Ai Editorial: Controlling fraud via a blend of right data + right people

29th October, 2019

St. Petersburg, Tampa Bay

Ai Editorial: Amidst all the talk around use of machine learning and artificial intelligence (AI), and overall transaction analysis, the industry tends to forget that the human element is vital, too, in preventing various types of e-commerce fraud.


A well-balanced approach, one that encompasses an apt blend of a proficient anti-fraud team and data/ tools expertise, is must to protect travel e-commerce businesses against fraudulent transactions, account takeovers (ATOs), data breaches etc.  

Speaking at the 2019 LFPA Fall Conference in St. Petersburg, Tina Burgess, Senior Manager of Risk and ePayments, Points, mentioned that amidst all the talk around use of machine learning and AI, and overall transaction analysis, the industry tends to forget that the human element is vital, too. She underlined the significance of hiring the right people as organizations try to curb various forms of fraud. "Diversity (while recruiting people), specialized knowledge/ skills, and training and support (is key to curbing fraud)," mentioned Tina. Citing an example, she said pattern analysis and the ability to identify certain patterns/ links is a way in which a skilful team contributes is important, and that's where diverse background of the specialists in the team comes into play.

Right type of data

Tina also asserted that acting on the right type of data, related to payment authorization, membership data and transactional history is another aspect that needs to looked into.

In addition to human expertise, organizations are also looking at machine learning technologies to secure accounts and prevent fraudulent transactions. Rely on both supervised and unsupervised machine learning to comprehend both the historical patterns of use, as well as identify anomalies. Specialists like Sift and CyberSource emphasise that airlines should analyze user behavior throughout the entire journey- including account creation and login, any account activity and also at the point of transaction such as redemption of points. Overall, favourable results come from the ability to experiment with various machine learning-based methods, trying variations on them and testing them with a variety of data sets. It is fascinating to assess how machine learning automates the extraction of known and unknown patterns from data.

Not comprising CX

IBM Security's Shaked Vax highlighted the role of real-time fraud detection across digital channels.

Travel merchants are evaluating ways to quickly and transparently establish digital identity trust. This can allow them to create a more seamless customer experience.

Vax said that digital trust top use cases include establish trust during initial on-boarding, frictionless and password-less login, and continuous trust validation.

He stated that it is going to be critically important for businesses to authenticate users in a way that’s less intrusive than multifactor authentication.  

"Silent security means using risk – your users’ background information and contextual data – instead of the password to authenticate, and letting your good users right in without bothering them. Great, successful digital businesses will differentiate based on this kind of smooth experience and they’ll know their users are who they say they are,"  said Vax.  

Balancing act

As highlighted previously by Ai, travel merchants need to be proficient in validating a buyer and such verification, it shouldn’t interrupt the manner in which they interact and transact with a business. Merchants need to look at new regulations, what sort of action is required and its impact on the user experience, and also the flexibility of consumes when it comes to additional measures that are being taken for authentication. Plus, merchants need to leverage the prowess of data-driven, artificial-intelligence powered offerings for combating fraud. And lastly, businesses also need to efficiently manage the operational costs of fraud management activities.


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