Are High-Security Checks Worth It?

by Florian Tanant
According to data published on the payment authentication Cardinal’s website, airlines can suffer attack rates in the 1-3% range depending on the region. It’s one of the worse hit verticals, and things get worse when you factor in the problem of false positives.
While we’ve previously written about the challenges of fraud in the travel industry, this post will focus on false positives and how to reduce them.
Low security
High security
Bad customer experience
Good customer experience
Low false positives
High false positives
Low fraud rate
High fraud rate
False positives are a great challenge in any industry. On the one hand, businesses want to ensure they don’t lose revenue to chargebacks or invalid payments. This pushes them to increase their fraud prevention measures.
On the other hand, customers want a fast, frictionless experience. And they sure don’t want their transactions to be flagged as fraudulent when they are legitimate, otherwise known as a false positive:
And that’s before you even take into account the total cost of fraud, which puts pressure on your team and resources.
The problem: the travel industry has all the reasons to be extra vigilant against fraudulent attacks. Airlines, hotel bookings, car rental companies and other travel businesses are the ideal targets for fraudsters:
Finally, another challenge comes in the form of a conflict of interest: the pressure from card payment providers. It is a difficult balancing act as it’s in their interest to increase false positives if it means lower chargeback rates. At the same time, they need your company to process as many payments as possible to make a profit, so false positives can also damage their margins.
The first step in reducing false positives is measuring them. Every fraud manager wants to implement the best automated rules. But when working with dozens or hundreds of data points, it can be hard to keep track of what works and what doesn’t.
This is why the success rates of statistical analysis should be measured through a confusion matrix, or error matrix.
Quite simply, it is a tool that lets you visualize the success of your rules and their predictions. It can help validate new rules through historical data, and also measure the impact of current rules with real, tangible data such as monetary value.
As mentioned above, one challenge is working with limited or siloed customer data. This is especially true when a long chain of middlemen guard the customer data before it reaches your company.
The solution? Data enrichment. Obviously, the more data you can access about a legitimate customer, the less likely you are to flag their purchase as fraudulent. And using a single data point can actually be enough to get a clearer picture, if you can learn more from an email address, IP, device or BIN.
Even before enriching the data, a lot of travel industry companies fail to extract every data point they can access. There are three areas where you should focus your fraud analysis efforts:
Now that you’ve managed to increase the size of your data set for each transaction, it’s time to leverage the power of AI to create efficient rules. Of course, this model will only work under two conditions:
Travel industry companies are under significant pressure to reduce false positives. Customers show no signs of brand loyalty, which means they will happily turn to competitors if your fraud engine prevents their payment.
Simultaneously, payment providers want you do control false positives, but without incurring extra chargeback rates.
This means the travel leaders who implement the best techniques for reducing false positives are not only increasing their profits: they’re creating a significant competitive advantage for themselves. Hopefully, these four tips will be useful to keep your travel business afloat, especially in an increasingly large vertical with shrinking profits.
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Communication Specialist | Florian helps tech startups and global leaders organise their thoughts, find their voices, and connect with customers worldwide.
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