ASIC and APRA have signalled clearly: AI in credit is welcome, but only if it's transparent, fair and auditable. With RG 278 on hardship and APS 220 on credit risk now explicitly calling out tech governance, lenders deploying agents must build compliance in from the start – not bolt it on later.
Evolving Regulatory Expectations
Australia's dual peaks have ramped up scrutiny on lifecycle credit management:
ASIC's hardship focus: RG 278 mandates proactive support, clear processes and evidence of fair outcomes; recent reviews (REP 782, REP 815) slam inconsistent handling and poor documentation.
APRA's risk lens: APS 220/APG 220 demand robust monitoring, judgment frameworks and provisioning for impaired loans; AI must enhance, not undermine, these.
Broader conduct rules: NCCP, Privacy Act and emerging AI guidance require explainability, bias checks and vulnerability safeguards in automated decisions.
Tech isn't the issue; unmonitored or opaque AI is. Regulators want outcomes: fewer defaults, better borrower help, defensible files.
Core Principles for AI Agent Compliance
Agents in origination, servicing or collections must embody these non-negotiables:
Policy as code: Embed NCCP/ASIC rules directly – e.g., hardship triggers, variation limits – so agents apply them consistently without drift.
Traceable reasoning: Log every step (data used, rules applied, escalations) for AFCA, ASIC data requests or internal QA.
Human accountability: No solo decisions on restructures/hardship; agents draft, triage and nudge – humans approve high-stakes calls.
Bias and vulnerability checks: Screen for protected attributes, flag at-risk borrowers (e.g., age/income combos) and diversify training data.
Testing regimes: Pre-live validation, ongoing monitoring for model drift, A/B tests against manual baselines.
Practical Implementation Roadmap
Lenders can operationalise this without massive overhauls:
Map agents to regs: Align use cases (hardship intake, arrears triage) to RG 278/APS 220 outcomes; document gaps early.
Build governance early: Form cross-functional panels (risk, compliance, tech) for agent approvals, with clear RACI.
Choose compliant stacks: Platforms with Aussie residency, audit APIs and policy engines accelerate safe rollout.
Monitor and report: Dashboards for agent performance, error rates and outcome parity vs humans; feed into APRA self-assessments.
Train and audit: Upskill teams on agent limits; run mock ASIC inquiries to stress-test records.
Opportunity Amid Obligations
Compliance isn't a brake – it's the accelerator. Reg-ready agents:
Strengthen AFCA defences with bulletproof trails.
Unlock efficiencies regulators endorse (proactive servicing).
Position lenders as leaders in "responsible AI" for investor/partners.
Ignore at your peril: fines, reputational hits and forced rewinds await sloppy deployments. Get it right, and AI becomes your compliance moat.