No. 1: The Latest Technology In Payments
In an early morning panel, representatives from the biggest players in credit cards — Visa, MasterCard, American Express, and Discover — discussed the latest technology developments affecting the way these giants do business.
At Visa, the future is contactless, says Darren Parslow, senior vice president of processing and partner solutions. Contactless payments already are business as usual in Europe; for the U.S., they’re up next. Parslow estimates that 70% of U.S. POS terminals are already contactless capable with 50% already enabled — negating concerns about additional hardware costs in the wake of the EMV conversion.
And while contactless offers the same security as EMV, the “tap and go” nature of these transactions increases speed without sacrificing authorization rates, which Parslow says will hit 98% or more. Potential challenges include consistent branding across POS systems and issuing contactless stock as cards turn over.
Meanwhile, as cybersecurity grows in importance and consumers take a more active role in data ownership, the widespread rollout of individual digital identities has the potential to change commerce. Stuart Vaeth, vice president of digital identity, enterprise security solutions at MasterCard, imagines a world where he doesn’t need to enter and re-enter his personal and payment information on every site he visits. For him, a biometrically secure, low-friction, government-assured digital ID improves internet-based commerce by increasing checkout speeds (and thus lowering abandonment) and security. For this idea to take hold, however, significant roadblocks remain: none more so than the need for multi-state government participation — to say nothing of international agreements that would need to be put in place.
American Express is a 150-year-old company with a DNA wired to experiment with new technology, says Kevin Rothman, chief technology counsel. Today, this means testing and researching the viability of the blockchain in the company’s operations. Internally, AmEx has set up blockchain labs to allow its employees to exchange ideas, foster learning, and practice different applications of the technology. In May, the company put its learnings to pilot, launching a blockchain-based loyalty program in partnership with digital retailer Boxed. American Express is leveraging Hyperledger — in which CULedger is a member — to let merchants create custom membership rewards programs for its cardholders. The pilot ended in June.
For Discover, innovation is borne from consumer need. “We’re trying to develop services that meet consumer needs and reduce friction with every interaction,” says Kate Manfred, who recently became senior vice president and manager of student loans for Discover after spending several years as its senior vice president of brand and insights.
Discover, which heavily touts its Social Security number alerts and live, 24-7 customer service, is working to take its customer service to the next level by leveraging machine learning insights to help serve its cardholders better. Not only do machine learning insights help prevent fraud, but Discover is working to predict what customers will need when they call.
No. 2: The Convergence Of Fintech And Financial Services
The digital revolution is here, and for companies like Wells Fargo which have historically developed technology solutions in-house, are faced with a decision: to partner or compete with fintechs?
Wells Fargo is based in San Francisco, in the “cradle of innovation,” said Ben Soccorsy, senior vice president and head of digital payments for Wells Fargo Virtual Channels in a panel discussion on convergence. It’s an area full of energy and coopetition, he says , which drives the nation’s third-largest bank by assets toward an agenda of “simplification, control, and transparency.” In September 2016, Wells Fargo announced it had fired 5,300 workers for opening as many as 3.5 million unauthorized bank and credit card accounts over several years.
But through newer and more advanced application program interfaces (APIs), the bank finds itself looking to more frequently partner with fintechs. Before doing so, Wells Fargo asks itself three questions, according to Soccorsy:
Is this technology better for the customer?
Does it expand our ability to meet their needs?
Can this partner bring something we can’t or don’t want to bring?
As more fintechs enter a financial services sector historically ruled by banks and credit unions, consumers will interact with financial firms in different and new ways, forcing legacy providers to update experiences and innovate to meet new expectations. As a result, too, financial lives might become more fragmented as consumers tie their money to a wider variety of accounts.
That’s part of the reason that Wells Fargo announced plans in July 2017 for its Control Tower service, which will allow customers to manage their fragmented financial lives from a central hub, including enabling the ability to control when and where their Wells Fargo account is shared via an on/off function. The service, available this summer in pilot, is expected to roll out to all Wells Fargo customers in late 2018.
No. 3: Do You Need AI?
Big data creates a big problem: what do we do with ever-escalating amounts of data and a finite number of people? How do we glean the insights we need?
Today, an easy answer might be artificial intelligence which, says Patrick Wood, head of business development at Kensho Technologies, can be used to “find the one needle in a pile of needles.”
While a powerful technology, Wood would counsel companies looking to leverage AI to consider the processes for which it is most valuable, saying, “There are some that lend themselves to AI, others that don’t.”
For Alex Beghdjian, financial services strategy lead at Ayasdi, this means focusing on high-value problems.
“Who cares that you can predict who will leave your site within 10 seconds of arriving? What are you going to do with that?” he asks.
At his firm’s largest client, HSBC, he’s embedded AI into the bank’s anti-money laundering efforts to help them find the true bad actors in a large data set containing potential criminal activity. That’s how he’d advise others to use the technology, too — not in anti-money laundering efforts, per se, but embedded into existing front-end applications to flag targeted behaviors.
“The wrong way to adopt AI is to make everyone a data scientist,” he says.
Another wrong way to tackle AI is by incorrectly defining a problem, says Cleveland Brown, president and CEO of Payscout. For instance, Netflix, in building their recommendation algorithm, imagined one problem: How do we provide an individualized experience to give our customers what they want to watch? With that goal, the algorithm was a success. Consumers were recommended the content they wanted and watched.
The issue? It wasn’t the content that Netflix had paid billions of dollars to license and on which it was now losing money. From a business standpoint, Netflix jumped a step: instead of considering how to easily present individual consumers with the content they want, Netflix could have considered whether all its content was wanted by some individual consumer.
This example also underscores one of the main benefits of AI: the unexpected insights it provides. In tackling large data sets, AI has the ability to make connections humans may not have considered or conceived. And in fact, says Wood, we assume that AI will discover something valuable and unexpected for us. For instance, it took years to recognize there was value in the aggregate behavior of people using the internet. AI has the ability to find that next breakthrough faster than we thought.
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