Insurance Deepfake Fraud Incidents: A Growing Timeline

This page tracks publicly documented deepfake and AI-generated fraud incidents, official alerts and research findings that matter to insurers. Each entry is dated and linked to its source.

Last updated: September 29, 2026

Not every entry is an insurance claim. Many come from banking, identity verification or corporate fraud. We include them because each shows a capability that applies directly to insurance claims processes, and the tools involved are the same ones available to people filing claims.

2022

June 2022 — FBI Warns of Deepfakes in Remote Job Interviews

What happened: The FBI’s Internet Crime Complaint Center reported an increase in complaints about people using deepfake video and stolen personal information to apply for remote jobs, including roles with access to customer data and financial systems. Interviewers noticed that lip movements didn’t match the audio.

Source: FBI IC3 Public Service Announcement, June 28, 2022

Insurance relevance: Real-time face and voice substitution was already being used in live video calls in 2022. The same technique applies to video inspections, remote consultations and recorded statements.

2023

April 2023 — Journalist’s AI Voice Clone Passes Her Bank’s Voice Check

What happened: A Wall Street Journal columnist, Joanna Stern, reported that an AI clone of her voice got past her bank’s voice verification and fooled members of her family (WSJ, April 28, 2023).

Insurance relevance: Insurance call centers also use voice to identify customers. A cloned voice can be used to report claims, change policy or payment details, or extract information about existing claims.

June 2023 — Researchers Bypass Voice Authentication in Six Tries

What happened: University of Waterloo researchers showed an attack that bypassed voice authentication systems with up to a 99% success rate after six attempts, presented at the IEEE Symposium on Security and Privacy.

Source: University of Waterloo

Insurance relevance: Voice authentication alone is not a sufficient control for high-risk actions such as changing payout details.

November 2023 — Onfido Reports a 31x Rise in Deepfake Attempts

What happened: Onfido’s 2024 Identity Fraud Report recorded a 3,000% (31x) increase in deepfake attempts in 2023 compared with 2022, and a fivefold increase in digitally forged identities.

Source: Onfido, via Entrust

Insurance relevance: Policy onboarding and claims payment both depend on identity checks. A rise in forged identities and deepfake attempts at verification points raises the risk of fictitious policyholders and claimants.

2024

February 2024 — Hong Kong: US$25.6M Lost After Deepfake Video Call

What happened: Hong Kong police disclosed that fraudsters had used deepfakes of several executives, including the CFO, in a video conference with an employee of a multinational company. The employee transferred HK$200 million (about US$25.6 million) in 15 transactions. In May 2024 the company was confirmed as the engineering firm Arup.

Source: CNN, February 2024

Insurance relevance: Live, multi-person video deepfakes were good enough to fool a professional. Video inspections, remote consultations and video-based identity checks face the same risk, and a static photo or document is easier to fake than a live call.

May 2024 — Deloitte Projects US$40B in Generative-AI-Enabled Fraud by 2027

What happened: Deloitte’s Center for Financial Services projected that generative AI could push US fraud losses to US$40 billion by 2027, from US$12.3 billion in 2023.

Source: Deloitte Insights, May 29, 2024

Insurance relevance: The projection focuses on banking, but insurers share the same exposure points: identity verification, submitted documents and remote interactions.

May 2024 — Insurance Council of Australia Sets Up a Counter-Fraud Function

What happened: The Insurance Council of Australia announced a dedicated counter-fraud and scams function to target organized fraud networks, reporting that members detected A$560 million of opportunistic motor and property fraud in 2023. The function became the Insurance Crime Intelligence Network of Australia (ICINA).

Source: Insurance Council of Australia, May 21, 2024

Insurance relevance: Industry bodies are building shared intelligence that can carry signals about AI-assisted fraud across insurers.

October 2024 — Regula: Deepfakes Cost Businesses About US$450,000 Each

What happened: Regula’s Deepfake Trends 2024 survey of 575 business decision-makers found that 92% had experienced identity fraud in the previous 12 months and about half had faced audio or video deepfakes. Businesses lost an average of nearly US$450,000 each to deepfakes; financial-services firms lost a little over US$600,000.

Source: Regula, October 31, 2024

Insurance relevance: These are per-business averages, not per-incident costs. Even so, a six-figure deepfake loss is well within the range of a handful of fraudulent property or motor claims.

November 2024 — FinCEN Alert on Deepfake Fraud

What happened: The US Financial Crimes Enforcement Network issued an alert warning financial institutions about fraud schemes using deepfake media, including altered or synthetic identity documents, and listed red flags for detection.

