First Published on 19th November, 2018
Ai Editorial: Data breaches/ stolen financial information, fraudulent transactions, account takeover (ATO)…merchants have to be at the top of their game to combat commerce-related fraud and at the same time ensure their buyers remain happy with their shopping experience, writes Ai’s Ritesh Gupta
The situation is trickier than ever. Validating a payment could be about running through a gamut of data points and returning with a decision in fraction of a second to optimize a risk strategy.
Payment and fraud executives have to be crafty enough to ensure that genuine customers aren’t denied an opportunity to complete a transaction or even face hiccups with added friction. At the same time, merchants can’t afford to be a victim of fraud owing to weak authentication or fraud prevention mechanism. A specialist like Braintree underlines that simplicity is synonymous with seamlessness. So the checkout process needs to be fluent, but the experience equation isn’t complete without identifying “real” buyers and cutting down on fraudulent transactions.
So what does balance denote? It’s about being proficient in validating a buyer and such verification 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.
In this context, Visa in the recent past initiated new offerings.
For instance, Visa chose to help merchants in following the new European requirements for Strong Customer Authentication (SCA) that come into force in September next year. One way to differentiate between transactions is the risk associated with them. Visa is helping various stakeholders, including merchants, in spotting transactions in real-time that are at low risk and working out a quick checkout for such transactions. Visa asserts that the team ensures a buy is evaluated on a variety of factors such as location, merchant type, previous purchases, transaction size etc. If on one hand, it is closely looking at adding convenient options for any additional step that prolongs the check-out process, on the other, Visa is also capitalizing on the evolution of the consumer technology to simplify authentication. One such move is enabling banks to count on biometric authentication into their respective apps so that users can avail their connected device and use their fingerprint, their voice their face to finish a transaction. The industry is also weighing ongoing improvements, for instance, EMV 3-D Secure Specifications, for a real-time, secure, information-sharing pipeline to authenticate buyers without adding any friction in the buying process.
Other than tools, global merchants like airlines, also need to dig deeper and understand the peculiarities of each market before taking steps to streamline the buying process.
In its 2018 Global Fraud and Identity Report, Experian shared critical findings (based on 11 countries surveyed):
· Consumer tolerance for friction for the sake of security varies with reference to various nations.
· This is a dynamic place and merchants need to be vigilant of the changing scenario. Considering the variance in tolerance for friction, one solution is hard to finalize. Also, since it is “a moving target”, companies need to adjust especially if buyers’ tolerance for friction could lessen over time.
Merchants need to understand the limitations of existing measures, and also leverage the prowess of data-driven, artificial-intelligence powered offerings for combatting fraud. Rules-based systems are in general reactive and probabilistic solutions, which is why they are unable to prevent fraud before it happens. Rather than using a blanket rule that forces every user to login with 2FA, real-time surveillance can be used to assess logins in the background, and only logins with borderline risks expected to go through 2FA.
Merchants should still develop their own fraud tools that are able to tap on their own sources of data for greater efficiency and more accurate detection of fraud. Real-time machine learning can help against blanket blacklists and whitelists by focusing on the customer’s behaviour instead. It works with real-time live data collected on the merchant’s website, where the system trains itself with each incoming transactions to identify fraud patterns instead.
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