Billion Dollars in Lost Revenue
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Canada’s retail signals get distorted when vehicles are bought domestically and quietly diverted for resale abroad—a grey-market (parallel import) pipeline that inflates demand, skews allocation, and invites VIN-duping and insurance fraud. ParallelProof validates the market by detecting export-intent before delivery, flagging known exporters and high-risk patterns at the point of sale. The result: OEMs protect allocation and brand equity, insurers and lenders reduce losses from collateral flight and staged claims, and law-enforcement gains actionable export routes for theft recovery—preventing billions in downstream revenue leakage across the Canadian ecosystem.
Billion Dollars in Lost Revenue
Brands Affected
Vehicles Exported
Major Regions Vehicles Being Exported From
Inventory shocks and shifting economics have fueled a sharp rise in grey-market exporting, VIN duping, theft, and fraud. Vehicles purchased in Canada are increasingly diverted for resale abroad, distorting demand, exposing dealers and OEMs to charge-backs, and raising losses for insurers, lenders, and law enforcement. ParallelProof brings validation at the point of decision to stop these losses before they occur.
Identify export hotspots and high-risk models to protect allocation.
Adjust inflated market share where exports distort sales signals.
Flag known exporters and suspicious buyer patterns pre-delivery.
Documented checks reduce financial and compliance exposure.
Shorten risk review.
Validate export timing vs claim timing; spot staged or misrepresented losses.
Export route + date narrows the search window and boosts recovery odds.
Detect export-intent before funding; protect residual values.
Systematic screening lowers delinquency and loss severity.
Export signals help focus on when/where across borders.
Shareable, time-stamped intelligence supports case building.
See how ParallelProof helps OEMs, dealers, insurers, lenders, and investigators prevent VIN duping, stop export fraud, and accelerate theft recovery—with methodology, data signals, and real case outcomes.