Ai Editorial: Shielding traveller’s data and combating fraud as an OTA
First published on 20th June, 2016
Ai Editorial: Be it for shielding customers’ information or nullifying fraudsters’ move to grab funds, OTAs have to be alert all the time, writes Ai’s Ritesh Gupta
Online travel agencies (OTAs), even the established global intermediaries, tend to be vulnerable when it comes to online fraud.
There are a couple of issues. One of them is fraudsters gaining access to contact details of customers. OTAs frequently receive complaints from customers about unauthorized credit card transactions. Plus there are areas where OTAs can be at the receiving end. Of course, nobody would like to face implications in case they end up with excessive fraud and chargeback rates.
Merchants are expected to adapt their risk settings and business practices accordingly to ensure fraud and chargeback levels are at an acceptable level.
The likes of Booking.com have had problems in the past as far as customer data is concerned. Also, fraud today is as an organized crime. I spoke to a couple of OTAs in the Asia Pacific to gain insight into 5 key areas/ trends:
- Protecting customer’s data
It is imperative to shield customers’ personal and financial information. Otherwise it can severely impact a brand’s image. Travel companies need to understand how hackers are gaining access to system data or server functionality. The breach of data is happening and it could be owing to a web application getting manipulated and a fraudster tricks that application into performing commands and accessing data. Another way is to get hold of an authorized account via focus on session IDs, and eventually stealing them.
Experts recommend that additional steps can be implemented to curtail risk of credit card and personal data exposure, such as compartmentalization and tokenization on the inside of the company’s DMZ (Demilitarized zone. Network added between a private and a public network to provide additional layer of security). This is being considered to be a vital add-on to firewalls and external fraud measures. Such mechanism keeps a tab, acts and reports on dubious activity and can feature configurable fraud-alert rule sets, data- profiling modules, and other validation methods. Also, at another level, it is important to know how to strike a balance while focusing on stringent fraud rules. Otherwise this can result in reduced acceptance and revenue.
- Going beyond passwords
It is being highlighted that password is no longer the best way to authenticate users. In fact, there is a need to go beyond conventional passwords and PIN based approach.
As highlighted by Visa, biometrics offer “the only way to link” a person’s physical identity to his or her digital identity. Biometric authentication features fingerprints, facial recognition to authenticate one’s identity. This is something that cannot be replicated with ease. Also, from a user experience perspective, there is no need to remember a password. However, an OTA executive mentioned that biometric authentication is still in its nascent stages as far as intermediaries in the region are concerned.
Also, Visa is working with EMVCo to develop an updated and enhanced version of 3D Secure, paving way for more consistent UX across various payment channels, including mobile web, in-app etc. The company has asserted that 3DS version 2.0 will offer a more seamless checkout experience via intelligent risk-based decisioning.
This sort of authentication features data to assess genuine user behaviour, device, location and other well-known characteristics, so there’s less need to ask for a password.
- Sudden spurt in dubious activity from one region
A senior executive from Mumbai-based OTA Cleartrip.com shared that there tends to be sudden spurts in fraudulent activity from one market/ country. For instance, last year it related to “seemingly Russian citizens” booking itineraries featuring a particular LCC in the Middle East. “The bookings featured destinations like Moscow, Kiev, Bishkek etc. Most of the passengers booked through these transactions sounded like Russian citizens (female names ending with “ova” or male ones ending with “ev”.” The carrier had strict policies, and before the OTA could verify and reach out to the airline, fraudsters were cancelling those flights, and gaining credit vouchers for future bookings. “We eventually decided to cancel the sector.” And this year, the same executive referred to “Indonesia fraud”, where fraudsters are using cards issued in the U. K., US and Australia, and booking same day check-in hotels and non-refundable/ non-cancellable airlines. Lot of activity is related to travel and booking of hotels in Indonesia.
There are tools in place that can differentiate between threats and genuine transactions by pinpointing the buyer’s location.
- Reviewing cancellations
Cleartrip.com also shared that it has been working on plans to curb virtual wallet fraud. “In this case, a fraudster does the fraud transaction using international card and cancels the trip to obtain the refund in a virtual wallet. The same can then be used for future booking. It also surpasses all the fraud conditions due to payment mode.” So rather than funds going back to the original instrument after cancellation, when fraudsters decide to cancel a booking they put into a private closed wallet. So Cleartrip.com reviews such cancellations, and nullifies the action taken by a fraudster. Rather the money is sent back to the credit card or the original instrument. “We revert in quick time,” shared the executive, who also referred to discount coupon fraud (the fraudster finds out a loophole in the system and uses the code to obtain false cashback).
- Relying on machine learning
While the moments between when a shopper clicks “buy” and when a merchant must deliver a reservation seems fast to us, it’s plenty of time for a computer to recognize a bad user or reward a good one with a smooth, easy buying experience. A flexible and online (instead of offline) machine learning system can start learning the second a user lands on your site, gathering behavioral data so you can spot a suspicious user long before he enters a stolen credit card number and you get hit with the inevitable chargeback. Armed with actionable machine learning findings, a business can create an adaptive checkout flow, that is tailored based on how risky each user is.
One of the best things about using machine learning is that it automatically learns about new fraud patterns in real time so you don’t have to keep close tabs on new tactics.
Moving on
Fraudsters always move on. Managing online fraud is an ongoing initiative, one that needs constant improvisation for better results. If this is not the case, then a travel organization would end up being a soft target.
Here it needs to be mentioned that the booking experience of a customer shouldn’t be jeopardized.
I know of an instance where an airline called up my colleague in the U. S. past mid-night, who had booked me for a trip in Asia. The airline had concerns about the itinerary, considering that the booker was in the U. S. But my colleague felt the check needed to be more vigilant, considering that the airline had information about him, and disturbed his sleep by calling at 3am!
Hear from experts at the upcoming 5th Airline & Travel Payments Summit Asia-Pacific to be held in Kuala Lumpur (17-18 August, 2016).
For more, click here
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