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Feb 7, 2023
When it comes to e-commerce, there’s a simple, indisputable truth about banks and credit card issuers, two of the key players in their traditionally conservative finance sector: The more aggressive their fraud detection strategy and technical toolkit, the more lost revenue they suffer.
And while a certain level of caution is warranted to protect your financial organization, you need to examine the nature of the transactions that are being declined — and those that shouldn’t be.
Here’s a scenario that occurred recently, frustrating one of Kipp’s own executives:
A member of our UK team traveled to our offices in Israel and tried to use his usual global eCommerce app to buy a replacement set of Air Pods that he needed to communicate on his phone. He logged in as usual, and expected the typical quick, easy “just a few clicks” purchase process he’s accustomed to when he orders. Alas, the transaction was rejected, despite his long-term history with the merchant and the additional cards he had associated with the account. He opened his eBay app, found the same product at the same price, and bought it there using a different card. The original card now finds itself at the bottom of his physical wallet and has been removed from his merchant and other accounts.
The effect, in short, was the loss of commission — both immediate and mid-term — for the bank. It was only looking to protect itself when spotting a suspicious — but not conclusive — data point.
The answer is a resounding “no.” The problem here is the lack (or limitations) of useful data driving the fraud prevention algorithms that determine whether to accept or decline the transaction. The science of fraud detection ought to be driven by a broad collection of data input along the decision path — and contradictory data should be seen as a critical counter-balance; when combined, it’s all part of a formula that can lead in both directions. The problem? Often, you don’t have much of the positive, reassuring data – only the risk indicators. Specifically, you know about the activity conducted through your bank or card, but not general shopping patterns or reliable, consistent, successful use of other cards.
In the case above, the eCommerce merchant knew a lot more about our executive, and by extension, the legitimacy of his transaction than the bank did. Because the bank had no access or way to collaborate with the eCommerce merchant, it issued a decline and needlessly lost that one-time — and future — revenue.
All that’s needed here is that open channel: a way for the merchant to reassure the issuer that the risk is indeed lower than it seems. The merchant can supply metrics about longevity, frequency, typical purchase amounts, and other data points. The data exists… it only needs to be shared.
And remember, it’s in the merchant’s best interest to work with you. While the typical credit card issuer earns between 0.2% and ~2% from interchange on a typical transaction, the merchant often sees profit margins of up to 35% and more. And that’s after investing all the customer acquisition costs of marketing, sales, retention, tech support, and more.
Kipp’s platform is designed to create this win-win-win. Summarizing supplemental customer data in a simple score, the system provides a bank with valuable insight as it’s about to reject a transaction. Then the merchant can offer to participate in the correspondingly reduced risk, paying a small premium that’s algorithmically negotiated between the two parties, using ranges acceptable to both. Kipp thus helps both parties preserve their respective revenues, and leaves a customer satisfied and willing to return to work with both.
And all this can even happen in insufficient funds scenario as well, where participating in the risk is a simple calculation without even sharing supporting data; in “gray area” situations where very often the NSF warning does not necessarily mean the customer will default, the merchant can once again choose to share the risk.
What’s the real cost to a credit card issuer of your size and activity? We’ve created an Authorization Calculator for you. Just add a few high-level figures to get an estimate. We’re warning you, the results may make you wince. For instance:
Interested to learn more? schedule a demo with our team to present to you how you can optimize your transactions in real time and increase revenue.