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.

Zendesk today announced it has acquired Cleverly.ai, a Lisbon, Portugal-based platform that finds answers to customer’s questions by creating a knowledge layer on top of apps. Zendesk says it will integrate Cleverly’s technology across its existing products, enabling teams to automate more processes while keeping up with customer demand.

With conversation volume increasing by more than 20% year-over-year, customer support teams are struggling to keep up. As a result, businesses are increasingly turning to AI to provide faster and more reliable service. A 2020 IDC survey found that automated customer service agents are a top priority for companies with over 5,000 employees. Indeed, technologies like chatbots are expected to save customers and enterprises over 2.5 billion hours by 2023.

Cleverly, whose customers include Vodafone, Dashlane, and Decathlon, taps machine learning to classify, prioritize, and route customer support tickets based on intents. The platform can classify content in over a dozen languages, integrating with help desk, FAQ, and customer relationship management software to identify knowledge gaps and automate replies for common customer queries — on either the agent or self-service side.

“Cleverly and Zendesk share a vision of democratizing AI, as well as a passion for creating practical applications that make it possible for businesses to get started with AI right out of the box — without a team of data scientists required,” Zendesk EVP Shawna Wolverton wrote in a blog post. “With Cleverly, we will deliver a range of capabilities that automate key insights, further reduce manual tasks and improve workflows, and overall lead to happier, more productive support teams.”

Zendesk’s purchase of Cleverly comes after the company snatched up ecommerce customer service startup Smooch in 2019 for an undisclosed amount. Prior to that, Zendesk bought San Francisco-based Base, which develops software for analyzing large volumes of sales data.

New features

Alongside the acquisition, Zendesk added new features to its software-as-a-service ticketing system, including workflow automation on social media customer service channels. Now Zendesk can report on the performance of a brand’s automation strategy, like the number of conversations engaged with bots and interactions escalated to an agent. It also suggests macros that leverage machine learning to recommend a response based on ticket context, employing prebuilt integrations with Zoom, Microsoft Teams, and Monday.com to keep teams connected.

“While Zendesk has invested in AI to help our customers achieve better, faster, and more reliable customer service, we believe there is still so much untapped potential. Today, our AI-enabled capabilities help businesses automate the conversations they have with customers, boost agent productivity, and increase operational efficiency,” Wolverton added.

Zendesk, which was founded in Copenhagen, Denmark in 2007, went public in 2014 after raising about $86 million in venture capital investments. In recent years, it has leaned heavily into automation, introducing a chatbot that has conversations with customers and attempts to help them find useful information, with algorithms that better predict answers.

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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