How Australian Insurers Are Fighting Deepfake Fraud

Australia’s general insurance industry is a A$70+ billion market regulated by some of the world’s most rigorous prudential standards. It’s also increasingly exposed to a fraud threat that its current detection infrastructure wasn’t designed to address: AI-generated deepfakes.

While much of the global deepfake fraud conversation centers on the US market, the threat is equally real for Australian insurers — and the regulatory, legal, and operational landscape creates both unique challenges and unique opportunities for the local market.

The Australian Insurance Fraud Landscape

Scale of the Problem

The Insurance Council of Australia (ICA) reports that in 2017, insurers detected A$280 million in fraudulent claims across all insurance classes (excluding health insurance and personal injury). This represents only detected fraud — the ICA acknowledges that “an estimate of the value of undetected insurance fraud in the Australian market is not yet available.”

The global context suggests the undetected portion is substantial. The Coalition Against Insurance Fraud estimates that fraud constitutes roughly 10% of property-casualty losses worldwide. Applied to Australia’s general insurance market, this implies total fraud exposure well into the billions of dollars annually.

Insurance fraud in Australia is classified as a serious indictable offense, with penalties of up to 10 years imprisonment, substantial fines, or both. Despite this, the ICA distinguishes between two persistent categories:

Opportunistic fraud — exaggeration of otherwise legitimate claims (the most common form)
Premeditated fraud — planned schemes by professional criminals, often involving organized criminal groups

AI-generated deepfakes amplify both categories: making opportunistic fraud easier (photo manipulation to exaggerate damage) and premeditated fraud more scalable (bulk generation of fabricated evidence across multiple claims).

The Insurance Fraud Bureau of Australia (IFBA)

The IFBA, established by ICA members in 2010, coordinates the industry’s response to fraud:

Provides a reporting service for community members to report suspected fraud
Facilitates police investigations where insurance fraud is a factor
Coordinates information exchange between insurers where fraud is reasonably believed to have occurred
Participates in government and community crime prevention forums

The IFBA plays a similar role to the NICB in the US — but operates in a smaller, more concentrated market where information sharing between major insurers can be more direct and effective.

The Australian Regulatory Environment

APRA (Australian Prudential Regulation Authority)

APRA regulates general insurers, life insurers, private health insurers, and superannuation entities. Key regulatory requirements relevant to fraud detection include:

CPS 220 — Risk Management. Requires regulated entities to maintain a risk management framework that identifies, assesses, mitigates, and monitors risks. Deepfake fraud is an emerging operational risk that APRA expects insurers to identify and address within their risk frameworks.

CPS 234 — Information Security. Requires entities to maintain information security capabilities commensurate with the size and extent of threats to their information assets. As AI-generated fraud becomes a documented threat, the argument that current detection capabilities are insufficient strengthens.

CPS 230 — Operational Risk Management (effective July 2025). The new standard broadens operational resilience requirements and explicitly includes technology-related risks. Deepfake-enabled fraud falls squarely within the operational risks this standard addresses.

Guidance on AI and technology. APRA has signalled increasing attention to AI risks in financial services, including the risks posed by adversarial AI applications. While specific guidance on deepfake detection hasn’t been issued, the regulatory trajectory is clear.

ASIC (Australian Securities and Investments Commission)

ASIC’s focus on consumer protection and fair claims handling creates additional obligations:

Claims handling standards. ASIC expects insurers to handle claims fairly and efficiently. Fraudulent claims that go undetected ultimately harm policyholders through higher premiums. Effective fraud detection is a component of fair claims handling.

Product disclosure. Insurers must disclose material information about their products and claims processes. As AI fraud awareness grows among consumers and regulators, disclosure about fraud prevention measures may become expected.

AML/CTF (Anti-Money Laundering / Counter-Terrorism Financing)

While general insurance is less directly impacted by AML/CTF requirements than banking or life insurance, certain products (particularly those with investment components) fall under AUSTRAC regulation:

Customer identification and verification requirements
Suspicious matter reporting obligations
Transaction monitoring requirements

Deepfake-powered identity fraud directly threatens the effectiveness of AML/CTF compliance. Insurers subject to AUSTRAC regulation need to ensure their KYC processes can withstand AI-generated identity documents and biometric spoofing.

