Executive Summary
The insurance industry is seeing a sharp rise in AI-generated and manipulated media used to defraud claims systems. According to Shift Technologies, 20-30% of insurance claims may now include altered images, fabricated documents, or synthetic medical reports1. These “synthetic frauds” are becoming more sophisticated, global in scale, and often difficult to spot, even for experienced investigators and adjusters.
Insurers need to adopt technologies capable of verifying where the digital content came from, whether it’s been altered, and how confident they can be in its authenticity. Just as important, they need modern core systems capable of scalable integrations, regulatory alignment, and human-centered design.
The Emerging Challenge: AI-Generated and Manipulated Media
Generative AI has made media manipulation far more accessible. Anyone with a smartphone can now create convincing deepfakes, fabricate vehicle or property damage, falsify signatures, manipulate invoices, or generate synthetic photos, videos, and individuals with minimal effort.
For insurers processing thousands or millions of claims each year, even a small percentage of falsified materials can create sizable financial and reputational exposure. Accordingly, a 2025 Deloitte survey found that 35% of insurance executives now rank fraud detection among their top priorities for generative AI investment2.
In practice, claims teams tend to encounter three common forms of digital media fraud:
- Deepfakes: AI-generated video or audio impersonations, such as bogus witness statements or fabricated event footage
- Shallow Fakes: Simple yet effective alterations like cropping, splicing, or reusing images from prior claims
- Synthetic Media: Fully fabricated images, videos, voices, individuals, and even businesses created by readily available GenAI tools and the dark web producing artifacts that are often indistinguishable from authentic content
Traditional review methods and legacy fraud models weren’t designed to detect these manipulations. As claim automation and straight-through processing increase, insurers should embed AI-driven authenticity verification at the core of their claims operation.
Rising Risk for Vulnerable Consumers
Synthetic media fraud creates risk on two fronts. It increases financial risk for insurers and creates new ways to exploit vulnerable claimants.
Fraudsters now use GenAI to manipulate, intimidate, or deceive individuals who are already navigating stress that follows a loss. Hyper-realistic synthetic content can create false narratives, mimic the voice of an adjuster (or claimant), and even fabricate “evidence” with the intent to coerce or confuse.
Some groups face higher risk than others:
- Older adults who may assume a familiar voice or branded communication is legitimate
- Recent immigrants who may struggle with language nuances and authentication steps
- Digitally inexperienced consumers who lack the skills to spot AI-driven impersonation or document manipulation
- Anyone dealing with emotional distress after a loss, when cognitive load and urgency are high
These customers may be more susceptible to scams that redirect claims payments, authorize fraudulent vendors, or pressure them into sharing sensitive information.
This places added responsibility on insurers. Trust has always been central to the insurance relationship, but the synthetic era demands a more deliberate approach, such as providing clear paths to human support, building verification steps that don’t disadvantage less tech-savvy customers, and balancing fraud defenses with empathy. Protecting vulnerable consumers is closely tied to safeguarding the integrity of the claims process itself.
Four Key Pillars for Managing Synthetic Media Fraud in P&C Claims
To reduce exposure and build resilience, insurers should modernize their claim operations across four key pillars. These pillars turn the growing threat of AI-generated media into practical steps claims teams can take, combining technical rigor with customer protection, operational resilience, and industry-wide collaboration.
Pillar 1: Precision Detection and Digital Forensics
Modern fraud requires a modern forensic toolkit. Leading insurers are deploying multi-layered detection systems that analyze every digital artifact entering the claims process.
- Multimodal Forensic Analysis
AI models evaluate image, video, audio, and text simultaneously, looking for inconsistencies in compression, lighting, sound patterns, and frame transitions. When anomalies appear, cases route automatically to human review.
- Content Provenance and C2PA Verification
C2PA content credentials help adjusters validate where and how a photo, document, audio or video was captured. By encouraging or requiring credentialed submissions through portals and partner ecosystems, insurers create a tamper-resistant chain of custody.
- Behavioral and Network Anomaly Detection
Advanced analytics scan structured claim data for unusual patterns across devices, IP addresses, timestamps, vendors, and claimant histories. When these signals are reviewed alongside media forensics, it becomes easier to spot coordinated fraud rings and synthetic identity schemes.
- Document and Invoice Authentication
Optical character recognition (OCR) and machine learning models identify forged PDFs and invoices by examining metadata, font patterns, template variations, and supplier authentication.
This pillar establishes the technical backbone for addressing synthetic media fraud, detecting what is real, what is manipulated, and what deserves escalation.
Pillar 2: Human-Centered Protection for Vulnerable Claimants
Fraud affects systems and people alike. As fraudsters begin targeting vulnerable policyholders with AI-driven impersonation and synthetic content, it’s best for insurers to adopt safeguards that reflect empathy and accuracy.
