Solutions · Industries

Financial services

Move faster while keeping regulators confident.

Banks, insurers, super funds and advisers have strong use cases for AI in operations, customer service and risk. They also operate under prudential and conduct regulators who expect AI to be governed like any other material risk.

01 / Where AI helps

Opportunities

Operations

Claims triage, document checks and reconciliation support.

Customer communication

Drafting and reviewing customer correspondence for clarity and consistency.

Risk and compliance

Summarising regulatory change and searching policy obligations.

02 / Australian rules to check

What to get right

APRA CPS 234 and CPS 230

APRA regulated entities must protect information security (CPS 234) and manage operational risk, including material service providers (CPS 230). AI vendors and models fall inside both.

ASIC expectations

ASIC's review of AI use by financial services licensees (Report 798) found governance lagging adoption. Licensees remain responsible for outcomes, disclosure and fair treatment.

Fairness in decisions

Models used in credit, pricing or claims can encode bias. Test outcomes across customer groups and keep decisions explainable.

This is general information, not legal advice. See our Australian AI compliance guide for the wider landscape and links to official sources.

03 / Getting started

Where to run it

Material service provider rules make vendor concentration a real risk. Open weight models on infrastructure you control reduce dependence on a single overseas provider.

First steps

  1. Add AI to your risk register and your material service provider assessments.
  2. Start with internal productivity uses before customer facing decisions.
  3. Document model choice, testing and monitoring as you would for any model risk.

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