Credit decisioning AI
Fairness assessment, explainability assurance, and full audit traceability for automated credit decisions — so every outcome is defensible under ASIC RG 273 and internal model-risk policy.
Solutions / Financial Services
Prove your AI is trustworthy. Before the regulator asks.
APRA, ASIC, and AUSTRAC are watching AI deployment in financial services more closely than ever. The organisations that get ahead of this will define the standard.
Regulatory Context
Frameworks you already know.
Financial services organisations operate under layered AI obligations: APRA CPS 234 (Information Security) and CPS 230 (Operational Risk Management) require robust governance of model risk; the Australian Securities and Investments Commission (ASIC) Regulatory Guide 273 addresses AI-driven advice; AUSTRAC's AML/CTF obligations extend to automated decisioning. Sentrify maps controls to every layer.
APRA CPS 234APRA CPS 230ASIC RG 273AUSTRAC AML/CTFPrivacy Act 1988 (Cth)ISO 42001 Annex A
Use Cases
What Financial Services uses Sentrify for.
Fraud detection models
Ongoing monitoring, bias checks, and governance documentation for fraud and anomaly detection models — aligned to APRA CPS 234 and operational resilience requirements.
Underwriting and pricing AI
Regulatory evidence for actuarial and pricing AI systems, including documentation of model assumptions, validation results, and risk-owner sign-off.
Customer-facing AI
Responsible AI assurance for chatbots, robo-advisers, and recommendation engines — transparency notices, fairness evaluation, and a TrustScore™ report your compliance team can file.
How Sentrify Helps
Platform capabilities for your vertical.
Model risk governance
Register every AI system with a version-tracked governance record. Risk tier is calculated automatically from the system's characteristics — no spreadsheet model inventory.
Audit-ready evidence vault
Every control decision is linked to the evidence document that supports it. When APRA asks, the answer is already assembled.
Multi-stakeholder approvals
Governance lead, risk committee, and technology owner each have a defined role in the review workflow — with quorum, endorsement records, and mandatory rejection notes.
Join our founding pilot cohort in Financial Services.
We're working with a small group of financial services organisations on an 8-week pilot: one real AI system, the full evaluation, and a board-ready assurance report. Help shape the product and get your evidence base in place first. Start with a customer-facing or decision-support model and produce evidence aligned to CPS 230 and CPS 234.
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AI Governance Checklist
50 checkpoints for responsible AI deployment: governance documentation, evidence requirements, control mapping and regulator-ready reporting. Built for Australian compliance contexts (ISO 42001, APRA CPS 230, TEQSA).
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APRA's model risk guidance continues to evolve. Start building your defensible evidence base now.