things: the kinds of personal information used in the operation of those computer programs, the kinds of decisions made solely by the operation of a computer program, and the kinds of decisions where a program does something substantially and directly related to making the decision. APP 1.9 confirms that a decision includes refusing or failing to make one, and that the effect on an individual counts whether it is adverse or beneficial.
Does this apply to systems we already run?
Yes. The obligation applies regardless of whether the arrangement for the program was made before or after the amendments commence, and regardless of when the personal information was collected. A rule-based credit scorecard or a scoring spreadsheet counts as a computer program on the same terms as a machine learning model.
Working with Levercon.
Levercon builds the AI operating system for credit funds: Fund OS connects a fund's own data into a knowledge layer, and Custom Agents run repetitive work across origination and monitoring. To talk to us, email info@levercon.ai.
This guide is general information, not advice. Factual claims that rely on public sources link to those sources in the text. Practical guidance also draws on patterns Levercon observes across Australian credit funds. No client is named and no figure is attributed to one. Written by Levercon, reviewed before publication and revised in place as the facts change.