The antifraud market is undergoing a structural shift, but most companies still haven’t grasped its scale. In recent years, major players have stopped positioning themselves as standalone solutions and started talking about orchestration platforms instead, in an attempt to respond to rising operational complexity and digital risk.
72% of Organizations Under Pressure: What the Antifraud Market Finally Understood
This shift is happening at a moment of rising pressure. According to the World Economic Forum’s Global Cybersecurity Outlook 2025, 72% of organizations reported an increase in cyber risk. At the same time, 54% of companies cite managing multiple vendors as the main bottleneck in mitigating those threats.
In practice, the market is starting to realize the problem is no longer a lack of technology. The new challenge lies in the ability to connect tools, interpret risk signals, and turn different solutions into genuinely intelligent journeys.
Antifraud Orchestration vs. Verification Intelligence Hub: Where the Difference Begins
This is exactly where a still poorly understood question comes in: is there a real difference between an orchestration model and an intelligent hub?
The two concepts often appear side by side, but they rest on very different logics. Orchestration organizes flows between vendors, while an intelligent hub model adds a continuous layer of intelligence, context, and decision-making across the entire operation.
And that raises an inevitable question: can standalone tools still handle today’s fraud landscape on their own?
Most Companies Are Running an API Hub and Calling It Intelligence
A study by LexisNexis with Oxford Economics uncovered an uncomfortable finding: most companies that believe they’re running an intelligent operation are actually running an API hub. They connect three or four vendors, layer a static rules engine on top, and give the whole package an appealing name.
In theory, orchestration should work as the logic layer that governs decisions, timing, and the intensity of validations. In practice, the concept has been hollowed out and reduced to simple technical integration, falling short of the strategic intelligence it promises.
A few criteria help tell the two models apart in practice:
- Learning: orchestration executes manually defined rules; the hub learns from every transaction and updates context continuously.
- Context: orchestration passes signals from one vendor to another; the hub accumulates history and interprets the current signal based on all prior behavior.
- Adaptation: orchestration reacts to the incident; the hub adjusts the route before the pattern repeats.
- Intelligence: orchestration connects solutions; the hub generates a decision layer that no isolated component can replicate.
- False positives: in orchestration, the static rules engine tends to drive up wrongful blocks; in the hub, precision improves as the model accumulates context.
Fraud as a Service: When AI Became the Attacker’s Tool Too
This shift is gaining even more momentum because the threat itself has evolved in sophisticated ways. We’ve entered the era of Fraud as a Service (FaaS). The fraudster of 2026 doesn’t work alone: they run artificial intelligence to produce deepfakes, synthetic identities, and autonomous agents at scale.
Investment in fraud prevention is projected to jump to USD 243 billion by 2034, according to the Fraud Detection & Prevention Market 2025 report, yet U.S. companies lost nearly 10% of their revenue to fraud in 2025, according to TransUnion’s H2 2025 Update to the Top Fraud Trends Report. If we’re spending more, why isn’t fraud going down?
The answer lies in the fact that AI, once our biggest advantage, has become a commodity. When criminals get access to the same open-source models and APIs to manipulate AI itself and exploit vulnerabilities, competitive advantage stops living in the tool and shifts to the intelligence that runs the decision architecture.
The impact on ROI is direct. Operations that depend on static rules and simple integrations tend to rack up rising costs from manual review, high false positive rates, and update cycles that lag behind how fast attack patterns evolve. A hub that learns continuously drives those costs down as it accumulates context, because every past decision feeds the next one with more precision.
The Hub Doesn’t Just Connect Flights. It Learns from Every Route and Adapts When One Fails
An airport hub doesn’t become the biggest in the world just by connecting flights from different origins. It becomes the biggest because its logistical intelligence is so sophisticated that the entire system gravitates around it. Remove a route, and the hub adapts instantly. Remove the hub, and the whole system collapses.
A Verification Intelligence Hub works the same way: it’s the gravitational center that concentrates, optimizes, and learns from everything that passes through it. It doesn’t just relay a vendor’s signal. It generates a layer of context and history that no isolated component or simple integration can replicate.
In practice, that means every transaction feeds the model, context accumulates, and the next signal gets read with more precision than the last one. The result is a system that doesn’t just react to the incident; it grows more resilient and more efficient while the contest is still playing out.
Given this opportunity, the big discussion in 2026 is about learning faster and shortening the distance between a new attack pattern and its correction. This is where antifraud strategy stops being a set of rigid controls and starts behaving like a living system: an organism that doesn’t just react to the incident, but becomes more resilient and more efficient while the contest is still underway.
At Certta, this translates into an architecture that brings together the full context of the user journey across overlapping layers of intelligence. Every signal processed enriches the model and lowers the cost of the next decision, whether in precision, speed, or the end user’s experience.
The Right Questions to Ask Before Choosing an Antifraud Architecture Model
In the end, the line between orchestration and an intelligent hub may still be blurry for part of the market, and that helps explain why so many companies keep buying technology without a clear sense of the problem they need to solve.
The semantic debate is real, of course. But it becomes secondary next to more structural questions:
- What is the company’s operational context?
- How much risk can it tolerate?
- What kind of experience does it want to deliver?
- Does it have the maturity to operate multiple vendors?
- Is the goal simply to connect solutions, or to generate continuous intelligence across the entire journey?
Because in a market increasingly squeezed by fraud, efficiency, and user experience, understanding all of these questions is what actually helps identify which model makes the most sense for your operation.
And Certta offers solutions for a wide variety of scenarios. Learn more at Flow and Hubby: no-code anti-fraud with AI.
