AI apps are shaping up to be an essential part of financial institution and fintech offerings. Yet these innovative solutions are only as useful as the data they can access. Join this VB Live event to learn how predictive analytics and AI can deliver valuable insights and power more personalized user experiences.

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“AI and machine learning are absolutely going to alter the landscape for fintech, for big tech, for China tech, as well as for your bank,” says Don Lisle, VP head of FinTech at Capgemini America. “And the question is how you go about that journey.”

AI is the future of every industry, Lisle says, pointing out the billions of dollars that companies like Amazon, Apple, and Facebook are spending on researching, acquiring AI startups, and developing cognitive computing resources — and financial institutions need to keep up.

“I’m amazed how many banks I talk to that understand the importance of AI and machine learning, but don’t have a well thought-out strategy beyond a chatbot, or robotic process automation,” Lisle says. “Banks that invest in AI will grow and prosper; the ones that don’t will become big dumb pipes that just move money around and really have no brand equity or customer preference.”

AI and machine learning have become the building blocks of bank profitability and growth (think customer engagement, loyalty, and the financial wellness tools). With access to some of the most powerful data sets available extracted from customer transactions, banks are uniquely positioned across industries to create next-gen experiences with these AI tools, Lisle says.

Machine learning powers predictive analytics: the ability to find patterns and then apply those patterns to other data. AI, on the other hand, allows you basically to say, “Please alter the pattern until you get the best possible outcome.” And that’s having a significant impact on personalized services and products that help people make the right decisions about their finances including what they do with their savings, what investments to make, and more.

Where, when, and how a customer uses a credit card, for example — what purchases they make, what stores they choose, even which geographies they’re purchasing in — all add up to invaluable data points that allow deeper assumptions and insights into customer behavior.

“I think what’s most exciting is the ability to look at a consumer and really ascertain their intent or the context of their activity,” Lisle says.

Spending patterns (understanding what bills are coming in, when they’re arriving, and other financial data) all become predictable once you start applying machine learning and artificial intelligence. Extracting and delivering valuable insights from that is the goal — but especially in a privacy-sensitive area like personal finance, it’s key to present your personalized offerings in a way that doesn’t just creep your user out.

“Big Brother looking over your shoulder is not the customer experience anyone’s looking for,” says Lisle. “As you connect to CRM systems, or to transaction back-end systems, what are the insights that you’re going to look at, and how are you going to share those with consumers?”

Lisle suggests the integration of natural language processing (NLP) could be one pathway to consumer comfort.

“I think a combination of access to transaction data, as well as a good user experience that feels very natural, friendly, and comfortable will help undo a lot of the artificial feeling of AI,” he says. “Siri was certainly a step in that direction, but has a long way to go as far as how you can ask questions — it has to allow much more natural language. And there’s a lot of work to be done on that.”

AI tools and systems are already driving value for fintech companies, giving them a tremendous edge in the industry. Learn how to drive customer engagement and loyalty with the next wave of personalized financial wellness solutions when you join this interactive VB Live event.

Don’t miss out.

Register here for free.

In this VB Live webinar, you’ll find out how to:

  • Drive customer engagement and loyalty with the next wave of financial wellness solutions
  • Use predictive analytics and AI to deliver more personalized and engaging apps and chatbots
  • Provide users with intelligent financial guidance based on past behavior
  • Extract valuable insight from a wealth of data to measure users’ financial health
  • Partner with vendors to develop the machine-learning based systems that constantly analyze data and derive insights to drive more meaningful conversations with your end users


  • Katy Gibson, VP of Application Products, Envestnet | Yodlee
  • Dion F. Lisle, VP Head of FinTech, Capgemini America Inc.
  • John Vars, Chief Product Officer, Varo Money
  • Keith Armstrong, Co-founder and Chief Operating Officer,
  • Evan Schuman, Moderator, VentureBeat

Sponsored by Envestnet | Yodlee