[Interview] LiveVox CEO Louis Summe’s Future of Fintech Fireside Chat

LiveVox CEO Louis Summe’s Future of Fintech Fireside Chat

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LiveVox CEO Louis Summe sat down with Forbes Snark Tank Senior Contributor Ron Shevlin at last month’s Future of Fintech event to discuss the essential role cloud plays in this moment of financial services digital transformation. Watch the interview for reflections on lessons learned since LiveVox’s founding in 2000 and thoughts on the future of customer experience. 

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Full Transcript

Tamaya Machael: [00:00:00] Welcome back to the future of FinTech 2020, before we start our next session. I just want to remind everyone that every session you see here will be available on demand on this platform. So if you miss a talk that you really want it to catch, no worries. You’ll definitely be able to see it later. And now without further ado, please welcome Louis  Summe,  CEO and Co-founder of LiveVox and welcome back Ron Shevlin contributor, Ron Shevlin.

Ron Shevlin: [00:00:27] Thank you. And welcome today to the next session. Uh, Ron Ron Shevlin, senior contributor at Ron Shevlin. I write the FinTech snark tank blog there. And today I’m joined by Louis Sonny, the CEO of live box. Hi Louis. How are you doing? 

Louis Summe: [00:00:40] Hey, Ron, how are you? 

[00:00:42] Ron Shevlin: [00:00:42] Doing great. Thanks. And thanks for joining us today, Louis, for those who might not be aware of LiveVox can you tell us a little bit about what your firm does?

Louis Summe: [00:00:49] Yeah. LiveVox provides cloud contact center software. And we have a pretty strong predisposition towards financial services. A lot of our customers are in the, in that segment and, and where LiveVox  has really been focused is on putting together a broader contact center platform.

[00:01:13] That includes not only the omnichannel capabilities, but also CRM and analytics capabilities, all in one solution. Because we believe that by giving, uh, our customers an easier path to implementation that that really positions them to get more quickly to sort of the business optimization, uh, part. 

Ron Shevlin: [00:01:41] So Louis, you were an early advocate for cloud-based tools.

[00:01:46] What was your original vision for live Vox? How has that evolved? What have you seen change over the years? 

[00:01:50] Louis Summe: [00:01:50] Yeah. And I think that, you know, cloud has always meant to us just a way of [00:02:00] using technology or in an easier form again, so that, so that you can spend more time focused on your business objectives and that’s always been kind of how we’ve we’ve approached it and why we’ve embraced cloud.

[00:02:12] I think, I think our original business plan is one of the reasons that we really always had that perspective. Our first, uh, application that we developed back in 2000, 2001 was a, actually a, uh, an AI application, a speech recognition, AI application for healthcare, for prescription renewals and that product.

[00:02:38] I think that didn’t really go as well as we had hoped you wanted it to. And, and the reason that it stumbled was because the technology was so hard to work with. And the underlying, uh, workflows were so, uh, siloed. And so, uh, you know, kinda just broken off in their own [00:03:00] little areas that it was, it was hard to make that application work.

[00:03:03] And so after that experience, we really pivoted our energy to, instead of making that AI application work to really making that contact center workflow easier. And, and more seamless. And, and it’s kind of funny because now of course, that we’ve done that a big application for our, uh, our more seamless, integrated workflow is actually to put AI on top of it.

[00:03:33] And so, you know, our, our, uh, our, our world has kind of come full circle here. 

Ron Shevlin: [00:03:39] Yeah. You know, a lot of, uh, so institutions have been slow to move to the cloud. I think the past year has helped accelerate that a bit. And I know that we’ve got a lot of folks from FinTech startups in the audience today as well.

[00:03:52] And many of them are looking to either partner or sell to financial institutions. Are you still seeing resistance to the cloud? And if [00:04:00] not, what kind of strategies are you seeing them deploy and you know, how do you get them to be more friendly towards the solutions you’re bringing to the table? 

Louis Summe: [00:04:08] Yeah. I mean, I, I think that, and, and only time will tell, but I think that is what we’ve seen here.

