Episode Thirty-Two: Data is a Journey, Not a Destination

Shifting from Omni Channel to Connected Customer Experiences

Data is a journey, not a destination. Business leaders need to be decisive about the problems they want to solve with data and analytics and work diligently to solve them.
 

We’re joined by Lisa Fiondella, Chief Data Officer at Finastra, where we discuss utilizing data to solve real-world problems, making better connections between banks, employees and customers through data and Artificial Intelligence and why risk, revenue, growth and productivity are going to be even more important in the future as we seek to try more effectively serve customers.

(Please note that this podcast was recorded remotely.)

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The Power of Data Podcast

Episode 32: Data is a Journey, Not a Destination

Guest: Lisa Fiondella, Chief Data Officer, Finastra
Interviewer: Sam Tidswell-Norrish, International CMO, Dun & Bradstreet

Sam 00:00
Welcome back. You're joined by me, Sam today and I have with me, on the phone I should add, Lisa, Fiondella, Chief Data Officer at Finastra. Welcome, Lisa.

Lisa 00:08
Thanks, Sam. Good to be here.

Sam 00:10
Lisa, let's set the scene because people aren't listening to this on their morning commute. They're probably listening to this from their wingback-armchair at home. Where are you in the world right now?

Lisa 00:19
Well, I happen to be in my kitchen and Atlanta, Georgia, and like most people around the world who have the opportunity, I'm working from home.

Sam 00:26
Awesome. Atlanta, Georgia is actually somewhere I know relatively well. I believe if I get the stat right, 70% of the US payments flow through that payments hub Atlanta is that correct?

Lisa 00:37
You know, I thought the number was 80%, but 70 to 80, both are directionally the same. So yes, that's correct.

Sam 00:44
It's no surprise then that you’re a Chief Data Officer, the flow of payments around the world giving us so much insight into both consumer and commercial analytics, but you're new at Finastra. I believe if I'm right, you joined towards the end of last year and you had a storied career. Working with a number of other data businesses and financial technology firms, can you tell our listeners a little bit about what you've been up to both in the last few months in Finastra, but also historically?

Lisa 01:10
Absolutely. So yes, I joined Finastra at the end of October of last year. So it's been about five months. It's been fantastic journey so far, although where we are, and kind of the history of the world is a little unique place to be, as we all know. But just a quick background, I started my working career in banking. I worked in a bank when I was in school and had the opportunity to kind of work with consumers and businesses and I actually fell in love with financial services. At that point in time, I just thought it was the coolest job I could possibly have. But my first career role was with Equifax where I really had the opportunity to learn the importance of what data driven decision making looks like, and had the opportunity to really see how analytics could play an important role and just helping enable people transaction. So all those things that I watched and participated in, in banking, I had the opportunity to sort of see it from the data standpoint. I spent a lot of years at Equifax and then went on to spend a couple of years with another large core system provider, then moved from regulated data into non-regulated data with a small division of Reed Elsevier, which is the parent company of LexisNexis. And most recently, I was with Experian where I was responsible for analytic products in North America. During my time back at Reed Elsevier, I actually had an opportunity to work with D&B, so D&B was important partner for my business at that time. It's been a long data and analytic journey with regulated, non- regulated, consumer or commercial data and kind of all sides of the business. So that's a bit of my background.

Sam 02:48
Thank you. And Finastra is a fascinating company, at D&B we've had a very long corporate history and lots of companies have spun out of dun & Bradstreet, including firms by Moody's and Cognizant. Finastra has had an equally interesting history and most recently with private equity ownership. Can you tell our listeners a little bit about Finastra and how it came to be?

Lisa 03:08
Yeah, so the background on Finastra is, it's a combination of two companies to Mysis, which is largely a global financial software company and DNH, a North American based financial software company, those two companies came together in 2017 to create Finastra. Our footprint is in fact global. It's a bit of a powerhouse of software solutions serving about 90% of the software needs of financial institution. We have about 10,000 employees globally and about 9,000 clients. So just a really fascinating company to be part of today.

Sam 03:45
I can only imagine the Finastra that I know friend and colleague, Richard Lumb is actually on the board of Finastra, he talks about it as being one of the world's largest FinTechs and I know that you guys are focused on delivering innovative next gen technology across the Financial Services ecosystem. What does that mean from a data analytics perspective? And what are some of the key priorities you're focused on?

