Ai Editorial: Chargebacks a cost of doing business, not an apt assessment

First published on 7th April, 2017

Ai Editorial: A meticulous approach needs to be attempted to target every source of chargeback. The role of data along with human expertise needs to be optimized, writes Ai’s Ritesh Gupta


Fraud threats are constantly changing and expanding. As fraud detection technology evolves, criminals alter their tactics—what worked for them in the past might not work today.

When it comes to fraud and chargeback management, agility is one potent weapon.

Be it for counting on new technology or human expertise or ensuring earning potential isn’t being curbed, airlines, like any merchant, need to be spot on with their moves.  

The consolidated figure for airline chargebacks is estimated to be $1.5 billion on annual basis. The financial consequences include dealing with fraudulent orders, expenditure incurred on fighting fraud and turning down valid orders. What’s typically the chargeback rate for an airline or a travel e-commerce entity that processes millions of card-not-present transactions on annual basis? Is it 0.8%, how can it be brought down to 0.7%? What’s the timeline and how can it improve the financial situation? This way travel e-commerce organizations not only keep the rate in control, but they are also striving to improve with pragmatic goals.

Here we assess some of the initiatives that can help in prevention of chargebacks.

Addressing the real issues: Airlines need to rely on technology, machine learning, and human forensics, or the blend of all to ensure one knows the real source of each chargeback. Otherwise one can never get to the core of the problem. The reason being a customized action, as part of a robust prevention strategy, is required to combat each chargeback source. Otherwise airlines won’t be able to target the right problem at an opportune time.

In this context, getting into details related to criminal fraud (how to cut down on unauthorized transactions that get processed?), friendly fraud (difficult to detect at time of purchase and issuers usually accept a customer’s assertion) and merchant error (it could be that even up to 40% of chargebacks could be cause by the merchant’s own mistakes, oversights, or shortcomings) is must. Also, airlines can’t only consider basic tools. At the same time, one can’t also feature every offering available for managing risk exposure. For instance, any merchant who uses Address Verification Service along with card security codes or 3D Secure is technically using multiple solutions to prevent fraud. Other options include card security codes, geo-location, device authentication, proxy piercing, biometrics etc. So airlines need to work out a meticulously constructed fraud mitigation plan.



Experts recommend that a move such as enforcing blacklists (featuring fraudsters) post an attack (rather than preventing the unauthorized transactions) isn’t an ideal move. Rather look at non-technical and API integration options, and act “faster”. Look out for the real source of each chargeback. Sort out areas like uncertain merchant error.

Coming to grips with the problem in time: The industry today is improving the acceptance rate with an integrated system for pre-authorization fraud scoring/ screening and post-authorization chargeback mitigation/ fraud recovery.

The travel industry is also relying on the efficacy of a machine learning engine that evaluates fraudulent users in real-time. Data is analyzed instantly, linking seemingly unconnected signs left behind by fraudsters. Other than detecting fraud, data is also playing its part in ensuring “genuine” orders do not get declined owing to any uncertainty around the transaction.

Alerts have emerged as a viable, faster alternative to the chargeback process. It is about how to do away with the need for a chargeback. And the key here is to stop processing of a chargeback in time.  As shared by ethoca during one of our conferences, upon notification from issuers, the company transmits an alert to the merchant. For their part, airlines can refund the passenger to avoid chargeback. Alert outcome is passed on to the issuer. Result: merchant and issuer liable losses recovered by card issuer on first contact. What this also means is companies can be in better control of things to come, preventing instances of fraud in the future. And companies can also use link analysis to eradicate related fraudulent orders.

Making the most of human expertise: Artificial intelligence or AI can extract anomalies and identify patterns from real-time data but human intelligence is still needed. According to Kount, it’s not just quality of data, its accuracy or the number of datasets that only matters, but human capabilities, too, are needed to communicate, strategize, and guide machines to the optimum business result.

Working in unison: There are multiple stakeholders at risk when it comes to chargebacks. 

Fraudulently filed chargebacks affect each stakeholder in the payment chain.

·          For merchants, a multi-layered approach is best. Today’s solution must be agile and diverse, coupling an evolving defence with effective representment strategies. 

·          Acquiring banks can help reduce the effects of fraud by establishing internal blacklists and developing chargeback triggers for advanced alert notifications.

·          Processors who undergo the most stringent underwriting procedures to maximize their KYC (Know Your Customer) compliance will ultimately reap the benefits through helping to ensure their merchants are following best practice methods that work alongside operational efforts to prevent friendly fraud.

·          For issuers, additional due diligence is key.  Despite the temptation to rapidly resolve a cardholder dispute, additional effort will pay off in the long run for those who consciously work to prevent bad habits from forming in the first place.


Are you bold enough to survive in the brave new world?  Assess your preparedness at 11th Airline & Travel Payments Summit (ATPS).

Date: 03 May 2017 - 05 May 2017   

Location: Berlin, Germany 

For information, click here

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