Source: FinCEN Alert FIN-2024-Alert004, November 13, 2024

Insurance relevance: A federal alert confirmed that deepfake fraud was occurring at enough scale to warrant formal guidance. Its red flags for identity documents apply directly to insurance onboarding and claims.

November 2024 — Sumsub: Deepfakes Up Fourfold in a Year

What happened: Sumsub’s 2024 identity fraud research reported a fourfold increase in detected deepfakes from 2023 to 2024, after the tenfold increase from 2022 to 2023 in its 2023 report. Its report found the global identity fraud rate had risen from 1.10% of verifications in 2021 to 2.50% in 2024, with banking and insurance among the five most affected sectors.

Insurance relevance: Insurance onboarding and claims include identity verification, so insurers face the same escalation whether or not they are measuring it.

2025

February 2025 — Signicat: Deepfakes Now 1 in 15 Fraud Attempts

What happened: Signicat’s research found deepfake-based fraud attempts had risen 2,137% over three years and now make up 6.5% of all fraud attempts. Only 22% of organizations had implemented AI-based fraud defenses.

Insurance relevance: Rapid growth in attempts combined with slow adoption of defenses leaves a gap that insurers, like banks, have to close.

June 2025 — Pindrop: Synthetic-Voice Attacks on Insurers Up 475%

What happened: Pindrop’s 2025 Voice Intelligence and Security Report found that deepfake fraud attempts rose more than 1,300%, and synthetic-voice attacks on insurers rose 475%, faster than banking (+149%) or retail (+107%) (press release).

Insurance relevance: This is one of the few published data points specific to insurers, and it shows voice attacks on insurance contact centers growing fastest of the sectors measured.

November 2025 — Australia Moves Toward a National Fraud Platform

What happened: The Insurance Council of Australia announced a collaboration with Shift Technology and EXL to build a national fraud detection and investigations platform for the Australian insurance industry, run through ICINA.

Insurance relevance: Shared industry platforms make it easier to spot patterns, including reused or AI-generated evidence, that no single insurer sees on its own.

2025 — Analysts Start Mapping a Deepfake Detection Market

What happened: Industry analysts, including Gartner, began publishing research that treats deepfake detection as its own emerging market. Gartner described the market as nascent.

Insurance relevance: Buyers now have more independent material for comparing vendors. It remains important to evaluate any detector on media like your own.

2026

August 2026 — EU AI Act Deepfake Disclosure Duties Apply

What happened: EU AI Act Article 50 transparency obligations, including disclosure of deepfakes and other AI-generated content, began to apply on August 2, 2026. The Digital Omnibus (Regulation (EU) 2026/1744) moved the Act’s main high-risk obligations to December 2, 2027.

Source: Mayer Brown summary, July 2026

Insurance relevance: Disclosure rules bind lawful AI providers and deployers, not fraudsters. They do not reduce the need to verify the evidence submitted with a claim.

Patterns and Trends

What the Timeline Shows

Escalating capability. The record runs from deepfaked job interviews (2022) and voice clones passing bank checks (2023) to multi-person live video fraud (2024) and voice attacks at contact-center scale (2025).
Decreasing barriers. Early deepfakes required technical expertise. Current tools are consumer-accessible, so the pool of potential fraudsters now includes opportunistic individuals as well as organized groups.
Financial services as a leading indicator. Banking and identity verification have been the main targets. Insurance is structurally similar (document submission, identity verification, payment authorization) and should expect a similar trajectory; the Pindrop data suggests voice attacks on insurers are already catching up.
Defenses lagging attacks. Surveys consistently show fraud tools advancing faster than organizations adopt countermeasures.
Regulatory response building. FinCEN’s alert, APRA’s operational risk standard and the EU AI Act’s disclosure rules show regulators responding, but no regulator has yet issued insurance-specific guidance on AI-generated claims evidence.

What’s Missing from the Timeline

This timeline is limited to what has been publicly reported. Several kinds of incident are likely happening but rarely documented:

Individual claims with AI-manipulated photos: usually handled internally and not reported publicly
Coordinated fraud rings using AI tools: these may be under investigation
Exaggeration fraud using AI editing: the most common and hardest to detect, and unlikely to make headlines

A lack of public insurance-specific incidents does not show that the threat is absent. It mostly reflects limited detection and reporting.

The State of Deepfake Fraud in Insurance: attack vectors and industry readiness
Deepfake Fraud Statistics: the data behind these entries
The True Cost of Deepfake Fraud in Insurance: what it could cost

This timeline is updated as new incidents and research are published. If you know of a deepfake fraud incident relevant to insurance that should be included, contact us.

deetech™ helps insurers and claims teams check the photos, video, audio and documents submitted with claims, using versioned detector releases. Request a demo.

Sources cited: