An average of US$11 million is lost to fraud every year in the travel industry. Travel businesses face a payment fraud and chargeback problem that’s structurally different from what many other industries experience. High transaction values, long gaps between payment and service delivery, and complex cancellation policies create conditions where disputes are more frequent, harder to win, and more expensive to absorb.

Below, we’ll go over why travel businesses are especially vulnerable to fraud and chargebacks, how to identify some specific patterns likely to affect your bookings, and what a prevention program looks like across the full booking lifecycle.

Key takeaways

• Travel businesses are more vulnerable to fraud and chargebacks. The gap between payment collection and service delivery gives fraudulent actors more time and opportunity.

• Booking fraud with stolen credentials, friendly fraud from legitimate guests disputing valid charges, and refund abuse are all common in the travel industry.

• Real-time risk scoring, clear cancellation policies, thorough transaction documentation, and structured dispute response workflows can help businesses combat fraud losses and chargeback rates.

Why are travel chargebacks and fraud often higher than in other industries?

Travel businesses carry a structural disadvantage that many retailers don’t: money often changes hands long before any service is delivered. Once a dispute occurs, the reservation window has closed and the business is left dealing with the loss.

The transaction values make it worse. High values attract fraud because the return on a single successful scheme is substantial. Flexible cancellation policies, which can be effective conversion tools, also give bad actors more room to extract refunds. And unlike retail, there’s no shipping address to verify and no package to intercept. Card-not-present (CNP) fraud in travel is harder to catch precisely because the product is intangible and the delivery is deferred.

What are some common types of fraud in travel and hospitality?

Fraud in travel often follows predictable patterns once you know what to look for. The three types below are prevalent.

Booking fraud using stolen payment credentials

Booking fraud is the most direct form of travel fraud. It occurs when a bad actor uses stolen card details to book a hotel room, flight, or holiday rental. The real cardholder disputes the charge when they notice it, and the business faces both the revenue loss and a chargeback fee. The detection window matters here: there are often days or weeks between booking and check-in, which gives businesses a real opportunity to flag suspicious reservations before service is delivered. Bookings with mismatches between billing address and Internet Protocol (IP) geolocation, multiple rooms under a single name, or a newly created account attached to a high-value reservation are all worth scrutiny before the stay begins.

Refund and cancellation abuse

Bad actors with access to legitimate customer accounts might also try to get refunds or compensation for things such as supposedly lost baggage, delays, or damage that they claim happened.

Friendly fraud and poststay dispute claims

Friendly fraud, where a legitimate guest disputes a valid charge, is common in hospitality. A guest stays, checks out, then files a chargeback claiming the charge was unauthorised or the service wasn’t as described. Sometimes it’s opportunistic; sometimes it’s a genuine misunderstanding about what the booking included. High booking values make the math attractive: a US$400 hotel stay is worth disputing in a way a US$40 purchase isn’t. It’s one of the harder fraud types to prevent because the transaction was real and the guest did receive service, which means your representment case depends largely on how well you documented the stay.

How do chargebacks affect travel businesses financially and day-to-day?

Fraud carries costs that go beyond the original transaction amount: an average of US$5.75 for every US$1 of fraud loss.

Here’s what travel businesses are actually absorbing when fraud volume climbs:

• Non-refundable dispute fees: Generally, each chargeback comes with a fee, which ranges depending on the card network and payment provider, whether you win or lose. That fee typically applies to every dispute filed, so even a well-run representment process doesn’t recover it.

• Staff time on dispute response: Winning a chargeback requires gathering evidence, writing representment documentation, and meeting card network deadlines. Businesses that handle disputes ad hoc face a drain on staff time that scales with chargeback volume.

• Card network monitoring programmes: Businesses that breach certain thresholds might enter monitoring programmes with possible fines or required corrective action. The Mastercard Fraud Monitoring Program (MFMP) starts at a 0.9% fraud-to-sales ratio, while its Excessive Fraud Merchant Program (EFM) threshold is 1.5%; the Visa Acquirer Monitoring Program (VAMP) has a 1.5% threshold that’s considered excessive for fraud and chargebacks.

• Increased rolling reserve requirements: Processors can respond to elevated chargeback rates by holding back a percentage of revenue as a buffer against future disputes. That’s a direct cash flow constraint that compounds over time, particularly for smaller travel businesses operating on thin margins.

How do you reduce chargebacks in hotels and travel businesses?

Many chargebacks in travel are preventable, and the interventions are fairly uncomplicated.

These practices help address some common failure points:

• Capturing authorisation at the right time: Authorising a card at booking rather than at check-in confirms the card is valid and reduces no-show losses. Longer stays or high-value bookings might call for splitting authorisations or placing a preauthorisation hold that reflects your cancellation fee exposure.

