How FraudLens Detects Fraud Automatically

5 AI-powered detection layers working together. Every claim photo analyzed in 5 seconds. Clear verdict: Approve, Review, or Deny.

Insurance Fraud Just Got Impossible to Detect

🤖

AI-Generated Photos

Fraudsters use Midjourney and DALL-E to create perfect damage photos. Your adjusters can't tell real from fake anymore.

+300% increase since 2021
📍

Location Fraud

Claims say "accident in Nicosia" but photo was taken in Limassol. Manual review misses GPS mismatches and visual inconsistencies.

15-20% of fraudulent claims
📝

Description Mismatches

Customer writes "minor scratch" but photo shows major collision. Or claims rear damage, shows front. Adjusters miss these in high-volume processing.

25-30% of suspicious claims
🔄

Recycled Photos

Same damage photo used across multiple claims, or downloaded from internet. Impossible to catch without reverse image search at scale.

10-15% of fraud attempts

The Cost of Missing Fraud:

€80B+ Lost globally to insurance fraud annually
€150-225M Lost in Cyprus alone (10-15% of premiums)
60-70% Fraud detection rate with manual review
€3K-5K Average fraudulent claim value

Our Solution: 5-Layer AI Detection

1

AI-Generated Image Detection

What It Does

Identifies photos created by Midjourney, DALL-E, Stable Diffusion, and other AI generators with 95%+ accuracy.

How It Works

Deep learning models analyze pixel patterns, noise signatures, and visual artifacts invisible to human eyes. Our system checks:

  • Synthetic pattern detection (AI fingerprints)
  • Natural camera noise vs artificial noise
  • Lighting and shadow consistency
  • Model-specific signatures (Midjourney, DALL-E, etc.)
Technology: Hive AI + proprietary algorithms
Example Catch: Customer submits "perfect" damage photo with no visible flaws. FraudLens detects Midjourney signature in 2 seconds. Claim denied, €4,200 saved.
Detection Results
AI Generation Detected Confidence: 94%
2

Metadata Forensics

What It Does

Analyzes EXIF data for tampering, inconsistencies, and manipulation traces.

What We Check

  • Device Consistency: iPhone model with Samsung make = fraud
  • GPS Coordinates: Location matches claimed incident location
  • Timestamp Validation: Photo age vs claim submission date
  • Software Field: Photoshop, GIMP, screenshot tools detected
  • Stripped Metadata: Intentionally removed EXIF to hide evidence
Example Catch: Photo claims to be from accident scene but GPS shows it was taken 67km away 2 weeks earlier. Metadata also shows Photoshop editing. Fraud score: 85. Investigation opened.
Metadata Analysis
3

Claim-Photo Consistency Check

What It Does

Compares written claim description with actual photo content using GPT-4 Vision and natural language processing.

What We Detect

  • "Rear bumper" claim, photo shows front damage
  • "Minor scratch" description, major collision visible
  • Missing angles for claimed damage areas
  • Severity mismatch (claimed minor, shows major)
  • Vehicle type inconsistency
Technology: GPT-4 Vision + NLP text analysis
Example Catch: Claim says "small dent from parking" but photo shows high-speed collision damage with airbag deployment. Consistency score: 15/100. Red flag raised.
Consistency Analysis
Claimed: "Minor rear bumper scratch"
Photo Shows: "Major front-end collision"
⚠️ Critical Mismatch Detected
4

Location Verification

What It Does

Confirms photo was taken at claimed accident location through three-level verification.

Verification Levels

  • GPS Validation: Distance between photo location and claimed location (threshold: 5km)
  • Visual Matching: Background comparison with Google Street View
  • Landmark Detection: Buildings, signs, geography match claimed area
Technology: GPS validation + Google Maps API + Computer Vision
Example Catch: Claim says "Nicosia city center" but photo background shows Limassol Marina (67km away). Street View comparison confirms location mismatch. Fraud detected.
Location Check
Distance: 67km
Claimed: Nicosia
Actual: Limassol
5

Behavioral Pattern Analysis

What It Does

Tracks customer claim history and identifies fraud rings through pattern recognition.

