Manipulated Image Detection AI for Insurance

Inaza’s Altered Image Detection Model automatically identifies digitally manipulated or tampered images, helping insurers reduce fraudulent claims and ensure claim authenticity.
Altered Image Detection AI

Detect Manipulated Images & Prevent Fraud

What value does Inaza's AI Image Manipulation Detection model provide to the various teams in Insurance?

Underwriting Teams

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Better Risk Assessment – Stop altered images from impacting how you assess risk and underwrite policies.

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Fraud Prevention – Identify images that have been altered to hide pre-existing damage or commercial vehicle markers.

Claims
Teams

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Instant Image Fraud Detection – Identify manipulated or edited claim photos before payouts.

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Reduce Payout Errors – Prevents fraudulent claims from slipping through manual reviews.

Fraud & SIU Teams

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Advanced Tampering Detection – Flags images with AI-driven forensic analysis.

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Automated Alerts for Suspicious Claims – Ensures high-risk claims receive extra scrutiny.

How AI-Powered Altered Image Detection Works

Inaza’s Altered Image Detection Model provides insurers with a seamless, automated way to verify image authenticity.

Image Metadata & Pixel Analysis

Scans image metadata and pixel patterns to detect anomalies or alterations.
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AI-Powered Cross Checking

Compares submitted images against past records to identify inconsistencies.
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Real-Time Fraud Flagging Alerts

Automatically flags suspect images for further investigation.
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Instant Claims & UW Integration

Works within existing, Underwriting, FNOL and claims systems to enhance fraud detection without disrupting workflows.
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