False declines cost merchants plenty: billions in lost sales and even more in broken consumer relationships. That commerce-killer is what inspired Mastercard to create its new Decision Intelligence platform, which launches today with a promise to turn false declines into a thing of the past for the payments ecosystem. Ajay Bhalla, Mastercard’s president of enterprise risk, shares all the details.
$118 billion is a lot of money.
It would take someone 11,800 years to save that much, assuming they could save the princely sum of $10,000,000 each of those years.
Yet, it only takes one year for merchants, collectively, to lose that much in sales due to false positives — declines for legitimate customers with enough available credit to make those purchases but who are turned away at the merchant’s physical or virtual front door.
Today, it’s the problem that Mastercard, with the announcement of its Decision Intelligence platform, hopes to solve for merchants, issuers and consumers.
Globally.
Mastercard’s president of enterprise risk and security, Ajay Bhalla, told Karen Webster in a recent conversation that one in every six consumers experiences false declines. And when that happens, no one wins.
According to Mastercard’s data, about a third of the time, that customer never returns to that merchant. And, 20 percent of the time, consumers change banks.
But despite the fact that the problem is clearly pressing and taking a demonstrable toll on the all the players in the payments ecosystem, Bhalla said that the problem has not been solved so much as simply dealt with. Bhalla told Webster that, up until now, the collective industry just hasn’t done enough to solve the commerce-killing problem that is false declines.
But the times, he noted, are a-changin’.
“AI is the game-changer, and we are now at the moment of truth when things can really change for the future,” Bhalla remarked.
Said simply, Decision Intelligence leverages AI technologies to boost the accuracy of real-time approvals of genuine transactions and reduce false declines — getting smarter with each and every transaction that an individual makes.
The more complicated but more interesting part of the platform, Bhalla told Webster, is the difference in approach that AI takes to making its “choices.” Instead of limiting the decisioning engine to a narrow view of the transaction in front of it, the platform instead looks holistically at it as another data point in a consumer’s overall shopping portrait. Decision Intelligence, Bhalla said, can see data from the merchant side, the device side and the cardholder side and brings all of that data together for the benefit of a real-time authorization — and a sale to the merchant.
Data that reflects behaviors at the individual consumer — and not simply the account — level. That depth of insight is one of the ways that Decision Intelligence can make such a big dent in the rate of false declines.
“Normally, in the past, what has been looked at was transactions, and that can be very misleading,” Bhalla explained. “We, of course, still look at the transaction itself, but that’s just the tip of the spear. We take into account devices, behavior, IP address and location and combine all of that to produce a more reliable insight for issuers to make their decisions — in real time.”
Bhalla said that, at its core, Decision Intelligence can answer two very pertinent questions about the consumer who’s presenting a card for payment: (a) Is this how the consumer normally shops? and (b) Is this the sort of thing that this customer normally buys?
The false decline problem in the U.S. is bad enough — $118 billion a year, or roughly 15 percent of all transactions. But in some parts of the world, Bhalla noted, the decline rate on digital purchases bounces up to 50 percent.
“Part of what excites me so much about this project is that innovation is normally possible where you can touch one part of an organization, nation or product,” Bhalla said. “But rarely do you get to make a change that can really positively affect the whole world.”
Introducing a world of complexity in the process. But, Bhalla noted, it wasn’t complexity that Mastercard was entirely unfamiliar with. The infrastructure needed to create Decision Intelligence exists and has been rolled out through various releases and projects all over the world. That global platform gave Mastercard a running head start in building — and now deploying — Decision Intelligence everywhere in the world.
Bhalla told Webster that Decision Intelligence is a complement to — and not a replacement for — other identity and security solutions, like Identity Check and 3D Secure 2.0. In fact, both will feed data back to the Decision Intelligence platform so as to inform its total “knowledge base” to help merchants, issuers and consumers fight fraud, while giving the consumer a better checkout experience.
That bigger, more robust knowledge base, Bhalla said, then gives banks the tools to make better authorization decisions — better than they could do on their own and only as a single financial institution.
With Decision Intelligence, Bhalla said that they “can simply see things that issuers that are in one country or one locality just can’t because they don’t have the range. And institutions don’t have the luxury to wait or hear about it in news or wait to be told about it.”
The cost of being defrauded is high, Bhalla noted, but the commerce lost to falsely declined cards is orders of magnitude higher. The solutions, going forward, aren’t just about trying to pick bad transactions out like needles in an ever-growing digital haystack but instead to find a way to make the needles stand out more immediately.
And then, making those solutions work as well in Nigeria as they do in New York.
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