BoI pre Money2020 episode with Kevin Levitt Global Director Financial Services Industry at NVIDIA

In this special pre-Money20/20 episode we speak with Kevin Levitt, Global Director Financial Services Industry at NVIDIA about some of the key themes and use cases NVIDIA will be addressing at the Money20/20 conference starting on Sunday October 27th in Las Vegas.

Kevin explores the transformative role of generative AI in banking and FinTech. From personalized customer experiences to fraud detection and AI factories, this episode highlights how financial institutions can leverage AI to drive ROI, improve efficiency, and gain competitive advantages.

Key Words

• Generative AI
• Banking
• FinTech
• Fraud detection
• Customer service
• Personalized experiences
• AI factories
• Data governance
• Financial institutions
• ROI (Return on Investment)
• Money 20/20
• NVIDIA
• AWS partnership

Transcript

Hello, and welcome to a special pre-Money 20/20 episode of Banking on Information. Today, my guest is Kevin Levitt, Global Director, Financial Services Industry at NVIDIA. Kevin, welcome to this special pre-Money 20/20 episode of the podcast. Thanks for having me. We're all getting ready for Money 20/20 in Las Vegas. It's going to be October 27th through the 30th. And this year on Sunday, NVIDIA will kick things off at the AI Summit with the title, 'From Hype to Reality, Gen AI in Banking and FinTech Accelerated.' Now, I don't know if you read this article in the Wall Street Journal. It had the title, Companies Had Fun Experimenting with AI. Now they have to show the returns. It seems to align well with the title From Hype to Reality.

What do you think, Kevin? Yeah, certainly. That's why we chose the theme we did. There's, I would say, a huge myth out in the marketplace right now that we're aiming to bust, which is that companies need to prove that there's an ROI in all of this investment in AI infrastructure, teams, etc. I can tell you with certainty that within financial services, there is plenty of ROI being generated already by our customers that are leveraging not just Nvidia's platform but our partners in the entire ecosystem to build and deliver AI-enabled applications, that's why we're seeing the growth that we are within Nvidia, particularly within our financial services practice. And as you know, banks don't tread lightly into investments in technology; the reason that we're seeing such growth is because the ROI is real, yeah.

So, can you share some generative AI use cases in banking or payments that NVIDIA is involved in that are showing those returns that we're seeing in the Wall Street Journal article? Sure, happy to. And we're supporting customers across trading, banking, payments, and those entire ecosystems. There are any number of generative AI use cases, we'll just talk through a couple. One certainly relates to improving customer service and enabling, first of all, internal call center agents to be more effective in how they deliver customer service. So the generative AI is being utilized today to call through policies, contracts, documents, helping customer service agents find information. That is more accurate than simply summarized and provides a more accurate detailed response to the customer to help with their inquiry, and that's not just a B2C situation; it's also in B2B and companies that service at scale with APIs and other solutions and services that have uptime requirements can fail and need to be rectified quickly so that their B2B customers can can service the industry as efficiently as possible.

And then certainly you've seen the news from Klarna and others that are using chatbots, virtual assistants, digital avatars to service in a B2C scenario and the gains that they're making in terms of better, more accurate customer service, reduction in call center times. Obviously, this is about gaining efficiencies where possible, but also using generative AI to create new revenue streams. And one way in which they can do that is to ultimately deliver on this goal of a one-to-one hyper-personalized experience and using generative AI to produce imagery and content based on the individual that's being addressed, to help improve click-to-conversion rates on banner ads or to promote more relevant content that helps the customer along their financial journey, which ultimately leads to greater customer retention and customer loyalty.

Uh, so that's just a couple of scenarios, uh, the third one that we'll probably talk about in more detail just relates to helping on an identity verification fraud investigation standpoint using generative AI to take all of the information that's gathered by the investigators, for example when they're pulling together suspicious activity reports and to generate the actual report itself so that it follows the regulatory guidelines has all the information that's required and really cuts down that investigation time significantly so that investigators can spend more time on the higher value, more complex needs of the organization. So plenty of use cases to go around. Yeah, so absolutely a win-win, right? Where there is less time needed to solve customers' Problems and they actually say that they're just as happy with it in the Klarna case.

So I think that obviously is something. Where there is an ROI. So that's great to hear. Now, one of the challenges of AI is that it can be pointed at many use cases. And so not just one AI solution is required. Now, we're seeing the leaders in the industry building industrial-scale AI factories. Can you explain what these AI factories are and how they're crucial in deploying and scaling AI? Yeah, of course. And I mean, this is because we're at this dawn of a new industrial revolution. And if you think about the prior one of the late 1800s is about taking water in and generating electricity and ultimately products and goods. This new industrial revolution is about taking data in and generating intelligence that helps, in this case, banks and financial institutions operate more efficiently, drive costs out of the system and identify new revenue opportunities.

And it takes an AI factory to take all of this data and produce the intelligence that's necessary to operate in a more competitive fashion in today's landscape. And an AI factory is a full stack platform. It's everything from the infrastructure to the operating software to the application frameworks that help your data scientists, your machine learning engineers, your product managers build and deliver AI-enabled applications reliably and at scale. And the reason that these are necessary is because, particularly in financial services, there is no silver bullet use case that will predominate within the ecosystem when it comes to AI-enabled applications. There are hundreds of applications for AI and generative AI today. There will be thousands into the future, and if you think about how banks differentiate, it's not because they build a better mousetrap in terms of a more effective cashback rewards card.

