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When Fraud Prevention Becomes a Growth Problem
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Automate your manual tasks with AI-powered Software as a Service
You don’t need in-house AI tools to do this, most software providers will be doing the heavy lifting for you
2
Step up your SEO and AI Optimisation (AIO) strategy
Make sure your experiences are easily discoverable in consumer-generated itineraries. If you’ve invested in search engine optimisation (SEO) in the past, a lot of that work will be paying off now, but if not, it’s never too late to tag your images, set meta descriptions and make sure your most important content is machine readable.
3
Experiment cautiously with customer facing AI tools
If you’re not yet using any AI in your business, now is not the time to rip out your search function on your website and replace it with an AI chat bot! As an end consumer you probably know how frustrating it can be to deal with a poorly trained bot. Instead, find a problem you have which is worth solving but not business critical to start learning in a low-risk environment.
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For years, fraud prevention in payments has been treated as a technical safeguard. Add 3DS, rely on a risk score, block a few countries, and move on.
That model no longer reflects reality.
Fraud today is automated, distributed, and deliberately adaptive. Which means fraud controls need to be adaptive too, capable of evolving as patterns change, rather than locking businesses into static defences that age quickly.
For travel businesses, the impact is sharper than in most sectors.
High-value transactions, delayed fulfilment, complex booking journeys, and a mix of online, agent-assisted, and MOTO payments create a risk profile that generic fraud tools were never designed to handle. Yet many travel merchants are still relying on exactly those tools.
The result is a familiar trade-off: tighten controls and damage conversion, or loosen them and absorb the risk.
Most fraud systems take a blunt approach. Either they rely on opaque third-party scores that block transactions without explanation, or they enforce rigid rules that apply equally across all customers, markets, and booking types.
In travel, this quickly becomes counterproductive.
A legitimate traveller booking a complex, cross-border itinerary can look risky on paper. At the same time, a coordinated card-testing attack can pass unnoticed if it stays just below static thresholds.
When fraud controls lack context, they stop being protective and start becoming obstructive. Conversion drops, customer experience suffers, and operations teams spend increasing amounts of time reviewing edge cases that should never have been flagged in the first place.
At that point, fraud prevention stops being a security function and becomes a growth problem.
The underlying issue is not that travel businesses need more fraud rules. It is that they need better signals, connected together, and the ability to decide how those signals should be used.
Modern fraud is behavioural. It reveals itself through patterns over time, through inconsistencies between customer, card, device, and location, and through the misuse of mechanisms like 3DS rather than simple card theft.
Addressing that requires a connected, layered approach to risk, where signals across the payment lifecycle are assessed together, not in isolation. It also requires acknowledging a reality many fraud tools ignore: not every travel business has the same risk profile, booking model, or tolerance for friction.
What is acceptable risk for a multi-destination tour operator is very different from that of a single-market accommodation provider. Static defaults fail both.
This is the thinking behind Fraud Shield, felloh’s advanced fraud protection layer.
Rather than imposing one-size-fits-all logic, Fraud Shield is designed to give travel merchants granular control over how fraud is assessed and handled, embedded directly within the payments flow rather than operating as a disconnected bolt-on.
Find out more about Fraud Shield
One of the most damaging aspects of traditional fraud tooling is not just false positives, but lack of control.
When rules are fixed and decisions are opaque, merchants are forced into a passive position. Transactions fail, customers abandon bookings, and teams are left guessing what changed and why.
In contrast, a configurable approach allows businesses to actively define their own risk posture. Controls can be adjusted by market, booking type, seasonality, or growth stage, reflecting how the business actually operates rather than how a generic model assumes it should.
This is especially critical in travel, where legitimate behaviour often looks unusual and where risk profiles shift constantly based on destination mix, customer geography, and demand cycles.
Treating fraud controls as something that can be tuned and evolved, rather than simply switched on or off, is a clear indicator of whether a payments stack is future-proof.
The most important shift is conceptual.
Fraud prevention is no longer just about blocking bad transactions. It is about maintaining operational resilience, protecting conversion, and demonstrating control to acquirers, partners, and regulators.
In other words, it is risk governance, not just fraud blocking.
Static defences are increasingly outpaced by adaptive threats. Travel businesses that continue to treat fraud as a background technical setting will find themselves paying for it in lost revenue, customer frustration, and operational drag.
Those that recognise fraud as a dynamic system, and design their payments infrastructure accordingly, are far better positioned to scale with confidence.