Vision AI: AI returns fraud detection and grading at the point of return
The customer uploads photos or a short video when they start a return, warranty claim or damage claim. Vision AI checks the item against your product book, spots photo fraud, decides eligibility before a label is issued, pre-grades the unit and routes it straight to a store, a refurbisher or a scratch-and-dent vendor. Fewer scrapped returns, fewer fraudulent refunds, one model.
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What happens at return initiation with Vision AI
Most returns platforms decide a return from order data: what was bought, when, for how much, and how often this customer returns. Vision AI looks at the item itself. When a customer starts a return, a warranty claim or a damage claim in the ReverseLogix portal, they are asked for photos or a short video. A proprietary model, trained on your product book and on generic products in the same family, reads those images and answers four questions in seconds:
- Is this the item that was sold? Model, colour, size and accessories are matched to the order line.
- Is it eligible? Your return, warranty and damage rules run against what the photo shows, not what the customer typed.
- Is the photo real? Reused, edited, stock or mismatched images are flagged as photo fraud.
- What condition is it in? The unit is pre-graded, with visible faults and likely repairs recorded before it ships.
The answers drive the outcome: approve, deny, or approve with a route. Denials happen before a label exists, so the unit never comes in the door. Approvals carry a grade and a destination, so the unit goes where it recovers the most value, not to a central returns center to be sorted weeks later.
Proven outcomes across enterprise deployments
Deployment-level numbers, each traceable to a named source.
$25M+
in savings after ReverseLogix deployment
Large Global Appliance Manufacturer
50-60%
faster returns vs a legacy SAP system
Samsonite
25%
higher customer satisfaction
Jabra
4-6 wks
standard go-live (vs 12-18 mo ERP build)
ReverseLogix deployment data
AI photo fraud detection: deny the return before it comes in the door
Return fraud detection software from fraud vendors scores identity and behaviour. That catches serial abusers and stolen tender. It does not catch the customer who sends back last season’s jacket, photographs a working product to claim it is broken, or uploads the same cracked-screen image on three claims. Vision AI closes that gap because it inspects the evidence, not the account.
- Wardrobing detection. Wear, missing tags, washed labels and use marks are visible in the photo and compared with the item’s condition at sale.
- Wrong item and empty box. The photographed item is matched to the SKU sold. A different model, a counterfeit or a rock in a box is denied at initiation.
- Reused and edited images. Photos are checked against prior claims and for manipulation. The same damage image cannot support a second claim.
- Undisclosed damage on warranty and damage claims. Impact damage, liquid damage and misuse are graded from the image before the claim is approved.
Every denial carries the reason and the image, so customer service can uphold it in one reply. Every approval carries the same record, so the warehouse receives a known item in a known condition. Vision AI works alongside the policy and risk rules in ReverseLogix return fraud prevention, which handle the order-data side.
Automated returns grading and disposition: reroute instead of scrap
The second cost of a returns center is the unit that arrives, waits, gets inspected and is written off. By the time it is graded, the season has moved on, the box is damaged and the resale value has fallen. Between 8% and 20% of enterprise returns end this way: scrapped, salvaged for parts, liquidated for pennies or donated.
Vision AI grades the unit at initiation, from the customer’s photos, and picks the destination the grade deserves. A grade A unit with tags goes to the nearest store for restock. A grade B unit with a scuff goes to a scratch-and-dent vendor or an outlet channel. A unit with a repairable fault goes to a refurbisher with the fault already logged. Only the unit that is truly unsellable goes to salvage, and it goes there directly, without a stop at the returns center.
Vision AI runs at 85% confidence today. Conservatively, that means 85% of the returns you scrap, salvage or donate can be rerouted to a destination that recovers resale value, and about half of fraudulent returns and claims can be denied before they ship. The calculator below uses those figures as defaults; lower them to match your own risk appetite.
Scrap and fraud savings calculator
Four short steps. Enter your returns and claims, what gets scrapped today, what fraud looks like in your operation, and how aggressive you want Vision AI to be. The estimate builds as you answer. Download the report for the line items.
See Vision AI run against your own product catalog.
What scrapped and fraudulent returns cost today
Fraudulent returns and claims cost U.S. retailers $103 billion in 2024, and 15.14% of all returns were judged fraudulent, according to Appriss Retail's 2024 report with the NRF. Total merchandise returns reached $685 billion, 13.21% of retail sales. Sixty percent of retailers reported wardrobing.
On the scrap side, an Optoro-commissioned study cited by Retail Dive put returned goods sent to landfill in the U.S. at 5 billion pounds a year. Every one of those units was received, handled and inspected before it was thrown away. Vision AI is built to keep them out of the returns center in the first place.
For the labor side of the same problem, run the returns ROI calculator; for the whole bill, the total cost of returns calculator.
How Vision AI compares to Loop, Narvar, AfterShip, Optoro and ClaimLane
Loop Returns scores return risk from order size, discounts, customer history and geography. Narvar's Shield does the same across its network and adds delivery-claim fraud. AfterShip runs rules-based anti-fraud workflows and a risk score. All three decide from data about the order and the customer; none of them looks at the item.
Optoro's SmartDisposition routes a unit after it has been received and graded at a returns facility. ClaimLane has written about AI image recognition for warranty claims but does not ship it as a named product. Vision AI is the only returns platform feature that inspects the photo itself, at initiation, and uses one model for eligibility, photo fraud, grading and routing. Compare the full platforms on our Loop, Narvar and Optoro pages.
Vision AI questions, answered
It is a model that reads the photos or video a customer uploads at return initiation and checks whether the image is genuine, whether it shows the item that was sold, and whether the condition matches the claim. Vision AI flags reused, edited, stock and mismatched images and denies the return or claim before a shipping label is issued.
Yes. Wear marks, missing or reattached tags, washed labels and signs of use are visible in the customer's photos and are compared with the item's condition at sale. A worn item that does not meet the return policy is denied at initiation, with the image attached to the decision.
Automated returns grading assigns a condition grade, visible faults and likely repairs to a unit from images, before it ships. Vision AI runs at 85% confidence today against a customer's own product book. Units below the confidence threshold fall back to your standard inspection flow, so nothing is routed on a guess.
It works best with it. The model is trained on your product book, including images, specifications and accessories, and on generic products in the same family, so it recognises your SKUs and their common faults. New SKUs are covered by the family model until they are added.
Both, in one step. Triage: every approved return leaves initiation with a grade and a destination, so the warehouse, store or refurbisher receives a known unit. Fraud prevention: ineligible and fraudulent returns and claims are denied from the evidence before they come in the door. It runs inside ReverseLogix returns initiation and feeds returns processing, warranty management and recommerce.
See Vision AI run against your own product catalog
Evaluating fraud tools or a returns platform? Book a 30-minute call. A specialist walks your return, warranty and damage claim flow, loads a sample of your product book and shows what Vision AI approves, denies and reroutes, before any demonstration.
85%
model confidence today; scrap mitigation is capped there and fraud denial defaults to 50%
ReverseLogix Vision AI
