E-Commerce · Fraude en devoluciones y reembolsos

Visual Fraud Prevention

Generative AI is being used to add fake damage to product photos and submit them as refund evidence. Catch it before you issue the refund.

The Return Score reads the refund claim text, identifies what damage was described, and focuses the forensic scan on exactly those image regions.

Moda y vestimenta Entrega de alimentos Muebles y hogar Electrónica de consumo
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Woman holding jeans with damage
Photo by Freepik
Return Fraud Score
100 = fully AI-generated · 0 = authentic
0 / 100
0-50 50-70 70-80 80-100
Recommended action Require return / reject
Context Engine
1 Leyendo reclamación de reembolso
"Recibí los jeans con un agujero en el área del bolsillo trasero..."
2 Extrayendo reclamaciones de daño
agujero trasero
3 Dirigiendo análisis
Enfocando escaneo forense en la región del bolsillo trasero...
4 Puntuación de región
Límite de inpainting: 91 % · Discordancia de textura: 87 % · Tejido denim ausente: 94 %

How refund fraud works

Refund-without-return policies save millions in reverse logistics. But they also create an attack surface: submit a convincing photo of damage, and the refund is issued automatically.

01
Customer receives item
Product arrives in perfect condition. Customer opens the package and inspects the item.
02
Damage added in post
Using generative AI tools, the customer inpaints realistic-looking damage onto a photo of the product.
03
Fraudulent claim submitted
"Item arrived with burn hole in front. Requesting full refund."
04
Manual review can't keep up
Human reviewers process thousands of claims daily. AI-generated damage is visually indistinguishable at scale.

Real damage vs. AI-generated damage

"Received the sweater with a burn hole in the front panel. The fabric is visibly singed and damaged."

Real t-shirt with damage
Scan Region
Imagen generada por IA
Texto de reclamación: "Recibí el suéter con un agujero quemado en el panel frontal. La tela está visiblemente chamuscada y dañada."
El daño es auténtico
Distorsión de fibra
92%
Gradiente de quemado
89%
Continuidad de textura
94%
Firma de ruido
88%
12 / 100 Return Score
AI-generated t-shirt with fake damage
Anomaly
Imagen generada por IA
Texto de reclamación: "Recibí el suéter con un agujero quemado en el panel frontal. La tela está visiblemente chamuscada y dañada."
Inpainting IA · fraude detectado
Distorsión de fibra
92% anomaly
Gradiente de quemado
89% anomaly
Continuidad de textura
91% anomaly
Firma de ruido
87% anomaly
91 / 100 Return Score

Your rules. Our intelligence.

You define the thresholds. We provide the score. Automate refund decisions or route claims to the right team based on risk level.

0-50
Instant refund

Damage is consistent with the claim. Approve the refund automatically.

50-70
Request additional evidence

Some signals are ambiguous. Ask the customer for more photos or details.

70-80
Manual review

Multiple forensic signals triggered. Route to a human reviewer for inspection.

80-100
Require physical return or reject

High confidence of AI manipulation. Require the item to be returned before issuing any refund.

0%
Aumento del fraude IA en devoluciones (2023–2025)
0%
De las devoluciones de e-commerce son fraudulentas
+0%
Aumento del fraude en devoluciones interanual
0%
De los minoristas reportan fraude basado en fotos

Know your refund fraud exposure

Run your refund claims through our forensic engine. See what percentage of damage photos contain AI manipulation.

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