Lisa 04:07
I think characterizing Finastra as the world's largest FinTech is spot on. And from a data and analytics perspective, when you think about just the interactions we have with data in the financial process, it's really quite a fascinating set of information. And so I think the best way to look at it is, it's largely untapped. Most financial institutions just don't really realize the full benefit of the data that they have available to them. Even the largest enterprises, and many of them have the resources and the bandwidth to try and bring some of this information together. But they're on a journey as well. So data is critically important to our business and our to our clients. And one of the things that interested me and brought me to the company was Finastra’s investment in fusion fabric cloud. So if you're familiar with our most recent technology innovation, we've created an open banking platform that's built on cloud technology that facilitates the interactions of Finastra’s software applications with other clients and FinTech applications to create this open banking ecosystem. Well, if you think about open banking, and if you think about all those interactions, what's making them work is data. So data is the most important really, asset in that journey. And Finastra really recognized the opportunity to not only create and facilitate an open banking environment, but also make sure that the data that's flowing through that environment is in fact being utilized to the best of its ability. And so that was really the driving force behind my joining Finastra quite frankly, Finastra creating the role of Chief Data Officer. And I'm very early in the journey but it's a, like I said, a great time to be part of the company.

Sam 05:59
You know at D&B, we talk about the five V's about data, which is, you know, every day the volume, velocity and veracity of data is increasing. And so to have the opportunities for those that leverage data and analytics, that opportunity is also an opportunity gap for those that aren't leveraging them. And I think the companies that are left behind are going to be the ones that don't have appropriate data structures, don't apply data analytics to meaningful use cases, both internal use cases, and also external. And one of the ways we look at how we deliver value for clients is on the defensive and offensive side. On the defensive, financial and risk solutions to help understand more about a customer to help make better decisions relating to the customer. And then on the offensive side, and again, a lot of people don't know this, about D&B, 40% of our revenues are focused on growth related solutions for clients. How can we take corporate and commercial data and analytics and help them add more value to their clients, to grow their client bases to seek new clients to propensity analysis, and prospecting, and then internally to link all of their systems together through customer data platforms, for example, and so that they can connect the data segment the data, and activate the day to meaningfully. This stuff is complicated. When you're speaking to your financial services clients, many of whom have senior executives in banks who don't understand this stuff, how do you communicate to them the value of what you're doing?

Lisa 07:33
So that's a great question. So first of all, I think you have to have the conversation with these senior leaders from the standpoint of the value that it brings to the business. Because, you know, listen, data at the end of the day is an intangible, it's very hard to touch and feel. So while we can create visualization around data, the richest forms of data solutions are those that are embedded in the processes and workflows of a business. And that's a really important point because we all like dashboards, and we all like looking at business intelligence applications. And those things are critically important to the operations of a financial institution in particular. But what we want to do is we also want to take the insights that come from the data sitting behind those visuals, and we want to utilize it to make better decisions. So I think going back to your point about the way D&B thinks about data, I tend to think about it from three points of view. One is around managing risk, the second is around growth and revenue, and the third is around productivity. So if you have a conversation with you know, a leader about some of the challenges they're facing in automating the back office, or you know, ensuring that their customers have the right products at the right particular point in time, then you can take those conversations and say, well, with those problems or those challenges in mind, let's talk about how your data or other third party data such as DMV can actually help facilitate the answer to that question. And I think if you start with sort of the challenge of the problem statement, you're able to move them through a process to where they go, Aha. Now I understand that if I take data, maybe I need to do some modeling and so forth. And I use the answer to that data set in my, my Finastra loan system, for example, then I can realize this benefit, that's when it becomes real and tangible, and then they can start to associate real value with the data that they have either internally or that they acquire externally. Does that make sense?

Sam 09:39
Makes perfect sense and productivity is a great way to look at it. You know, if you speak to a bank executive these days us where the focus points are, I suspect much of the time they're going to tell you they're under pressure from shareholders to increase top line growth, to cut costs, which doing both and sometimes hard, to innovate more and to solve customer pain points and create new use cases. And then there's probably something to do with capital risk ratios. But there's a new issue today, and that's Coronavirus. And when you think about the biggest challenges for financial institutions, this is invariably going to be one of them. You said it earlier, this is an uncharted historic moment in time, for worse sadly, what kind of challenges do you think this is going to kick up for your clients, but also for the wider economic landscape?

