How open API standards will transform financial services

Open standards will have a huge impact on driving innovation in banking. Learn the status in the U.S. – and the bold new opportunities open standards are set to usher in.

The impact artificial intelligence will have on the digital universe should not be understated. Not since the development of the electrical grid have humans faced such a radical shift in their relationship to the natural world.

And while many leading experts tout the ways AI will alter key functions that we all take for granted — everything from transportation to buying new shoes — it appears the first realm to face a new AI-driven operating paradigm is the one that created AI in the first place: software development.

Expanding intelligence

According to IDC, the worldwide AI market is expected to top $341.8 billion in 2021 and then blow past $500 billion by 2024 for an annual growth rate of 18.8%. It should be noted, however, that fully 88% of this market will be in the form of software, about half from applications.

How will this change the software market? For one thing, it will alter the way code is written, updated, and released. With AI empowered to make changes to itself, the focus of highly trained, highly paid software engineers will shift from the dull drudgery of writing and rewriting minute functions to more creative, strategic-level operations that produce greater value and drive core business operations. At the same time, DevOps will become increasingly automated and responsive to users with the power to define their objectives and have AI convert them into code.

This could alter the way software is bought and sold, with individual users getting the updates they need from AI, rather than having to shell out more dollars for a generic new release from the developer.

This does not mean the end of commercial software development, however. As tech writer Smith Johnes notes, AI will help companies become leaner and meaner in a number of ways. Starting with more generic AI benefits, like better market analysis and cost-planning, firms can also look forward to AI-based programming assistants, automated testing and compiling, and streamlined bug fixing — all of which promises to deliver better products at a faster pace and with higher levels of customization than traditional approaches.

A broader view

Like other members of the digital workforce, software developers will have to adjust to this new paradigm. One way is to stop thinking like a developer or even an architect and start focusing on the aspects of software that are not so easily automated. One way to do this, says Biz Tech Age’s Harry Miller, is to shift away from perfecting single programs or platforms and look for ways multiple software systems can work together. With the rise of no-code and low-code programs, much of it likely written by AI, human developers will shift away from the practice and process of development to building highly customized solutions for a wide range of challenges.

As AI continues to evolve and acquires the ability to learn on its own and infer from context, we can expect to see broader democratization of software development to the point that virtually anyone can create new programs — no experience necessary. Prem Natarajan, vice president of Amazon’s Alexa program, highlights the way advanced neural networks and other developments are enabling AI to understand plain speech. So instead of having to master a lifetime’s worth of esoteric commands, all anyone will have to do is simply describe what they want and let AI do the rest. Sound too good to be true? We are already seeing this in a rudimentary fashion in the way people are able to reprogram their smart cars, smart homes, and other devices, and this process has only barely begun.

With AI poised to unleash significant disruption across all other areas of the digital landscape, it’s only fair that developers take their lumps. As is true in other areas across the industry, developers must adapt to the changes they have wrought with confidence that things will come out better in the end.

How open API standards will transform financial services

Open standards will have a huge impact on driving innovation in banking. Learn the status in the U.S. – and the bold new opportunities open standards are set to usher in.

Presented by Abe.ai

For those of us that are regulars at fintech and artificial intelligence (AI) conferences and follow the development and innovation around AI, virtual financial assistants (VFAs) have gotten a lot of attention at these events for a few years now. But lately it seems that VFAs might be becoming old news — conferences have started moving onto other topics after focusing on conversational AI for several years in a row.

So the questions many people have are: “What’s taking so long? Where are these VFAs? Why doesn’t my bank have one yet?”

Virtual financial assistants take time to build

The hype around VFAs and their benefits the last few years may seem new but it is not, it just got louder. We have seen plenty of primitive iterations of chatbots over the last decade promising similar benefits, but in 2018, Bank of America actually delivered.

They came out with what some called the first “full-featured” VFA, “Erica,” delivering personalized, timely advice and assistance. “Erica” has enjoyed tremendous success (55% adoption as of February 2021), but they were very much on the bleeding edge of this technology when it comes to financial institutions (FIs). They invested multiple years, a large team and a chunk of their technology budget — something not many FIs have been willing to do.

A chatbot in 2014 felt stale and rigid using decision trees to guide you, while the advanced natural language processing/understanding technology of today that we and some others like Bank of America use to build a VFA, is significantly more complex. It requires a team of expert data scientists and several years of development.

While FIs execute their VFA project, it will take time, and how much time depends on the path they choose — build versus buy or a combination of both.

Where the financial institution focuses matters

While many conversational banking projects with FIs often started with every VFA functionality on the table (some combination of customer service, transactions, product offerings, financial insights, etc.), things changed over the past 18 months.

As FI’s budgets were strained, conversations with technology decision-makers quickly focused on cost-cutting features. So while full-featured VFAs may be on the roadmaps of most mid- to large-tier FIs, many are deploying an initial phase with service functionality first, and that is a strategy we have seen work well and recommend.

While a VFA focused solely on assisting the service center is not glamorous, it has been vital in reducing service center costs at many FIs at a time when many were seeing peak demand during the pandemic.

You may not see the VFA pop up in your app with helpful advice on what or when to do it just yet, but many FIs do have the VFAs in the help section of the app, on IVR, or even helping the agent you are talking with get the answer you need.

While FIs execute their VFA projects, branching out into the other functions beyond assisting the service center will take time — how much depends on when technology budgets loosen with a broader focus on innovation again.

The VFA is the mouthpiece, but you need the data

While the perceived delay in next generation VFAs can be chalked up to development time of advanced technologies and the high prioritization of cost-cutting service functionality, there is another factor keeping the hype of full-featured VFAs from realizing full potential.

The VFA may be the perfect delivery method for service, advice, and the nudge towards financial wellness, but without accurate data and timely insights to trigger those conversations, the experience is significantly less powerful. Delivering a personalized conversation to a customer with general information, even if it contains their authenticated data, is not enough.

What makes a personalized conversation with a VFA engaging is the feeling that your FI knows you, your habits, and what you need. Then having the tools to not only engage through a personalized conversation, but also take action directly in the VFA session as if you were speaking to a personal banker.

In order to do this, an FI needs to have their data house in order and work with vendors who can help enrich the data and deliver valuable insights. Once this need for the right data/insights becomes clear to FIs looking to deliver a full-featured VFA, this data work sometimes gets prioritized, extensively delaying the VFA implementation. While FIs execute their VFA projects, they will need to do significant work on their data and insights capability in order to deliver a real full-featured VFA, and that will take time.

So when asking what’s taking so long for you to get a full-featured VFA at your FI, it’s likely that your bank did build or has been building for some time now. We often see FIs come to us after spending two or three years building on their own, looking to partner now to supplement that work or even start over. So, while it still might be some time before you see a full-featured VFA, the good news is more FIs are recognizing the importance of partnering with a conversational AI provider and yep, you guessed it, that will take time.

Download The Next Generation of Conversational Banking to learn how financial institutions can leverage conversational artificial intelligence to go beyond simple reactive use cases and instead generate proactive interactions that engage customers on meaningful money matters and support financial wellness.

Juan Romera is Product Evangelist at Abe.ai (an Envestnet | Yodlee solution).

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