• Writing cancellation policies in plain language: Ambiguous policy language is a chargeback waiting to happen. Put the cancellation policy on the booking confirmation, the pre-arrival email, and the check-in document, and require explicit acknowledgement during booking.

• Sending pre-arrival and post-stay communication: A confirmation email that restates what the guest booked (i.e., room type, dates, total charge, cancellation terms) gives you a paper trail and reduces misunderstanding-driven disputes. A post-stay message inviting feedback before a dispute is filed can intercept chargebacks from guests who are frustrated but still addressable.

• Keeping transaction records at the property level: Signed registration cards, check-in timestamps, room assignment records, and incident documentation are your representment evidence if a dispute is filed months later. Digital systems that timestamp and store these records are much easier to work with than paper logs.

• Using clear billing descriptors: If your billing descriptor shows a corporate entity name rather than the hotel name the guest recognises, you might generate confusion-driven disputes. Make sure what appears on a cardholder’s statement matches what they booked.

What fraud prevention tools and strategies work for travel businesses?

Travel fraud prevention benefits from both automated detection and human judgment. No single tool covers the full attack surface, but the following tactics used together can make a real difference:

• Real-time risk scoring: When a booking comes in, a risk model can evaluate many signals at once, including device fingerprint, IP reputation, card Bank Identification Number (BIN) data, velocity, email age, and billing-to-IP geolocation match. It can then return a risk score before the transaction is authorised. The challenge is calibrating that threshold: if it’s too low, you block legitimate travellers; if it’s too high, you’re accepting fraud.

• Identity verification at check-in: Requiring a matching photo ID doesn’t necessarily stop a fraudulent booking, but it stops the fraudulent guest from completing the stay. Combined with preauthorisation holds, it can limit revenue loss even when a bad booking slips through screening.

• Rule-based controls: Travel-specific logic catches patterns that generic fraud models might miss. A rule flagging suspicious bookings (e.g., for more than four rooms under a single name) can catch fraud that scores as acceptable in a broader model. This is often because that specific form of fraud didn’t occur frequently enough in the broader model’s training data.

• Behavioural signals during checkout: How quickly a user moved through the booking flow, whether they copied and pasted card numbers rather than typing them, or whether they used autofill can all suggest automation or fraud tooling that warrants consideration in tandem with other factors.

How do you build a fraud and chargeback prevention program for travel?

An ideal prevention program is a set of processes that span the booking lifecycle. You will need to maintain and update the program over time as fraud patterns shift.

It should include the following:

• Prebooking screening: Risk scoring runs at transaction time, rules flag anomalies, and high-risk bookings enter a review queue. That queue needs a defined Service Level Agreement (SLA) to ensure things are processed on time. If you’re reviewing high-value reservations manually, decisions need to happen before the guest’s arrival window opens.

• Postbooking monitoring: Watch for card update requests on existing reservations, modifications that increase booking value or extend stay dates shortly before arrival, and no-shows on high-value bookings that weren’t pre-authorised for the full amount. The period between confirmation and check-in is where a lot of fraud signals surface.

• Dispute response workflows: When a chargeback arrives, you might have fewer than 30 days to submit representment. That requires knowing where your evidence is, who’s responsible for compiling it, and how to format a response that meets card network standards, all while continuing to run the rest of your business. Businesses that handle this ad hoc might lose disputes they should win.

• Rule tuning: Fraud patterns shift seasonally, geographically, and in response to your own controls. Once you block one vector, fraud moves to another. Reviewing your fraud and chargeback data monthly and adjusting rules accordingly is what keeps a program effective rather than letting it degrade over time.

Tools such as Stripe Radar integrate directly into this kind of program for businesses processing payments through Stripe. Radar uses artificial intelligence (AI) trained across Stripe’s global transaction network to score each booking in real time, a meaningful advantage because the model has exposure to fraud patterns across industries and geographies that a single property or chain couldn’t replicate internally.

How Stripe Radar can help

Stripe Radar uses AI models to detect and prevent fraud, trained on data from Stripe's global network. It continuously updates these models based on the latest fraud trends, protecting your business as fraud evolves.

Stripe also offers Radar for Fraud Teams, which allows users to add custom rules addressing fraud scenarios specific to their businesses and access advanced fraud insights.
Radar can help your business:

• Prevent fraud losses: Stripe processes over $1 trillion in payments annually. This scale uniquely enables Radar to accurately detect and prevent fraud, saving you money.

• Increase revenue: Radar's AI models are trained on actual dispute data, customer information, browsing data and more. This enables Radar to identify risky transactions and reduce false positives, boosting your revenue.

• Save time: Radar is built into Stripe and requires zero lines of code to set up. You can also monitor your fraud performance, write rules and more in a single platform, increasing efficiency.

Learn more about Stripe Radar or get started today.