Lisa 10:29
That's a great question. So a couple of things, and we've been thinking about this quite a bit in the last few weeks, certainly, because first of all, the way that business is going to be conducted, it already has changed, right? We're all working virtually we're relying on technology to enable these conversations like the one we're having here today. So the manner in which we work is going to be very different. The manner in which our clients interact with their customers may in fact, dramatically change. And then I guess the other piece of this is, if you've been following the economic situation over the last couple of years, you would know that it wasn't a matter of if, it was a matter of when so it was Coronavirus, the trigger to the next economic downturn. I think that's kind of obvious that it is. So what's happening in with our clients in you know, financial services is their acquisition channels are drying up, bringing on new customers is going to be challenging. They've got to completely reevaluate the risk associated with their portfolios, and differently than they did back in 2008-2007-2008. And then they've got to think about how they interact with our customers differently and customer relationships become far more important. They've always been important, but far more important because managing risk and retaining good customers is going to be critically important. So I think that going back to those three points of risk, revenue, growth and productivity are going to be even more important in the future as we seek to try and help our financial institution customers more effectively serve their customers.

Sam 12:07
Thanks, Lisa. And I guess sort of related to that, I'm interested to know a little bit about what your thinking is around some of the more exciting and industry changing developments in data over recent years. What are some of the interesting AI and machine learning type innovations that are impacting the way we manage data that you're interested in?

Lisa 12:25
This is one of my favorite questions, because I really am fascinated by a couple of things. One is, you know, everybody always talks about how data is exploding at an incredible rate on a daily basis. And the statistics are all out there. But I don't think people often recognize sort of why that's happening sometimes. And digitization is the reason why. So if you think about the way and of course, you know, I spend all my time in financial services and thinking about how banking and financial institutions actually interact with their customers. But if you think about the way you interacted with your financial institution, even just a decade ago, you may have actually gone into a branch and the interaction that you had with whomever you spoke to was never digitized. In today's world, we very seldom go into a branch and every aspect of our interaction with a financial institution is digitized. That means more data. But more data doesn't necessarily mean that it's actually helping the financial institution make better decisions about how they use it. So my view is that this kind of explosion of data and helping organizations whether they're, quite frankly, in financial institutions, or any other industry, helping them better understand how to take advantage of that digital data and use it to solve some very real-world problems is pretty important. The other thing that's really kind of front of mind for me right now is the area of productivity. And that is where you are able to really take the mass amounts of data, apply it machine learning and artificial intelligence and kind of realize some very real-world benefits for your customers. And that may be as simple as creating a better connection between the customer and the bank employee. Or it may be making sure that your customer has the product that they need at the right price, so that they are more attached to your institution. They're more loyal to you as a client because they're getting what they need from you as a financial institution. So this digital explosion and mass amounts of data, and then using that to in particular, help solve some of these productivity as well as revenue opportunities is kind of front and center for me.
There's one other area I think that's important. One of the things that we talked a moment ago about digitization and how it's creating massive amounts of data. One of the things I'm also especially interested in around the use of AI is how it can be used to improve the customer experience. And this is everything from the front-end account origination through the customer onboarding. And as well just kind of the back end of customer and account management. You know, we used to talk in terms of omni channel engagement. But in today's world, I believe that what we need to really do is shift our thinking from omni channel to what we might refer to as connected customer experiences. And if we think in terms of connected customer experiences, then what we by default have to gravitate towards is how data and artificial intelligence can actually facilitate those interactions. Whether they are in fact interactions between customers, partners, employees, it doesn't really matter. That's just a different way of looking at the omni channel experience and by default fault. You know, data and analytics are the best way in my view to actually try and help facilitate those connections.

Sam 16:07
Yeah, and talk about data solving real world problems that's never going to have been truer than it is over the next few months quarters, potentially even years with Coronavirus. And I know that governments around the world are leaning on data to identify groups of individuals and corporates that are most in need of stimulus packages for example. This kind of activity depends heavily on high quality, accurate data, and then the right analytics to support that.

Lisa 16:35
It's gonna be interesting because one other aspect about me is my husband and I are small business owners and have been for many decades. And so the challenges that in particular, the SMB market, um, listen, don't get me wrong. I mean, I read a statistic on Friday that delta is losing $80 million a day over the course of this horrible situation we find ourselves in. I know you know, my husband and I spend a lot of time talking about what needs happen with his business in order to survive this really horrible situation. And we talked about it in terms of two things. One is his employees, and how to make sure we protect them and put them in a situation where they can live their lives. And the second thing we do is we talk about his banking relationship. So we're talking about the financials of the business. So we're not the only ones that say, what's happening around the globe.

