Global trade moves at breakneck speed, but the systems designed to protect it often lag behind. Modern supply chains face shifting trade policies, tight regulatory scrutiny, and sophisticated fraud schemes that exploit visibility gaps across borders. Traditional fraud detection relies heavily on manual, document-by-document inspections. Because bad actors routinely craft individual paperwork that looks entirely legitimate on the surface, high-stakes discrepancies slip past compliance teams every day, costing businesses millions and stalling legitimate commerce.
Toronto-based technology firm YDelay tackles this operational vulnerability directly with its new Trade Fraud Risk Intelligence Framework. By connecting fragmented physical checkpoints with digital records, the framework identifies deceptive patterns hidden between the lines of standard trade documentation. In this executive interview, Abhi Arora, Founder and Managing Director of YDelay, unpacks why isolated document checks fail, how automated cross-correlation transforms risk assessment, and what leaders must do to secure modern cross-border logistics.
Q: You have noted that trade fraud rarely announces itself in a single document. Why are traditional, document-by-document compliance reviews failing to catch modern cross-border fraud?
Abhi Arora: Global trade is operating at enormous scale and increasing complexity. In 2025, global trade in goods and commercial services reached approximately US$34.9 trillion, an 8% increase from the previous year.
Canada alone exported approximately $562.7 billion in merchandise to the United States in 2025, while its total global merchandise imports reached $807.1 billion.
At this scale, even small gaps in visibility can have significant operational and financial consequences.
Traditional compliance reviews tend to look at documents in isolation — a manifest, commercial invoice, customs declaration, shipment record, or transaction. But trade fraud is becoming much more sophisticated and scalable.
In the past, executing fraud across a large number of shipments could require multiple people, significant time, and resources. With AI, a single bad actor can potentially manipulate information across hundreds of shipments much faster.That changes how we need to detect fraud. The risk often becomes visible only when you connect the entire shipment journey — documents, parties, transactions, routing, product information, and historical patterns.
The complexity of modern trade makes that connected view increasingly important. For example, Statistics Canada found that in 2024, more than 40% of Canada’s imports originating in Mexico were shipped to Canada from the United States, while more than 25% of goods originating in China were first imported into the U.S. This shows that the physical movement of goods and the flow of trade data do not always follow a simple origin-to-destination path.
At YDelay, our experience in high-volume logistics environments has shown us the value of analyzing millions of data points across manifests, shipment events, customs data, product information, dollar values, routing, and historical behaviour using our proprietary technology.
A manifest may look completely normal on its own. But when compared against the commodity, value, origin, destination, shipper history, and routing, anomalies can begin to surface.
That is the shift YDelay is focused on: moving beyond document-by-document compliance to connected intelligence that helps organizations identify potential fraud and risk earlier.
Q: YDelay addresses this blind spot through a five-stage intelligence pipeline: Scan, Extract, Correlate, Detect, and Decide. Could you walk us through how this pipeline functions during a live cross-border shipment?
Abhi Arora: As products move across countries, warehouses, and transporters, YDelay continuously analyzes the information surrounding each shipment. We scan incoming shipment data, extract key information from manifests and supporting documents, and correlate it across customs data, routing, parties, transactions, and historical patterns.
From there, our technology detects anomalies, inconsistencies, and combinations of signals that may indicate elevated risk. Finally, we turn those findings into actionable risk intelligence, providing teams with not only an alert, but also the context behind it.
The objective is to identify potential issues earlier in the shipment journey, enabling organizations to focus resources on higher-risk shipments before they become larger compliance, fraud, financial, or operational challenges.
Beyond risk detection, this can reduce financial losses, save time and resources, and help protect organizations from regulatory exposure and reputational damage. It also supports the broader mandate of protecting border security, strengthening regulatory compliance, and helping ensure goods entering a country are safe, compliant, and trusted.
We believe technology should create both commercial and public value by contributing to a more secure, resilient, and efficient trade ecosystem that benefits businesses, government agencies, and the country as a whole.
Q: Discrepancies often range from subtle Harmonized System (HS)-code variations to duplicate tracking numbers and routing shifts. How does your framework correlate these independent data signals to generate an actionable risk score?
Abhi Arora: YDelay’s proprietary platform analyzes HS-code variations, duplicate tracking numbers, declared values, routing changes, and shipment history to generate explainable risk scores.