It's because they use data to more effectively underwrite that product, to more effectively serve the customer when they have a question about that product, to more effectively help the customer not fall off the proverbial cliff when they're fighting in terms of their financial well-being and helping them come back from that brink of foreclosure or some form of bankruptcy. So the idea of AI in the context of financial services is critical because the way that banks and other financial institutions differentiate again is how they use data to reduce their risk underwrite more effectively serve customers better and ultimately generate outsized returns on their equity so this is a huge opportunity for the ecosystem that's why we're seeing so much investment and great returns from those that are leading Yeah. Yeah.

And financial services providers have access to a lot of customer data, right? So that puts them in a really good position. And AI really lets them help turn data into insights and then insights into action. So that is really good. Now, on Monday through Wednesday at Money 20/20, NVIDIA is welcoming attendees to the AI Pavilion in partnership with AWS. There you are premiering AI-focused speaker sessions, presentations, and demos. Now, some of the sessions will feature leaders in financial services who will share how they are using AI for transaction fraud detection and fighting financial crimes. You mentioned that a little bit. Can you discuss a little bit more about how that works and what type of use cases we're talking about? Sure. We'll start with identity verification.

As you know, there's a lot of focus across the industry and from regulators when it comes to KYC, know your customer, anti-money laundering, compliance and regulatory provisions. And using AI to improve how the banks adhere to those compliance standards has been a great use case that we see again get wide adoption across the ecosystem. We'll have some innovative leaders at the NVIDIA AWS AI Pavilion at MITU 2020, including companies like Reality Defender that will be showcasing their deepfake technology that identifies AI-generated text, images, video to help banks execute those identity verification requirements. And then we'll have other partners that are showcasing their capabilities when it comes to transaction fraud, which is another big opportunity to fight bad guys.

It's a $43 billion problem today globally across payments and transaction fraud, which can be benefited from the use of AI and identifying it more accurately, reducing false positives. We've got partners like Entropy that will be showcasing their platform for using AI to fight transaction fraud. We'll have large partners like ServiceNow demonstrating their dispute resolution technology that leverages generative AI to improve how transaction disputes are handled and serviced across the payments ecosystem. So we're super excited for our presence and partnership with AWS and Money 20/20, and bringing all of these AI-led innovations to the ecosystem. Yeah, that sounds great. I'd like to do this thing called futures thinking. Now, where we think about a possible future, we both don't know what the future holds, right?

We can only think about what a possible future could look like. So if we think 10 years out, that's usually kind of what we do in futures thinking. If we think about 2034, what role will AI be playing 10 years from now? Yeah, I wish my crystal ball was that clear to get us to 10 years from now. I can tell you there will be a lot more just physical AI in terms of robotics and robots. There will be a lot more agentic AI in terms of agents that help us with all facets of our lives as consumers, as employees, and becoming more productive in the workplace. But I can tell you. My line of sight in Crystal Ball is a little bit clearer when it comes to the next 12 to 18 months.

And where I know financial institutions will be focused is on improving the structure of their AI strategy and its robustness. They'll be investing in building the AI factories that we talked about earlier. They'll be investing in acquiring and retaining their talent, improving their data governance. Policies their trustworthy AI practices and they will be continuing to move from experimentation into production with their AI-enabled applications, and the fact is that the leading banks are already there with all these capabilities, and those that don't get there over the course of 2025 are going to be at a competitive disadvantage; they will be losing market share because those companies that don't leverage AI will be delivering inferior customer service. They'll be delivering less personalized content. They will have slower loan application processes.

And the stakes are just too great to not invest in an AI factory, AI capabilities. And you have to invest with a mindset for growth because that's what we're seeing from these leading institutions. Benefit and gain from their investments in AI. And so that's where the next 12 to 18 months are really going to take us. It's going to be about investing for growth, investing for scale, AI factories, and moving more and more of these AI-enabled applications into production. And this is not new. Financial services for decades now has learned how to take new technology innovations and apply them to our industry. From ATMs to internet banking to mobile banking. And now, of course, about AI and generative AI and NVIDIA and AWS. We're here to help and assist customers along their AI journey.

And we're looking forward to meeting everybody at Money 20/20. Yeah. Now, so if you aren't doing this yet, if you're still on the sidelines, get off the sidelines. And actually, when you are experimenting, you should be actually getting ROI from this. So very, very insightful. Thank you for thinking through what the future could look like and how important it is to get going and actually execute today. Thank you for joining me on the podcast today. I think I speak for everyone that we can't wait for Money 20/20 to start. We'll certainly be looking out for the sessions that NVIDIA and its partners are participating in. So thank you very much for being on the podcast, Kevin. It was a pleasure. Thanks for having us. And we'll see you at Money 2020. Great. Thank you for tuning in to this special episode of Banking on Information. We're looking forward to seeing you at Money 2020. And until next time, choose to be curious.