AI Solutions Built for APRA Compliance and Banking Excellence
Purpose-built AI for Australian banks and financial institutions. From fraud detection to regulatory reporting, our solutions meet the stringent requirements of APRA, ASIC, and the Privacy Act while delivering measurable business outcomes.
Includes a complimentary APRA compliance readiness guide
The State of AI in Australian Banking
Australian banking is undergoing a fundamental shift. The major banks and regional institutions alike are investing heavily in artificial intelligence, driven by the twin pressures of tightening regulation and rising customer expectations. APRA's strengthened prudential framework, including CPS 234 for information security and the new CPS 230 for operational risk management, means that AI deployments in financial services must be built on robust governance from day one. Institutions that treat compliance as an afterthought are finding themselves unable to scale their AI initiatives past the proof-of-concept stage.
At the same time, competitive dynamics are accelerating adoption. Digital-first challengers and fintech partnerships are forcing traditional banks to modernise their data infrastructure and customer-facing services. Fraud losses across Australian financial services continue to climb, with the Australian Competition and Consumer Commission reporting billions in scam losses annually. AI-powered fraud detection, credit risk modelling, and automated compliance are no longer optional capabilities. They are essential for any institution that wants to remain competitive and meet its regulatory obligations.
The challenge for most banks is not whether to adopt AI, but how to do it in a way that satisfies regulators, delivers genuine returns, and scales across the organisation. This requires deep expertise in both the technology and the regulatory landscape. It requires AI solutions that are explainable, auditable, and built with proper model risk management from the outset.
Challenges Facing Australian Financial Institutions
The banking sector faces unique pressures from regulators, customers, and competitors
APRA Regulatory Compliance for AI in Banking
Every AI system deployed in an Australian bank must satisfy multiple overlapping prudential standards. We design solutions that address these requirements from the architecture level, so compliance is built in rather than bolted on.
CPS 234: Information Security
CPS 234 requires APRA-regulated entities to maintain information security capabilities commensurate with the threats they face. For AI systems, this means end-to-end encryption of data pipelines, role-based access controls on model training data and outputs, comprehensive audit logging of all model interactions, and formal incident response procedures for AI-related security events. Our architectures implement these controls as default, not optional extras.
CPS 230: Operational Risk Management
Effective from July 2025, CPS 230 requires banks to identify, assess, and manage operational risks across critical operations. AI systems that support lending decisions, fraud detection, or customer-facing services are increasingly classified as critical. This means banks need business continuity plans for AI system failures, service level expectations for third-party AI providers, and robust testing and validation frameworks. We help institutions map their AI dependencies and build the resilience that CPS 230 demands.
CPS 220: Risk Management
CPS 220 establishes the overarching risk management framework that boards and senior management must maintain. As AI becomes a material driver of business decisions, institutions must demonstrate that their boards understand AI-related risks and that appropriate risk appetite statements, escalation procedures, and oversight mechanisms are in place. Our governance frameworks give boards the visibility and control they need.
Privacy Act & AML/CTF Obligations
AI systems processing customer data must comply with the Privacy Act 1988 and Australian Privacy Principles, including requirements around data minimisation, purpose limitation, and individual access rights. AI used in transaction monitoring must also satisfy AML/CTF Act obligations for suspicious matter reporting and customer due diligence.
Regulatory Compliance Coverage
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Our AI Governance service builds the policies, frameworks, and oversight structures that APRA expects.
Explore AI GovernanceAI Use Cases in Australian Banking
Proven applications of artificial intelligence across banking operations, risk management, and customer experience
Our AI Solutions for Banking
Transform your data infrastructure to meet regulatory requirements while unlocking AI-powered capabilities
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Measurable returns from AI implementations across Australian financial institutions
Reduction in fraud losses through real-time AI detection
Faster regulatory reporting through automation
Typical payback period for banking AI investments
Return on investment over three years
Where the Returns Come From
Cost Reduction
- Reduced manual processing in compliance and operations
- Lower fraud losses and investigation costs
- Decreased false positive rates in AML/fraud systems
Revenue Growth
- Better credit decisions leading to improved lending margins
- Personalised offers increasing product uptake
- Faster customer onboarding reducing drop-off
Leading Australian Bank Deploys Intelligent Knowledge Platform
A global financial institution transformed their policy and compliance document retrieval using a multi-agent RAG system, reducing retrieval time and increasing accuracy of generated summaries.
Key Results
Reduction in document retrieval time
Factual accuracy of generated summaries
Governed architecture across knowledge domains
AI-Powered Legal and Regulatory Summarisation
How we helped a major insurer automate compliance document review with RAG and transformer-based summarisation.
Banking-Ready Technology Stack
Enterprise-grade Databricks components designed for financial services
Why Australian Banks Choose Get AI Ready
Banking Expertise
Deep understanding of APRA requirements, banking workflows, and financial services regulations
Proven AI Solutions
Delivered fraud detection, risk modelling, and customer analytics for leading financial institutions
Local Presence
Australian team with offices in Sydney and Brisbane, understanding local market dynamics
Frequently Asked Questions About AI in Banking
How long does an AI implementation take in Australian banking?
A typical AI implementation in Australian banking takes between 12 and 24 weeks from discovery to production, depending on scope and regulatory requirements. Initial proof-of-concept deployments can be delivered in 6 to 8 weeks. The timeline accounts for APRA compliance reviews, model validation, and the governance approvals that regulated entities require. We recommend a phased approach starting with a well-defined use case like document processing or fraud detection, then expanding once the governance framework is proven.
What APRA requirements apply to AI in banking?
Several APRA prudential standards directly affect AI deployments in banking. CPS 234 (Information Security) requires that AI systems handling sensitive data have appropriate security controls, access management, and incident response procedures. CPS 230 (Operational Risk Management), effective from July 2025, requires banks to identify and manage risks from critical operations including AI-dependent processes. CPS 220 (Risk Management) mandates that boards understand and oversee material risks, which increasingly includes AI model risk. Banks must also consider the Privacy Act 1988, AML/CTF obligations, and ASIC guidance on responsible AI use in financial services.
How much does AI consulting cost for Australian banks?
AI consulting for Australian banks typically ranges from $150,000 to $500,000 for an initial implementation, depending on the complexity of the use case, integration requirements, and regulatory obligations. A focused proof of concept might start from $80,000, while enterprise-wide AI platform builds with full governance frameworks can exceed $1 million. We provide transparent, fixed-scope engagements so there are no surprises. The investment typically pays for itself within 12 months through operational efficiencies, reduced manual processing, and improved risk detection.
What is the ROI of AI in banking?
Australian banks implementing AI consistently report strong returns. Fraud detection models typically reduce fraudulent transaction losses by 40 to 60 percent while cutting false positives by up to 50 percent. Automated regulatory reporting can reduce preparation time by 70 to 90 percent. Credit risk models improve decision accuracy by 25 to 35 percent, leading to better lending outcomes and reduced defaults. Customer service automation handles 30 to 50 percent of routine enquiries, freeing staff for complex interactions. Most banks achieve full payback on their AI investment within 9 to 18 months, with compound returns as models improve and new use cases are deployed.
Ready to Implement AI in Your Bank?
Book a no-obligation AI assessment with our banking specialists. We will review your current data landscape, identify high-impact AI opportunities, and outline a compliance-ready implementation roadmap.
Every assessment includes a complimentary APRA CPS 234 AI compliance readiness guide.