Urgency has a way of making things fall into place when financial institution executives might otherwise dither or go down a bypath.
While COVID-19’s challenges were often met through stepped-up use of technology, the coronavirus has also had the effect of sharpening the focus of tech investment priorities among banking institutions. The unprecedented health and financial crisis sifted out those technologies that, even when they appeal strongly to the imagination, are still mostly hype as far as financial services providers are concerned.
An example of the latter is the Internet of Things, says Jost Hoppermann, Vice President and Principal Analyst at Forrester. Many people like the idea of smart things, from household appliances to heavy equipment. However, “when we look at consumer banking,” says Hoppermann, “there are very few reasonable use cases.”
Hoppermann and a team of Forrester analysts interviewed more than two dozen banking and technology decisionmakers. In an interview with The Financial Brand he discussed the findings, with some surprising indications of where these technologies will go in the future.
While much has been made of COVID’s acceleration of digital transformation in banking, Forrester says the smoothness of that transition has been overplayed.
“Some institutions certainly discovered the hard way that their systems were not 100% up to the requirements of the pandemic,” says Hoppermann. “So many had to urgently make their systems more scalable for digital interactions with customers and for employee homeworkers.”
For much of the pandemic, these efforts diverted some funding from developmental efforts not of immediate need. However, Hoppermann says the upshot is that many financial institutions caught up on five years of transformation tasks in a handful of frantic months.
And now they are preparing plans to further accelerate transformation as the pandemic becomes more manageable, says Hoppermann. “Hopefully we will see a more digital industry in a shorter timeframe than expected prior to the pandemic”
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Hot: Artificial Intelligence, that May Soon Be Part of Most Banking Software
In Forrester’s report, “The Top Emerging Technologies in Banking in 2021,” multiple forms of AI were on the hot list, including machine learning; deep learning; natural language understanding, generation and processing; and even “computer vision.” The report indicated that financial institutions “are doubling down on the role that AI will play in digital transformation.”
“At some point AI will just become a normal ingredient of banking software.”
— Jost Hoppermann, Forrester
There is widespread recognition that AI will make a difference in the customer experience. Hoppermann says the role will depend in part on the sophistication and budget of each institution. However, he adds, as more banking software vendors and fintech partners build AI into their products, the accessibility of AI is growing.
Already some AI-powered capabilities are being incorporated in banking software. Some of this consists of simpler forms of AI, but some is also more advanced. More significantly, Hoppermann says that the line between software and AI is melting. For example, digital engagement software that suggests which products to offer next increasingly is AI.
“AI is making solutions more powerful, more seamless, easier to use and more efficient for banking employees,” says Hoppermann. “At some point AI will just become a normal ingredient of banking software.”
Hot: Simple Chatbots (But More Advanced Ones. … Not)
The report made clear that not all chatbots are alike. While “simple chatbots” are relatively hot, Forrester says the next generation, “sophisticated chatbots,” are seen as hype right now by vendors and practitioners.
“Chatbots have to be able to do more than tell you to contact the call center when it comes to complex scenarios.”
“I had to use a chatbot recently,” says Hoppermann, “and after a series of questions, it asked if I wanted to look into this specific topic. I said yes, thinking I would finally get some help. Instead, the chatbot responded, ‘Please contact our call center’.”
That’s the boundary line between simple and sophisticated right now, he continues. “They have to be able to do more than tell you to contact the call center when it comes to complex scenarios.” The report indicates that such solutions are far from being ready for extensive deployment and many institutions aren’t ready to use more sophisticated bots.
Hoppermann knows of one financial institution that tried to implement a more-advanced chatbot to address consumer problems at ATMs, such as being shorted on cash. Unfortunately, conversations could take so long that growing queues at the machines began to cause social separation problems. In the end, the bank had to tweak the bot so that it mainly gave assurances that the consumer would be made whole, to keep lines moving.
“So they made the chatbot work in a potentially emotional situation, but it was also the decision of the bank to trust people not to leverage the mechanisms to get more cash out of the ATMs than they were supposed to,” says Hoppermann.
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Hot: APIs. But More Common Functionality Must Be Found
Application programming interfaces help make many of the services work that depend on rapid interaction between a bank or credit union and third parties and vendors whose services make sophisticated online and mobile products work.
APIs are spoken of as so fundamental to the future of financial services that a banking layman might think they all function seamlessly. Not quite the case.
“We need more standardization when it comes to APIs,” says Hoppermann. “We have plenty of technical specifications. Some are good. But some are not so good. Some are comparatively broad. None is complete and we do not have standards.”
Hoppermann says this is holding back some financial institutions.
“There’s still some homework they need to do before they can use APIs in a more comprehensive, strategic fashion, as opposed to tactical deployments,” says the analyst. Multiple groups have been working to set standards, but in the meantime, in simple terms, it’s somewhat like having house with multiple kinds of electrical outlets.
“This is why some banks are struggling to start a broader API journey,” says Hoppermann.
Not Hot (But Heating Up): Low-Code Programming and Distributed Ledger Technology
The report identifies several areas as being “on the radar,” though not hot yet. Among them:
Low-Code Programming. This is programming that, simply put, relies on software building blocks rather than hand coding every step in developing new applications. This method offers agility. It can speed up production of off-the-shelf applications and faster development of custom work. Hoppermann knows of fintechs that build products for banks completely using low-code tools.
But using this technology involves a tradeoff, according to the analyst. “You can get speed, but you will not get the same level of sophistication you can with normal programming,” he says. As a result developers tend to resist using low-code.
Distributed Ledger Technology/Blockchain. This is the technology that Bitcoin is built on. Forrester has been conservative about DLT, says Hoppermann, but he adds that the firm is more optimistic now about its potential for banking. However, potential uses remain limited for now, so widespread use will take years, Forrester predicts.
Still More Hype Than Hot
Besides two technologies already mentioned — Internet of Things and sophisticated chatbots — Forrester’s report also classifies other tech as “hype.”
Forrester calls such tech “pure market noise.”
Virtual reality. For some, this tech is so cool it ought to be hot, but it’s not. Hoppermann says it is not so much a disappointment, but in its early stages.
For retail banking, there have been efforts to build virtual branches consumers can “visit.”
“They were very interesting in a lab environment, but consumers haven’t fully accepted them. One reason is that the goggles are still too expensive unless you accept degraded quality,” says Hoppermann.
Edge computing. The concept is to speed up processing by moving it closer to the source of data. Forrester found that multiple challenges remain, including a basic: “shared understanding about what or where the edge is.”