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.

Involve.ai, a startup using AI to bolster customer success, today announced it has raised $16 million in a series A round led by Sapphire Ventures and other investors. The company says the capital will be put toward product development and hiring on the engineering, data science, and go-to-market sides.

Customer success emerged as a top priority for companies as the pandemic disrupted processes, causing businesses to rethink how they operate. But while having a good pulse on customer behaviors, preferences, and goals is essential — 35% of respondents in a Deloitte report ranked customer success objectives like reducing churn as leading objectives — customer success teams often lack the right tools to support their workflows. For example, in a recent SmartKarrot survey, 84% of customer success leaders said automation is important, yet 70% have no or low levels of automation.

Involve aims to help customers find signals in siloed systems and parse through millions of data points to prevent customer churn, increase revenue, and personalize customer experiences. The company was cofounded by Gaurav Bhattacharya and Saumya Bhatnagar, who started coding when they were just 10 years old and met in a high school coding class in India. Before Involve, Bhattacharya and Bhatnagar launched patient experience software out of high school. This software was eventually distributed by the Indian government to ultrasound specialists.

“Involve [began] as an employee engagement and volunteering platform. Being customer-centric, we built rudimentary AI scripts to find churn risk and expansion potential in our user base. That proved very valuable,” CEO Bhattacharya told VentureBeat via email. “When the pandemic hit and customer retention became an important topic, we provided our platform to companies to use, and they loved it. That was our ‘aha’ moment and when we decided to pivot the company to be an actionable customer intelligence platform, helping the world become more customer-centric.”

AI for customer success

Bhattacharya said that after the pivot Involve had to build its own datasets of the qualitative information a customer success representative reviews in their daily job. The company used these datasets to train its predictive model, which takes into account nine factors per business vertical to establish a customer’s success with an organization.

“We realized there was a massive problem for customer success organizations that we could help solve, but in order to do so we had to take a more qualitative versus quantitative approach,” Bhattacharya explained. “We [also] had to identify different variables that impacted a customer’s success across diverse verticals.”

Above: Involve.ai’s customer success analytics dashboard.

Image Credit: Involve.ai

The platform has managed to attract 22,000 paying customers in three years — revenue grew 480% in 2021 from 2020 — but Bhattacharya hopes to reach 200,000 customers by 2023. In the coming months, Involve plans to deploy new AI-driven workflows and enhance its renewal sentiment classifier, which parses natural language to find insights potentially valuable to customer success.

“Involve solves the massive loss companies face resulting from bad customer experiences. Companies are experiencing high pressure to retain customers and reduce churn, made especially challenging amidst the pandemic and even more important with the rise of the subscription economy,” Bhattacharya said. “Every customer matters post-COVID, so companies are finding ways to prevent churn, increase expansion, and give an excellent customer experience to every customer, which increases the value of our platform.”

San Francisco-based Involve, which currently has 34 employees, aims to have 58 by the end of the year and 120 by the middle of next year. The latest funding round brings the company’s total raised to $35 million.

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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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