Presented by DefinedCrowd
Companies like Mastercard are implementing AI strategies that are transforming how customer experience is done. Join this VB Live event for insights on why AI is essential for fintech companies, plus how to implement it, how to make it perfom, and more.
AI has been around for a long time — it’s only in the last three or four years that people have been paying attention to it in the fintech space, says Dr. Steve Flinter, VP of artificial intelligence and machine learning at Mastercard Labs.
“A huge driver of innovation is that small startups, fintechs, and non-technology corporates are able to get access to this technology that five or 10 years ago would have been locked away in university research labs and the big corporate R&D labs,” Flinter says.
The amount of data now available, and the ability to store and process that at scale, combined with open source technology, compute power, and breakthroughs in technologies like computer vision and NLP are all part of this AI democratization.
And AI and machine learning have become essential for fintechs to embrace, Flinter adds. He points to the need for improved security and safety in the financial world. Consumers need to have confidence that their funds are being well-marshalled and well-managed. AI technology is a powerful way to drive the security and safety of the financial system.
Flinter also emphasizes how AI can drive internal efficiency, making organizations run better, run more efficiently, which translates into a better customer experience for the end consumer. And the third is that consumers are demanding the kinds of products and services that AI and ML technologies deliver, from personalized financial planning products to virtual account assistants, and more.
“If you look at the early days of the chatbot space, it was very much around doing very transactional things. What’s the balance on my card? I want to transfer money from account A to account B,” explains Flinter. “As we see AI evolve, it will be into more high value things. We think of all of the things that all of us know are important in our financial lives, like balancing our budgets, managing our household finances, planning for retirement or college. They’re important, but for the average person, they’re not terribly interesting things to do. We’ll see AI being used to deliver more and more of those services with voice and NLP and text interfaces.”
Of course, chatbots and conversational commerce technology, whether it’s delivered through mobile or voice or web, are helping companies deliver ever-improved forms of customer service without having to employ armies of field agents or phone agents, while having a human in the loop for the harder queries.
But while chatbots are becoming more and more a part of expected, natural customer experiences in the fintech space, there are challenges for deploying some of those technologies. One is the need to integrate it into your legacy systems on the backend.
Second, there’s always the localization or personalization challenge, ensuring that you can deliver the service that a consumer wants in the language and the locale that they’re familiar with. If you’re deploying those kinds of solutions in the Middle East for example, or across Europe, of course you’re going to be dealing with different languages, but often different ways of doing banking as well.
There’s also the need to establish trust when implementing an AI tool, especially in the fintech space. It’s crucial that customers have trust in what you’re doing with their data, that your solution is delivering value for them, and they’re happy to allow you to use their data in that way in return for that value.
And finally, for companies that are embarking on the road to using AI, you need to understand the limitations. There have been huge advances in NLP and computer vision in many areas, but these systems aren’t magic, Flinter says. They rely on good data, good execution, and good technique in terms of applying the technologies.
“You need to think long and hard about where and to what extent it’s going to deliver business value, to make the investment decision,” he explains. “You should deploying technology to deliver value for the business and value for the customers, not delivering technology for its own sake, or AI for its own sake.”
To learn more about how your fintech company can leverage AI, NLP, and voice technologies to dramatically improve customer service, boost efficiency, and improve your bottom line.
Don’t miss out.
- Understand the different types of AI initiatives a company can launch to improve CX based on NLP and Voice technologies
- Know how to develop those AI initiatives and the role of data on training AI/ML models
- Get to know a case study from a fintech company (Mastercard)
- Steve Flinter, VP of Artificial Intelligence & Machine Learning, Mastercard Labs
- Daniela Braga, Founder & CEO, DefinedCrowd
- Hari Sivaraman, Head of AI Content Strategy, VentureBeat (moderator)