What We Analyze

  • Claim Frequency: 3 claims in 6 months vs industry average 0.3/year
  • Claim Amounts: Consistently at policy limits (suspicious pattern)
  • Timing Patterns: All claims on Fridays, or before holidays
  • Fraud Rings: Connected accounts with similar patterns
  • Geographic Patterns: Multiple claims from same locations
Example Catch: Customer files 5th claim this year (average: 0.3/year). All on Fridays. All with missing GPS. Pattern matches known fraud ring. Account flagged for investigation.
Behavioral Profile
🚩 5 claims in 12 months
🚩 All claims on Fridays
🚩 No GPS in any photos

The Result: One Clear Verdict

18/100
APPROVE

Low fraud risk. All checks passed. Process claim immediately.

65/100
REVIEW

Medium risk. GPS missing + old timestamp. Request additional photos.

94/100
DENY

High fraud risk. AI-generated image + location mismatch. Flag for investigation.

Simple 3-Step Process

1

Customer Submits Claim

Customer uploads damage photo through your existing claims portal or mobile app. Includes claim description and optional GPS location.

2

FraudLens Analyzes (5 seconds)

Photo automatically sent to FraudLens API. 5-layer analysis runs in parallel. AI checks completed before adjuster opens claim.

3

Adjuster Gets Clear Verdict

Claim appears in adjuster queue with fraud score and recommendation visible. High-risk claims automatically flagged for review.

Integration Options

API Integration

Add one API call to your claims workflow. 30-minute setup.

Browser Extension

Works alongside existing portal. No code changes needed.

Standalone Web Interface

Use our demo interface for spot checks. No integration required.

Calculate Your Savings

Fraudulent claims per month: 50
FraudLens catches (95% accuracy): 47
Monthly savings: €141,000
Annual savings: €1,692,000
FraudLens cost: €699/month
ROI: 20,129%

*Calculations based on industry averages. Actual results vary by company.

Simple, Transparent Pricing

No hidden fees. No long-term contracts. Cancel anytime.

Starter

€299 /month
  • ✓ 500 analyses/month
  • ✓ All 5 detection layers
  • ✓ PDF reports
  • ✓ API access
  • ✓ Email support
  • ✓ 30-day free trial
Start Free Trial

Best for: 100-500 claims/month

Business

€1,499 /month
  • ✓ 5,000 analyses/month
  • ✓ All features from Professional
  • ✓ White-label reports
  • ✓ Dedicated account manager
  • ✓ SLA guarantee (99.9% uptime)
  • ✓ Custom integration support
  • ✓ Team training included
  • ✓ 30-day free trial
Start Free Trial

Best for: 2,000-5,000 claims/month

Enterprise

Custom pricing
  • ✓ Unlimited analyses
  • ✓ All features from Business
  • ✓ Multi-tenancy
  • ✓ On-premise deployment option
  • ✓ Custom AI model training
  • ✓ 24/7 support
  • ✓ Legal & compliance support
  • ✓ Volume discounts
Contact Sales

Best for: 5,000+ claims/month

Frequently Asked Questions

How accurate is FraudLens?

95%+ fraud detection rate based on pilot testing. Less than 2% false positive rate (flagging legitimate claims as fraud). Accuracy improves over time as AI learns from your specific claim patterns.

How long does analysis take?

Typically 3-8 seconds per photo. Complex images with many details may take up to 10 seconds. Much faster than 30+ minute manual review.

What if a legitimate claim gets flagged?

FraudLens provides a risk score and recommendation, not a final decision. Your adjusters review flagged claims and make final call. System explains WHY it flagged (e.g., "GPS missing") so adjusters can request additional proof.

Do we need IT department to integrate?

No. API integration is simple - one POST request. Most companies integrate in 30 minutes. We provide code examples in Python, JavaScript, PHP. Or use our standalone web interface (no integration needed).

Is customer data secure?

Yes. Bank-level AES-256 encryption at rest, TLS 1.3 in transit. GDPR compliant. Data stored in EU. Photos automatically deleted after 90 days. SOC2 compliance in progress.

What languages do you support?

Currently English and Greek for UI and reports. Claim descriptions can be in any language - we use multilingual AI models. Additional languages available on request.

Can FraudLens replace human adjusters?

No. FraudLens is a decision support tool, not a replacement. It automates initial screening and flags high-risk claims, but humans make final decisions. Think of it as "AI assistant" for adjusters.

Do you offer a free trial?

Yes! 30-day free trial on all paid plans. No credit card required. Full access to all features. Can analyze up to 100 claims during trial. Cancel anytime with one click.

Ready to Stop Fraud?

Join insurance companies already using FraudLens to catch fraud automatically and save thousands monthly.

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