Fraudulent Invoice & Receipt Detection

Catch manually tampered, photoshopped or AI-generated invoices before payout. Identify physical manipulation, metadata anomalies, and fraud indicators with explainable scoring. Access it now as a standalone solution with Inaza Central.
fraudulent invoice detection

10-20%

Of all P&C claims are fraudulent.

$308 Billion

The amount paid out on fraudulent claims in the US each year.

Stop Paying out on Fraudulent Invoices

Invoice fraud doesn’t wait for audits. Every week, carriers lose thousands to doctored receipts, regenerated PDFs, or clever AI edits that slip through manual checks.

Inaza Central’s Fraudulent Invoice Detection module spots the red flags before a payout is made—so your claims team can focus on genuine cases, not digital counterfeits.

Prevent payouts on manipulated or AI-generated invoices
Catch metadata inconsistencies instantly
Explainable indicators your compliance team can defend
Deploy via drag-and-drop UI or API — no IT overhaul

From Problem to Solution in Minutes - not months.

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Deploy Into your Workflows

When you're ready to go live, Inaza Central provides fully documented, production-grade APIs for every solution.Whether you're automating invoice validation, underwriting data ingestion, or claims triage — everything is available in a format your developers can implement in hours, not weeks.
Underwriting Automation
FNOL & Fraud Automation
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Smarter Detection, Built for Real-World Fraud

Claims teams shouldn’t have to play forensic accountant. This Inaza Central solution automatically identifies document edits, calculation errors, and metadata inconsistencies that indicate manipulation — without slowing down approvals or overloading adjusters.
invoice fraud detection
Physical tamper detection
Catch the human touch in digital form. Detect whiteout marks, handwriting additions, and altered line items — across scans, photos, or PDFs.
invoice fraud detection
Metadata anomaly analysis
Inspect file properties and hidden data for red flags — timestamp mismatches, device ID swaps, inconsistent file structures, and re-exported PDFs. It surfaces subtle discrepancies invisible to human review.
Cost Control in insurance
Mathematical consistency checks
Automatically verify invoice totals and line-item sums. The engine spots rounding discrepancies, mismatched tax calculations, and arithmetic errors that often signal manual manipulation or duplicate entries.
invoice fraud detection
Gen AI content detection
Distinguish genuine documents from AI-generated fabrications. The model identifies synthetic textures, font irregularities, and metadata artifacts unique to genAI-created or regenerated invoices.
invoice fraud detection
Threshold tuning & explainable scoring
Adjust detection sensitivity to align with your fraud tolerance. Every score includes clear indicators, confidence levels, and visual evidence so compliance and SIU teams can defend each decision.

Supercharge your Systems today!

Join other groundbreaking MGAs, Carriers, Reinsurers, Brokers and TPAs revolutionizing their processes with Inaza!
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