The problem of false declines is massively growing, as it keeps up with the ecommerce growth and the emergence of different types of payments in the market. The seriousness of this issue is evident in research from Edgar, Dunn & Company, which found that more than USD 700 billion would be lost due to payment declines by 2022, and a majority of that would be attributed to the failed transactions of good customers. Beyond this data, the consequences of false declines are even more concerning, because rejecting a legitimate shopper means losing both the sale at hand, and the future lifetime value from that customer.
What are the main challenges merchants face in the process of accepting or declining orders?
Not having enough information about a transaction and not being able to send it to the issuer is obviously a problem. Another big challenge is that merchants don’t always know which issuer accepts what type of additional data, or what type of data each issuer wants to see. Moreover, there may be different means to send the data to the issuers downstream – it can be via direct API endpoints, or via 3DS rails, for example – and most of the time, the merchants don’t fully understand these methods.
How can data analytics be leveraged in the pre-authorisation phase of a transaction to prevent fraud and improve customer experience?
On the merchant’s side, a lot more information is available about the transaction itself than what’s available on the authorisation stage of the transaction. During the purchase process, merchants have access to data such as behavioural analytics, device ID, user’s time spent on the website, and so forth, but this information is not available to the issuer. If the information from the merchant side could be communicated to the issuer in the pre-authorisation phase, this would improve optimisation rates and prevent false declines.
How can merchants work directly with issuers to optimise their authorisation rates, and master the risk vs fraud strategy?
As mentioned before, some issuers are exploring direct API endpoints outside of the network rails, and others prefer to receive decision enhancement data on the traditional rails. Keeping up with all the issuers’ rules can be an onerous task for merchants, especially when there are multiple integrations and testing processes agreements in place. Essentially, merchants have two options here. They can directly use any publicly available integrations the issuers have to send the additional information to them in order to get more accurate authorisation decisions.
Or they can use partners like Signifyd that are connected to the issuers, and know the best way to send data to an issuer – the data elements to send that will result in the best outcome.
Sometimes declines occur due to the incorrect interpretation of an SCA exemption from the issuer side. How can this problem be solved?
It is actually not a matter of incorrect interpretation, rather it’s a function of the issuer’s appetite to accept or decline the exemption. If the exemption is properly flagged with the correct code, there should be no issue whatsoever. On the other hand, when the original decision is being submitted on behalf of the merchant, all the relevant variables must be taken into account, including the previous experience with the issuer regarding that particular exemption type. To better address any challenge related to this, Signifyd has developed an exemption management solution that determines which exemptions to use based on transaction risk analysis.
Friendly fraud and refund abuse are also increasingly affecting the payments ecosystem, and both merchants and issuers have their own role to play here. How can the relationship between these two parties be improved to bring down the rate of these types of fraud?
Friendly fraud is disproportionally rising compared to the normal growth of ecommerce, so it continues to be a real concern in the ecosystem. The sad truth is that friendly fraud can’t be prevented by 3DS because this issue by definition involves the real identity of a consumer, so any security check is basically passed by the cardholder. Hence, data sharing is the answer here. An efficient collaboration within the industry means that the involved players share previous experiences and events. Moreover, our company is able to centralise the information from thousands of merchants and connect the dots where needed to identify certain fraud patterns.
For example, we have intelligence based on several transaction attributes that a consumer committed friendly fraud with a certain card in the past, and when that consumer tries to do the same with another card, we can flag this situation and prevent the subsequent fraud attempt.
How do Signifyd services tie in with all these topics discussed above? How can you bridge the gap between merchants and issuers?
The way issuers receive additional decision-enhancing information from a merchant follows different paths. Signifyd is pursuing a comprehensive approach to this. Depending on the circumstances and needs, we are using either our direct API connection method, or the 3DS rails, and we believe that this is the most future-proof solution for merchants to address authorisation enhancement.
This editorial is part of The Fraud Prevention in Ecommerce Report 2021/2022, the ultimate source of knowledge that delves into the evolutionary trail of the payments fraud ecosystem, revealing the most effective security methods for businesses to win the battle against bad actors.
About Okan Ozaltin
About Signifyd
Every day we send out a free e-mail with the most important headlines of the last 24 hours.
Subscribe now