[00:04:16] Uh, in 2020, especially with the, you know, with the impact of the coronavirus and a lot of organizations moving their agents into work and home environments. So I think we’ve really seen kind of a tipping point in how people think about cloud versus premise. Historically, people really looked at premise as a more secure, more reliable, more compliant platform.

[00:04:42] And over time as the cloud is mature, that’s certainly become less true. And, and when, when people were asked, Hey, let’s move your contact center agents in response to this pandemic, let’s move them out of center where they’re at a higher risk [00:05:00] of infection into, you know, a work at home configuration where it’s, it’s safer for, for your employees.

[00:05:08] Um, I think at that point, A number of people started to look at the premise based solution really as, as not quite such an advantage anymore and maybe really more of a liability. And so I think that again, time will only tell, but I suspected this point that the, the market has, has really sort of pivoted towards the cloud.

[00:05:31] Now, now, again, with that said, um, that’s really only possible for financial services. If. If the cloud provider is strongly anchored in compliance and security and in reliability because inside of financial services, those, those are, those are important dimensions, really to any enterprise, but inside of financial services, there are of course, uh, of particular importance, 

Ron Shevlin: [00:05:55] Any preferences for any of one major cloud vendor over another?

Louis Summe: [00:06:00] Well, I mean, I liked the LiveVox solution for, you know, but, uh, but in terms of, in terms of the, uh, the public cloud providers, I think Amazon, uh, does, uh, does a pretty strong job. And, uh, we have, uh, we have a lot of our, uh, software in Amazon data centers. 

Ron Shevlin: [00:06:18] Yeah. So a big part of what LiveVox does of course is improve the customer experience.

[00:06:24] And I’ve gotta be honest with you, Louis. I’ve been hearing about the customer experience for 20 years, and even though I’m supposed to be an expert in the space, it gets me confused. What does a, you know, it’s it’s singular customer experience. I think. Aren’t there a lot of different experiences that cut across a lot of different channels that cut across a lot of different products and services.

[00:06:45] What’s really happening from a customer experience perspective? What are the leaders doing in this space? How are you helping enable them to do that? And where are things going with that? 

Louis Summe: [00:06:56] Yeah. Yeah. So you’re right. Customer experience is a [00:07:00] vague term and it applies to a lot of different things in a lot of different scenarios.

[00:07:04] But there are definitely some things that it has in common. And, and the first thing that applies to really all the customer experiences is that they end up being more or less a journey, a journey of how a customer interacts with an enterprise across multiple channels, whether that be internet, SMS, chat, voice.

[00:07:32] Or in person as well as multiple departments, whether that be in some sort of new business role, some sort of, uh, you know, underwriting department or a loan servicing department. And so as a customer goes through different channels and interacts with different departments, their experience can be sometimes.

[00:07:58] I would say awkward, [00:08:00] right? Because when a customer is interacting across different channels and different departments, they really expect those to have a kind of a common element to them and, and they, and they expect each of those different venues to, to know who they are and to, to adjust to they are and to provide a consistent experience.

[00:08:25] And given that most departments and most in many channels are on separate platforms. Getting to a seamless customer journey is, is, is difficult. And so that’s, that’s been a struggle. It’s a struggle in financial services, but it’s also a struggle in many industries. And that’s why it’s been such a topic over the years, but there is a lot of technology involved in the contact center.

[00:08:54] And pulling it together into a more seamless package that, you know, that’s really [00:09:00] what we are all about. And I, you know, that that’s work right. And, and, and other people are, are, are working on that as well. But that’s really the goal. And I think one thing that we think about first and foremost, when we, when we target, helping people get to a more seamless journey is, is really empowering their agents.

[00:09:23] Making sure that their agents have a, a stronger platform that has better customer information embedded in it so that the agent is really empowered to deliver a better, better customer experience. I think that’s something that is sometimes forgotten. That really, you know, as you strive to get a better journey and a more seamless experience.

[00:09:50] You gotta make sure that you’re really empowering that agent to be a strong partner in that and giving them the tools to, to personalize the experience and also to [00:10:00] resolve problems, uh, quickly and, uh, and give, give the, uh, the customers personalization and the fast response that they, they want. 

Ron Shevlin: [00:10:09] Yeah. You mentioned Louis, the, the multiple platforms that a lot of financial institutions have.

