Vanexus
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APRA AI readiness · 5-minute self-check

Would your AI survive APRA supervision?

Ten questions. Five minutes. A straight answer on where your agentic plans stand against APRA's expectations, and the specific gaps worth closing first.

Why now

The expectations are set. The clock is running.

On 30 April 2026, APRA set out what it expects of AI in regulated entities: an inventory of AI in use, monitoring of model and agent behaviour, clear lifecycle ownership, and independent assurance. CPS 230 amendments commence 1 July 2026; APP 1.7 automated-decision-making transparency follows on 10 December 2026. Most firms have AI policy on paper. Few can evidence the machinery behind it. Score yourself honestly below. For each statement, mark whether it is evidenced, partly in place, or not yet there.

Inventory & ownership

We maintain a current inventory of every AI and agentic system in use, including tools adopted by individual teams, with a named owner for each.

1.We maintain a current inventory of every AI and agentic system in use, including tools adopted by individual teams, with a named owner for each.

Every AI system is mapped to a lifecycle stage (pilot, controlled, production) and a defined autonomy level, not just “live / not live”.

2.Every AI system is mapped to a lifecycle stage (pilot, controlled, production) and a defined autonomy level, not just “live / not live”.

Behaviour monitoring & assurance

We monitor model and agent behaviour in production (drift, failure modes, out-of-policy actions), not just uptime.

3.We monitor model and agent behaviour in production (drift, failure modes, out-of-policy actions), not just uptime.

We can produce evidence of control (evaluation results, assurance artefacts) on request, rather than asserting that controls exist.

4.We can produce evidence of control (evaluation results, assurance artefacts) on request, rather than asserting that controls exist.

Our AI controls have been reviewed by someone independent of the team that built them.

5.Our AI controls have been reviewed by someone independent of the team that built them.

Autonomy & auditability

Every autonomous agent has identity, authority boundaries and a kill switch, and we can name who holds each.

6.Every autonomous agent has identity, authority boundaries and a kill switch, and we can name who holds each.

We can reconstruct any individual agent decision end-to-end, after the fact, from an audit trail.

7.We can reconstruct any individual agent decision end-to-end, after the fact, from an audit trail.

A human makes the final call on every consequential decision, by design, not by configuration that could be switched off.

8.A human makes the final call on every consequential decision, by design, not by configuration that could be switched off.

Data residency & regulatory readiness

We can evidence (not just assert) that regulated data stays within Australian borders across our AI toolchain.

9.We can evidence (not just assert) that regulated data stays within Australian borders across our AI toolchain.

We have mapped our automated decision-making against APP 1.7 ahead of its 10 December 2026 commencement.

10.We have mapped our automated decision-making against APP 1.7 ahead of its 10 December 2026 commencement.

0 of 10 answered

Where to from here

Your score tells you where you stand. Closing the gap is what we do.

Vanexus takes agentic AI from pilot to governed, auditable production for APRA-regulated banks, insurers and superannuation funds. Built by a founder with 22+ years on Tier-1 banking platforms and five years architecting financial-crime risk systems at a global Tier-1 bank.

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