AI for AASB Compliance: Boost Valuation & Growth
Essential information and practical guidance for using AI to streamline AASB reporting, strengthen controls, and support better valuations AI-enabled AASB reporting and compliance framework
Content reviewed and verified by Graham Chee, with 25+ years in accounting, taxation, investment management, governance, risk & compliance. Last reviewed December 2025. Next review scheduled for March 2026.
Introduction
Why this matters for your business
AASB reporting is complex and time-consuming, especially as businesses handle larger data sets, multiple entities, and evolving disclosure requirements. AI can help by automating data extraction, standardising calculations, drafting disclosures, and continuously monitoring controls. When implemented with strong governance, AI improves the quality and timeliness of financial reporting, reduces compliance risk, and provides stronger evidence for valuation valuation‑ready financial reporting and advisory for Australian SMEs. In this article you will learn key AI concepts relevant to AASB, practical use cases across common standards, a step-by-step approach to implementation, and answers to frequently asked questions.
Key Considerations
Essential points to understand
Standards alignment and policy mapping: AI should reflect your accounting policies and AASB requirements (for example AASB 15 Revenue, AASB 16 Leases, AASB 9 Financial Instruments, AASB 136 Impairment). Maintain a clear mapping from policy to data and calculation logic, and update when standards or interpretations change.
Evidence and auditability: Regulators and auditors expect traceability. Use systems that produce audit trails, version control, workpapers, and explainable outputs so reviewers can understand how numbers and disclosures were derived.
Data governance, privacy, and security: Protect source data under the Australian Privacy Principles. Apply data minimisation, encryption, role-based access, and vendor due diligence. Confirm data residency options and review certifications such as ISO 27001 or SOC 2 for relevant service providers.
Model risk management and explainability: Validate models, document assumptions, test for bias, and monitor for drift. Prefer interpretable methods where judgment is material and provide human-in-the-loop checks for critical decisions.
Human oversight and internal controls: AI augments, not replaces, professional judgment. Maintain maker-checker workflows, approvals, and segregation of duties. Ensure finance owners retain responsibility for policies and conclusions.
Integration and change management: Connect AI tools to your ERP, GL, CRM, and document stores. Redesign processes to embed controls, train users, and assign ownership for ongoing maintenance and updates.
Practical Application
How this works in real businesses
Revenue recognition (AASB 15): Natural language processing can read contracts to identify performance obligations, variable consideration, and timing of revenue. The system proposes revenue schedules, flags contract modifications, and drafts policy-consistent memos for review. Finance teams approve postings and retain a complete evidence pack for auditors.
Leases (AASB 16): Document intelligence extracts key terms from lease PDFs (commencement, options, CPI clauses). Calculators derive right-of-use assets and lease liabilities, handle reassessments, and prepare journals and disclosures. Controls ensure changes are reviewed before close.
Financial instruments (AASB 9): Machine learning can segment customers and estimate expected credit losses using probability of default, loss given default, and exposure at default. Scenario weightings align to your governance settings embed cyber governance and ITGCs that strengthen AASB assurance. Override logs and sensitivity analysis support judgmental overlays and board reporting.
Impairment testing (AASB 136): AI-assisted forecasting consolidates operational drivers into cash flow models, runs value-in-use scenarios, and performs automated sensitivity analysis on growth, margins, and discount rates. Dashboards monitor impairment indicators across entities and periods.
Narrative disclosures and consistency checks: Language models assist with drafting accounting policy summaries, significant judgments, and risks. Cross-checkers validate that narrative disclosures reconcile to the numbers and that terminology is consistent across notes.
Continuous controls monitoring: Anomaly detection scans the general ledger, AP/AR, and subledgers for unusual postings or cut-off issues. Close checklists, variance explanations, and reconciliations are standardised, reducing last-minute surprises and improving readiness for due diligence.
Valuation impact: Higher quality earnings evidence, stronger working capital analytics, and well-supported forecasts help external stakeholders assess risk with greater confidence. Better documentation and predictability can positively influence perceptions during capital raising, lending, or exit processes.
Recommended Steps
A structured approach
Assess
Identify AASB areas with the highest effort or risk (for example revenue, leases, ECL, impairment). Map current processes, data sources, and control gaps. Engage finance, IT, risk, and legal to align objectives and risk appetite.
Plan
Define governance, data protection requirements, and success criteria. Select tools based on standards coverage, explainability, integration, and security. Design roles, maker-checker controls, and a change management plan. Involve auditors early.
Implement
Pilot one use case end-to-end. Clean and connect data, configure policies, and enable human-in-the-loop review. Produce documentation, evidence packs, and training materials. Obtain sign-offs from process owners.
Review
Validate outcomes against independent calculations. Monitor model drift and update for new standards or business changes. Conduct periodic control testing and post-implementation reviews. Scale to additional use cases once stable.
Common Questions
What business owners ask us
Q.Is AI acceptable for AASB reporting?
Yes. AASB standards are technology-agnostic. The key is maintaining appropriate controls, evidence, and professional oversight. Document policies, assumptions, and review steps so outputs are auditable and explainable.
Q.How do we involve our auditors?
Engage them early. Share your use cases, control design, model documentation, data lineage, and sample evidence packs. Align on materiality, testing approaches, and how management review controls will operate.
Q.What data do we need to get started?
Begin with the essentials: ERP/GL data, relevant subledgers, contract and lease documents, and historic credit or cash collection data where applicable. Start with one well-defined area, improve data quality, and expand from there.
Q.Should we build or buy?
It depends on complexity, skills, and timelines. Evaluate solutions for AASB coverage, explainability, integration with your systems, security certifications, data residency options, and vendor support. Building in-house may suit bespoke needs; packaged tools can accelerate standard use cases.
Q.How does this support valuation and growth?
Stronger reporting, evidence, and forecasting enhance confidence in earnings quality and cash conversion, reduce perceived risk, and improve readiness for due diligence. This supports better decision-making for investment, lending, and growth initiatives.
About the Author
Graham Chee, FCPA, GRCP, GRCA, IAIP, IRMP, ICEP, IAAP
Principal Advisor & Founder
Graham Chee is a highly qualified business advisor with over 25 years of professional experience spanning accounting, taxation, investment management, governance, risk, and compliance. As a Fellow of CPA Australia (FCPA), Graham brings deep technical expertise combined with practical business acumen. His qualifications include Governance Risk and Compliance Professional (GRCP), Governance Risk and Compliance Auditor (GRCA), Integrated Artificial Intelligence Professional (IAIP), Integrated Risk Management Professional (IRMP), Integrated Compliance and Ethics Professional (ICEP), and Integrated Audit and Assurance Professional (IAAP). Graham has advised hundreds of Australian SMEs on strategic planning, succession, business valuation, and compliance matters, helping business owners build sustainable, valuable enterprises.
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