[00:10:15] I think a big reason for that is really driven by the organizational structure. There were just so many, you know, stovepiped in siloed channels and product organizations, you know, from your perspective, having worked with a lot of financial services firms, what are the smart ones and the successful ones doing to help overcome barriers like organizational silos.

Louis Summe: [00:10:36] Yeah. And, okay, so let me start off by saying what we do not do. As we do not go in and recommend to organizations that they shut down existing, uh, data silos. We do not do that instead. Our approach really is to come in and say, look, if you want to give a more seamless experience to the customers and empower your [00:11:00] agents with a more seamless experience.

[00:11:02] You should create a layer on top of a data layer and a workflow layer on top of your existing silos. And again, that’s, that’s, that’s where we are. That’s where we are focused on what we are all about. So when we think about our R and D a big part of what we develop is making sure that we can easily take data from multiple existing legacy systems.

[00:11:29] And securely with a high degree of compliance and cert them into our, our layer that sits on top that really gives the customer and the agent that more seamless experience without disrupting the existing underlying, uh, systems and underlying data flows that the corporation that the financial services entity is, is dependent on.

Ron Shevlin:: [00:11:52] How long does that take, how long should a financial institution expected to take to deploy these new 

Louis Summe: [00:11:59] workflows? Yeah, well, I, I don’t usually recommend a kind of, uh, an overly aggressive approach, you know, and I, it, it’s probably something that from a deployment perspective makes sense. It does. It makes sense really to think.

[00:12:20] Uh, department by department really starts in one area and then, and then moves into another area. And I, and so when you, when you think in that way, I think you can probably set up a department with a, uh, get started workflow. And, um, in, in 60 to 90 days from, uh, from, uh, let’s get started, uh, kind of moment, you know, post contract post, uh, Post-implementation implementation plan.

[00:12:49] So it can, it can go pretty quickly to get that first apartment. And that first workflow up with that said, once it’s up, of course, you’re going to want to iterate on [00:13:00] it and you’re going to want to see how it works and how you might apply it to other departments. 

Ron Shevlin: [00:13:05] Great. Let’s talk a little bit about the emerging technologies that are coming down the pike that are going to impact and transform the contact center and the customer experience.

[00:13:15] Uh, from a foundational perspective, what should financial services firms and even FinTech firms as well be thinking about in terms of deploying artificial intelligence technologies? 

Louis Summe: [00:13:26] Yeah, it’s a great question. I think there’s a lot of potential in artificial intelligence and where we’re excited about it, and we’ve been involved in it for many, many years.

[00:13:37] Um, but I think that’s a big part of what those, uh, those tools do. Um, you know, it, they rely heavily on, uh, on statistical processing and, and data-driven algorithms. And so if you really just peel that back a little bit and think about it, [00:14:00] they, they really are only as good. It doesn’t really matter what they are.

[00:14:05] They’re really only as good as the data set that they have. And there’s really two datasets that are, that are most important to inform the algorithms. The first data set is a customer profile data set. And of course that involves the customer journey, but it also involves, you know, a segmentation or, you know, product potential and, and classifications of the customer.

[00:14:29] But then on top of that, there’s the service history. That the customer has with the enterprise. So what did they most recently engage in? Are they following up on something? Where, where does that request or where does that engagement exist inside of the organization? And oftentimes that information is held inside of a ticketing system, which is tracking how the customer is being serviced, how [00:15:00] the service delivery model is operating.

[00:15:02] Across multiple departments and across multiple functions. And then there’s the knowledge database, which is sort of an expert database that helps the agents make good choices in, in, and executing that service delivery. And so I think, I think the customer profile, the, the service delivery data sets around ticketing and around a knowledge database.

[00:15:29] Those are all. Those are important elements for any, any algorithmically driven system, right? Because it’s those variables, those data variables that determine how the algorithm is going to operate. And that’s a big part of it fully is making sure that whether you’re talking about a virtual agent for the voice side, or whether you’re talking about a chat bot for a chat or for SMS.