The Evidence Act

The Evidence Act 1995 (Cth) and state equivalents govern the admissibility of evidence in Australian courts. For AI-detected fraud that proceeds to prosecution or civil recovery:

Expert opinion must be based on “specialized knowledge” derived from training, study, or experience
The Federal Court’s guidelines on expert evidence require disclosure of methodology and reasoning
Electronic evidence must be authenticated — the proponent must establish that the evidence is what it purports to be

These requirements mean that forensic reports from deepfake detection tools must be explainable, methodology-documented, and presented by qualified experts — the same standards we discuss in our court-ready forensic reports article, with Australian-specific legal requirements.

Why Australia Is Well-Positioned

Concentrated Market

Australia’s general insurance market is concentrated among a relatively small number of major insurers (IAG, Suncorp, QBE, Allianz, and others). This concentration enables:

Faster industry coordination — information sharing through IFBA is more practical than in the fragmented US market
Collective intelligence — fraud patterns identified by one major insurer can be rapidly communicated to others
Standardised approaches — industry-wide adoption of detection standards is more feasible when the market is concentrated

Digital-Forward Claims

Australian insurers have invested heavily in digital claims processes. Mobile-first claims, photo-based assessment, and remote settlement are standard across major insurers. This digital infrastructure is both a vulnerability (more attack surface for AI-generated evidence) and an advantage (detection tools can be integrated into existing digital workflows).

Strong Regulatory Framework

APRA’s principles-based regulation creates flexibility for insurers to adopt new technologies without waiting for prescriptive mandates. The risk management framework (CPS 220, CPS 230) expects insurers to address emerging risks — including AI fraud — within their existing governance structures.

Geographic Context

Australia’s exposure to natural catastrophes (bushfires, cyclones, floods, storms) creates regular surge events in claims processing — exactly the conditions where AI-generated fraud risk is highest and detection is most valuable. The 2019-2020 bushfire season, the 2022 eastern Australia floods, and recurring cyclone seasons demonstrate that CAT events are a regular feature of the Australian market, not an exception.

Practical Steps for Australian Insurers

Immediate Actions

Assess your deepfake exposure. Audit your digital claims intake: what proportion of claims are submitted with photos, videos, or documents? What verification is currently performed on this media? Where are the gaps?
Engage with IFBA. Report suspected deepfake fraud through IFBA’s reporting channels. The more intelligence the industry shares, the faster collective defenses improve.
Review your risk management framework. Ensure deepfake fraud is identified as an emerging risk within your CPS 220/CPS 230 risk management documentation. This positions you for regulatory conversations and justifies technology investment.

Medium-Term Investments

Deploy AI-powered media detection. Integrate deepfake detection into your digital claims workflow. The Australian market’s digital maturity means integration into existing mobile and web claims channels is straightforward.
Update KYC processes. For products requiring identity verification, ensure your KYC processes include deepfake-resistant biometric verification with presentation attack detection — particularly for life insurance and investment-linked products subject to AUSTRAC requirements.
Build forensic capability. Ensure your investigation team (internal or outsourced) has access to digital forensic tools and understands how to interpret AI detection results in the context of Australian evidence law.

Strategic Positioning

Lead on industry standards. The Australian market is small enough that a single major insurer adopting detection can influence industry norms. Be the insurer that sets the standard, not the one that follows.
Engage with APRA proactively. As APRA develops its understanding of AI risks in insurance, insurers with existing detection capabilities will be positioned as leaders. Proactive engagement shapes regulatory expectations in pragmatic directions.
Invest in Australian-validated detection. Ensure your detection tools are validated on media that reflects Australian conditions — vehicle types, property styles, weather patterns, document formats, and lighting conditions. A tool validated only on US market data may not perform equivalently on Australian claims.

The Opportunity

Australia’s insurance market has the characteristics that make early adoption of deepfake detection particularly valuable: concentrated market, digital-forward operations, strong regulation, and significant CAT event exposure.

The insurers that move now will build competitive advantage through lower fraud losses, stronger regulatory positioning, and industry leadership. In a market where a handful of major players control the majority of premiums, the first mover sets the standard that others must follow.

deetech is an Australian company, built in Adelaide, with detection validated on Australian insurance market conditions. We understand the local regulatory environment, the local claims landscape, and the local fraud patterns.

deetech is Australian-built, validated on Australian market conditions, and designed for the Australian regulatory environment. Request a demo to discuss how we can help your organization address deepfake fraud.

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