Sam 17:22
Yeah, and makes you realize just how systemic and interlinked everything is, every action has a knock on effect. And I think understanding that there's going to be really what separates the companies and the countries that survived the fastest and those that don't. But let's swing back to less morbid stuff at the moment. You've held a number of very senior positions in the data industry. The question I always ask is around mentorship, because I'm a firm believer in learning from others that have trodden the path before. Who are some of the people that inspired you early on in your career?

Lisa 17:55
My early inspirations or and I tried to figure out if there was a trend in this one, I wrote down the names, but my early inspirations are Abraham Lincoln, largely because of what he did from a leadership standpoint during a very difficult time in history. And here we are in another difficult time in history, right? I'm fascinated by the humanitarian works of Jimmy Carter after he left office. And just what he's done over the last decades has just been fascinating to me. Some of my early inspirations, quite frankly, were Sandra Day O'Connor and Ruth Bader Ginsburg. I'm a huge notorious RBG fan. And I think how they inspired me was that they showed me that anything is possible for a woman in a leadership position. And if you look at some of the challenges that they had to overcome to be the first and second female justices appointed to the Supreme Court, then you would know that they've had to overcome a lot. So those are really some of the people who inspired me, people who have dedicated their lives to something bigger than themselves. In my corporate time, it’s interesting when I was with Equifax in the early days of my leadership journey, I had a very unique opportunity to work for an individual by the name of Bill Tucci, and he was the former CEO of at&t Canada, he was brought in to basically turn a at&t Canada around in the early 90s, mid 90s. And I had the opportunity to work under him for about three years at Equifax. He was also a mentor for me during that time, and he introduced me to the balanced scorecard and how that approach can be used to transform business and I've considered him to be probably the greatest professional mentor I've had throughout my career and I, I will never forget him and have such great appreciation for the lessons he taught me.

Sam 19:42
That's awesome. Thank you. And if funnily enough, the first person you mentioned Abraham Lincoln was one of four US presidents who actually worked at a Dun and Bradstreet. He was a credit correspondent, just before he became congressman and left Dun & Bradstreet.

Lisa 19:56
I had no idea that is fascinating information. No idea. He was a fascinating individual. If you've never read the book about his time in office, Team of rivals, it's a fantastic read.

Sam 20:07
I will have to read it. I love some of the stories about him. He had a very pragmatic and philosophical view of the world, it always came back to the same thing, which is the value of people. We've got time for one more question, which when I've got a foremost data expert on the phone, I have to ask, what advice do you have for business leaders listening who want to better maximize the use of their data?

Lisa 20:30
That's a great question. And I think there are two things the first one, and this may sound incredibly cliché, but it's true that data is a journey. It is not a destination, business leaders need to be pretty decisive about the problems they want to solve with data and analytics and work diligently to solve them. But if they try and boil the ocean, they're never going to get there. So this is not about you know, Master Data Management and building big warehouses is about solving real life. Roll problems. So incremental progress is critically important. I guess the second thing I would mention is, it's really important to be good stewards of your data and your customers data. And in doing so, you'll make good decisions about, you know, where, when and how it should be used. You know, establishing a culture of accountability to data management, introducing a meaningful governance framework as you begin your journey, if that's where you are. And if you're not at the beginning, you know, making sure you have your infrastructure intact is really important. So those would be my two, I guess, words of advice to anyone either beginning or somewhere on their journey.

Sam 21:40
Thank you. I couldn't concur anymore. The good stewarding of data is something that we live our lives by that is one of our corporate objectives. Critically important that the ethical sourcing, maintenance and use of data is at the forefront of organizations minds and it doesn't come naturally to everyone. So where they need help, they should look to experts. Lisa, I'm gonna let you get back to you day. It's early there in Atlanta, and I'm sure you've got a busy day ahead. Thank you for your time. It's been such a pleasure to talk. And when we're next able to travel, and either on that way, or you're this way, we must catch up and we can continue the conversation.

Lisa 22:18
Sam, I look forward to that. And I appreciate the opportunity to have the conversation, albeit remotely. It would have been a pleasure to sit down and I and I do hope that we have that opportunity again very soon. And that the world we're living in gets us back to some semblance of the normalcy we had before. We will see where it takes us, so thanks again for your time, I enjoyed the conversation.

Sam 22:37
Thanks Lisa,