By automating the identification of high-risk shipments, it enables compliance and logistics teams to focus resources where they matter most, improving decision-making, accelerating investigations, and reducing operational risk.
The benefit is simple: teams can focus attention on the highest-risk transactions and understand exactly what triggered the alert, helping them investigate faster, reduce false positives, and intervene earlier.
Q: A major friction point for investigators is “black-box” alerting. How does YDelay ensure that risk scores remain fully explainable and auditable when a shipment is placed on hold?
Abhi Arora: YDelay is designed to provide transparency behind every alert, not simply generate a risk score. When a shipment is flagged, organizations can see the specific data points, discrepancies, and patterns that contributed to the assessment and understand why the shipment was identified as higher risk. Risk thresholds, rating scales, and alerting mechanisms can also be aligned to each organization’s operational and compliance requirements.
Unlike black-box alerting systems that provide little visibility into how a decision was reached, YDelay presents the underlying intelligence and evidence behind every alert. An assessment may be influenced by inconsistencies in declared value, classification, weight, shipment history, involved parties, routing, or other anomalous patterns, allowing teams to review, validate, and understand the underlying risk.
This creates a clear and auditable trail from source data to final alert. Ultimately, YDelay provides the intelligence and evidence, while the organization retains control of the final decision, enabling faster investigations, stronger governance, and more informed decisions on whether a shipment should proceed or require further review.
Q: Many logistics and customs operations rely on legacy infrastructure. How does YDelay integrate with existing ERP systems, customs databases, and warehouse tools without forcing organizations into a costly rip-and-replace cycle?
Abhi Arora: YDelay enables organizations to modernize quickly, securely, and cost-effectively without a major systems overhaul. Rather than forcing a costly rip-and-replace initiative, the platform integrates with existing ERP systems, customs and brokerage platforms, warehouse management systems, and other shipment data sources through APIs, or other secure data connections.
Our role is to create an intelligence layer across those systems, bringing fragmented information together so it can be analyzed consistently and securely. This allows YDelay to identify discrepancies, patterns, and potential risks while existing systems continue to perform their core functions.
The result is faster adoption, lower implementation costs, and reduced operational disruption. Organizations can continue working within familiar processes while gaining AI-driven intelligence, automation, and decision support across the cross-border shipment journey.
As regulatory requirements, business needs, and security risks evolve, YDelay helps organizations adapt quickly without re-engineering their underlying technology investments.
Q: YDelay structured this architecture to be roughly 70 percent standardized and 30 percent configurable. How do you see this intelligence framework expanding into broader operational risk areas beyond cargo shipping?
Abhi Arora: YDelay is designed around a simple principle: most organizations share a common operational foundation, even when their industries and data are different. That is why we have structured the architecture to be approximately 70% standardized and 30% configurable.
The standardized 70% covers the core intelligence capabilities — capturing, validating, enriching, and analyzing data; identifying patterns and anomalies; applying business rules; and supporting secure, auditable decision-making. The configurable 30% is where industry-specific regulations, policies, workflows, and business requirements are applied.
That architecture allows us to extend the same intelligence capabilities beyond trade and logistics. In financial services, for example, the framework can help identify unusual transactions, duplicate activity, or policy exceptions. In manufacturing and food distribution, it can connect supplier, traceability, quality, and compliance data to surface potential risks earlier. In healthcare and other regulated environments, the same approach can be applied to billing, procurement, access, compliance, and operational controls.
The broader opportunity is to create an operational intelligence layer across systems that were never designed to work together. Wherever products, money, information, or regulated activity move through a process, important risk signals can become fragmented across different systems and teams.
Our vision is therefore bigger than trade fraud detection. We see YDelay as an Operational Intelligence and Risk Management Engine that connects those signals, applies the right business context, and helps organizations identify risk earlier while keeping people in control of the final decision.
To learn more visit https://ydelay.com
Sources for the editors:
- World Trade Organization. “World Trade Statistics 2025.” 2026.
- Statistics Canada. “Canada’s Balance of International Payments, Fourth Quarter 2025.” Feb. 26, 2026.
- Statistics Canada. “Canadian International Merchandise Trade, January 2025.” March 6, 2025.