[00:15:56] That those, those applications have a [00:16:00] rich set of customer and service delivery data sets available to them because that will, in some ways define, uh, what they’re capable of doing. But on top of it, it also defined your ability to tune them. And ultimately these algorithms have to be, they have to be tuned and they have to be optimized.

[00:16:19] Nobody should. Deploy AI. And just assume that it works out of the box, because even when you look at the amount of time and effort to integrate and implement, which is an area that we really focus on making that easier, you still even setting aside that part of the exercise, you still should anticipate a fair amount of time.

[00:16:43] Of tuning and making sure that the, uh, that the, of the virtual assistant or the chat bot is executing in a way that delivers not only efficiency, but a superior customer experience. And that’s, that’s just not, it doesn’t just happen. Yeah. 

Ron Shevlin: [00:16:58] Yeah. Lewis a [00:17:00] bank like bank of America, JP Morgan chase has, I don’t know, somewhere between.

[00:17:05] 25 and 50 million customers with probably a billion transactions a year, a mid-size financial institution, even at the billion dollar asset level may only have, I don’t know, 150,000 to 350,000 customers and members. Do they have enough data to really drive a good AI system? 

Louis Summe: [00:17:25] Yeah. Yeah, I absolutely because, um, You know, you, you get, you get pretty far.

[00:17:35] I mean, you get something like if you, if you’ve ever interacted with, well, well, let me, let me backup for a second. Uh, when you talk about AI, uh, you know, from a financial services perspective, there is the, uh, I’ll give you an example there. Say for example, the, the use of AI for underwriting. And [00:18:00] identifying, uh, datasets that help underwriters make better decisions.

[00:18:07] When I, when I talk about AI, I’m really, I’m really focused more on how do you use AI for the customer experience? So I’m not, I’m not, I’m not addressing all of the AI use cases with my, with my comments. It’s mostly centered around what we do, which is the, which is the context center. And so when you look at the contact center and again, in the most common form, I mean, there’s three real forms of AI.

[00:18:35] There’s sort of the, uh, you know, the, uh, the virtual agent, which is more interacting over the phone. There’s a chat bot, which is more interacting over chat. And then there, there’s a form, more like an agent assist. It’s almost like an AI augmentation where, uh, there’s advice being provided to the agent on.

[00:18:56] Um, on either talk offs or on workflow decisions. [00:19:00] So you have three categories, um, of AI right there, but yes, you can absolutely build, uh, intelligence off of a, you know, 150,000 accounts. Absolutely. Because I mean, even with 100 or 200 or 300 experiences, they start to give you a data set. And once you have a data set, you can find patterns.

[00:19:24] And of course, some of the patterns don’t really choir AI either. They’re more, you know, they’re a little more obvious. So it isn’t, it isn’t that the, um, you know, that the AI tool has found some sort of long tail statistical pattern. I mean, there’s a lot of generalized patterns that are sort of low hanging fruit, pretty, relatively simple.

[00:19:44] And in that instance, the AI isn’t so much the tool to find the pattern. But it’s more of a tool actually to execute the pattern. 

Ron Shevlin: [00:19:52] Yeah. So let’s look to the future a little bit. Louis, there are folks out there who believe that AI will not just [00:20:00] transform the contact center, but actually replace human agents completely.

[00:20:04] What’s your view of the future of customer engagement and customer service in the contact center? Well, 

Louis Summe: [00:20:11] I suppose that AI may, uh, Well, look, AI will replace agents in some scenarios, but there, there will be, there will be many scenarios where, uh, where it doesn’t. And so I think, I think AI is, uh, we’ll, we’ll, we’ll replace some tasks and frankly, it’ll, it’ll probably first and foremost replace the tasks that are more rote and more repetitive.

[00:20:40] And then, and then as it does that, I think the agents will be asked to operate at a higher level of skill. And so then, then AI’s role will be again, more in sort of, an augmentation role in helping the agents deliver on, uh, you know, [00:21:00] on, on, on their ability to solve more complex tasks. 

Ron Shevlin: [00:21:05] I can see a scenario that we’re kind of getting into a bit of a problem in that way.

[00:21:09] AI delivered service. Isn’t actually part of the contact center. It’s part of a channel execution channel delivery, channel transactions, wherever that’s happening. We’d run into a problem where if there isn’t good integration of the data across the channels that the contact center or the future is actually hampered by developments.