- Real-time Liveness Verification
Live video walkthroughs, dynamic gestures, and geolocation-stamped recordings create verification steps that deepfake systems have trouble replicating. These checks reduce friction for legitimate customers.
- Voice Identification Biometrics
Using the policyholder’s unique voice characteristics such as pitch, tone and speaking patterns to confirm their identity. In claims, this technology helps verify the person reporting the loss or managing the claim is the legitimate policyholder, reducing fraud and streamlining the process.
- Sentiment and Confusion Detection
Borrowing from banking, insurers can use AI to detect distress, hesitation, or uncertainty in claimant voice interactions, triggering escalation to a human representative who can ensure the customer isn’t being manipulated.
- Behavioral Biometrics and Digital-lifecycle Monitoring
Just as banks detect unusual login behaviors, insurers can identify when someone other than the policyholder is entering information in claim portals, helping spot social engineering or coercion.
- Delayed or Escalated Reviews for At-Risk Populations
Similar to “pause windows” used in banking to protect older customers, insurers can slow or escalate certain claim decisions when red flags indicate the claimant may be at risk of exploitation.
These protections help prevent fraud while strengthening trust, especially for claimants who may be disadvantaged by the complexity of AI-enabled deception.
Pillar 3: Integrated and Scalable Claims Operations
Fraud detection is only effective when it’s embedded directly into everyday claims workflows. Strong infrastructure allows defenses to scale without overwhelming investigators.
- API-driven Integration
Fraud scoring, media forensics, and identity verification should be connected seamlessly from claim intake to case management to payment
- Clear Triage and Investigator Dashboards
Well-designed interfaces help SIU teams prioritize the highest-risk files, reducing noise and preventing alert fatigue
- File Acceptance Rate Over Referral Volume
Modern fraud programs emphasize precision, including fewer false positives, higher SIU conversion, and faster cycle times for legitimate claimants
- Localization and Global Compliance
A scalable platform must align with GDPR, LGPD, PIPEDA, APPs, CCPA, and regional data residency laws, while supporting native-language workflows and jurisdiction-specific encryption.
This pillar enables fraud defenses to support, rather than hinder, modern claims automation and straight-through processing.
Pillar 4: Cross-Industry and Cross-Carrier Collaboration
Synthetic media fraud travels across companies, regions, and digital channels, requiring a unified industry response.
- Industry Data Sharing
Fraud rings repeatedly target multiple carriers. Shared repositories of suspicious vendors, device IDs, patterns, and media fingerprints make detection faster and more powerful.
- Banking-Style Fraud Intelligence Networks
The banking sector has matured collaborative frameworks that share anonymized fraud signals and attack patterns. P&C carriers can adopt similar models to stay ahead of rapidly evolving GenAI-driven schemes.
- Shared Provenance and Authenticity Ecosystems
As more industries adopt C2PA content credentials, insurers gain clear insight into where digital content comes from and how it moves across systems
Collaboration helps insurers move beyond isolated detection to a shared defense, speeding up the industry’s response to synthetic threats.
Conclusions
- AI-generated media fraud is a persistent and accelerating threat that is reshaping how insurers approach trust, verification, and customer protection. The insurers that succeed will invest in detecting manipulated content while modernizing the entire lifecycle of claim intake, validation, and customer support.
- The four pillars offer a practical way for insurers to respond to the synthetic media era. They blend advanced detection, human-centered design, operational integration, and cross-industry coordination into a unified strategy. Insurers who invest in these capabilities will be better positioned to defend against emergent threats while strengthening claimant trust.
- This calls for capabilities that work across media types, systems, and regions, supported by a modern core platform such as Guidewire. It also means investing in digital forensics talent, provenance-protected workflows, real-time verification tools, and customer-centric safeguards that protect the most vulnerable claimants from synthetic manipulation.
- Insurers who act now can reduce loss exposure, strengthen regulatory readiness, and maintain customer trust during the claims process. Those who fall behind risk operating blind in an environment where fraudsters are evolving faster than traditional controls. The synthetic era is here, and the industry’s response must be as adaptive, resilient, and intelligent as the threat itself.
References:
1 Shift Technologies: 2025-The year US P&C insurers must modernize fraud detection- here’s why, September 5, 2025 https://www.shift-technology.com/resources/reports-and-insights/modernize-fraud-detection
2 Deloitte, Property and casualty carriers can wit the fight against insurance fraud, April 24, 2025 https://www.deloitte.com/us/en/insights/industry/financial-services/financial-services-industry-predictions/2025/ai-to-fight-insurance-fraud.html