Louis Summe: [00:21:30] There, there is zero doubt that if you put too much faith in technology, it will and will let you down. Right. I mean, you, you absolutely have to, uh, embrace technology and the Apple absolutely have to invest in it, but you also have to, you know, monitor it and, and test it and observe it and what we’re all, we’re all human beings and we want interaction and we want, uh, you know, we wanna, we want a [00:22:00] human touch.

[00:22:01] And so I, I think that, that people like AI and they like self-service. Uh, when it delivers quickly and easily for relatively simple tasks, but when it doesn’t deliver and when the task is maybe a little bit more complex or they feel a little bit more uncertain at that time, they want to clear an easy way to escalate to, to a human.

[00:22:27] And when they get to the human net, the human, they, they want them to be, uh, you know, knowledgeable of them. They want to personalize that experience and they want, they want that human to respond competently and quickly to, you know, to their needs. And so I think it’s, it’s the blending of all of those things that really, that really should be the goal.

[00:22:51] And, and if you just look at one part of that and say, Hey, I’m just all AI all the time. I, I think that you, you. [00:23:00] You know, I think people will find your customer experience to be, uh, not quite as good as somebody that really blends AI with the, with the human element. Um, more elegantly. Great. 

Ron Shevlin: [00:23:16] So we just got a couple minutes left Lewis and I want to transition to something that we do with a lot of sessions here at the event.

[00:23:22] And ask our speakers and our experts about, uh, uh, overestimated or underestimated that to run a few things by. And I want to get your gut sense if you feel they’re overestimated or underestimated, you ready?

Louis Summe: [00:23:34] Yeah, absolutely. 

Ron Shevlin: [00:23:36] All right. Open banking.

Louis Summe: [00:23:40] I’m sorry. I don’t know what that means. Show. 

Ron Shevlin: [00:23:43] Nope. That’s okay. It’s one of those buzzwords and I just want to see the reaction. Forget that one. Next one. Break bank branches, overestimated or underestimated. 

Louis Summe: [00:23:53] Um, I think bank branches are shrinking and I suspect that that will continue. 

Ron Shevlin: [00:24:02] Amazon as a bank. 

Louis Summe: [00:24:05] Overestimated.

Ron Shevlin: [00:24:07] Why is that? 

Louis Summe: [00:24:09] I mean, uh, I, I think, I think people are cautious when it comes to banks and. You know, banks have brand and they have brand around security and they have brand around reliability and Amazon has brand around, uh, getting the packages to you quickly and easily. And that’s great. That’s a great brand, but, uh, it’s not quite exactly the same brand, is reliability and security and trust. Just not exactly the same. 

Ron Shevlin: [00:24:45] I actually agree with you on that, but I’d add the point that I think Amazon is better positioned to be a partner to box than a competitor to banks, and actually help them more than, than hurt them. So I’m with you on that one. And with that, I think we are pretty [00:25:00] much running out of time.

[00:25:01] So Louis Sami, CEO of LiveVox. Thanks a lot for being with us today on this, uh, one-on-one fireside chat. 

Louis Summe: [00:25:07] Thank you, Ron. I appreciate it. Have a great day. 

Ron Shevlin: [00:25:09] You too. 

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About LiveVox

LiveVox (Nasdaq: LVOX) is a proven cloud CCaaS platform that helps business leaders redefine customer engagement and transform their contact center’s performance. Decision-makers use LiveVox to improve customer experience, boost agent productivity, empower their managers, and enhance their system orchestration capabilities. Everything needed to deliver game-changing results can be seamlessly integrated and configured to maximize your success: Omnichannel Communications, AI, a Contact Center CRM, and Workforce Engagement Management tools.

For more than 20 years, clients of all sizes and industries have trusted LiveVox’s scalable and reliable cloud platform to power billions of omnichannel interactions every year. LiveVox is headquartered in San Francisco, with international offices in Medellin, Colombia and Bangalore, India.

To stay up to date with everything LiveVox, follow us @LiveVox, visit www.livevox.com or call one of our specialists at (844) 207-6663.

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