Inside the Mind of a Modern CDO: Data, AI, and Getting It Done

Welcome back to how I Met Your Data. The show where we stop pretending data is simple and start getting real about what it takes to work with it. We've been in the data trenches, and now we're here as your companions in this ever evolving world where the community is as diverse as the stories we share, from hands on practitioners to the rapidly shifting tech. We're bringing you the insights, strategies and sometimes chaos that shape the way data really works. Whether you're here for fresh ideas, a spark of inspiration, or just some good old fashioned data banter, you're in the right place. Views expressed by me and our guests are our own and do not reflect those of our employers. So grab a coffee, get comfy, and let's dive in. I am so excited today to have my friend Vanessa Jones Nyoni join us! Welcome, Vanessa, to the podcast. Thank you Anjali. Thank you for having me. It's it's a pleasure to have this conversation with you. Would you like to give our audience a little background on yourself? Yeah, sure. Of course. I don't know how far back you want me to go, but as you mentioned, my name is Vanessa Jones, and I'm currently the chief data officer for Commerzbank in in New York. I work in New York City and I live in the suburbs in Westchester County, and I've been with the bank for about, uh, 12 years now, almost 12 years. I spent about nine of those 12 years as head of IT governance, covering New York and Sao Paulo, Brazil. And then I was asked to assume the chief data officer role in October of 2022. Prior to joining Commerzbank, I was at Deutsche Bank for about a year consulting on the investment banking side, and I did some, you know, project management work for various regulatory projects. For example, Dodd, Frank, Volcker and I spent a year doing that, and prior to that I was at Credit Suisse, which at the time I joined back in 96. It was first Boston became Credit Suisse, first Boston and then Credit Suisse, and it's actually now now UBS. And so I spent about 16 years at Credit Suisse in various capacities in it supporting various business functions Treasury, IT, tax, finance, you name it. I got I got the opportunity to move around quite a bit, which, which kept me there for as long as I was there and, and yeah. So I actually met my husband there And he. He's still there. Um, and I think this is his 29th year now. So he's been a survivor through all of the transitions and the mergers and acquisitions. So I met him there, and I'm actually originally from Freetown, Sierra Leone, which is in West Africa. I came to this country for college. I studied at Morehead State University in in Minnesota, where I obtained a bachelor's degree in mathematics. And then I went on to get my master's degree in applied mathematics at the University of Virginia before being recruited out of UVA, University of Virginia to join what was then first Boston. And then I have two children, ages 23 and 21. And yeah, in my free time, I love to, you know, kind of work out, spend time with family and friends. It's always interesting to hear people's journey. It's always it's almost always fascinating. You know, I had gotten into data. I was telling Angela earlier that I started off as an accountant, and I fell into data because I was correcting journal entries and kind of fell into it. Most people fall into data. I was curious, like, what? Is there a thing? So you never plan to have a data career, right? You studied mathematics. You did. You worked at night programming? Yeah. I mean, there are. Let me ask you a question. What are the things that you love most about data, and what are the things that you may not like as much about working in data? So I love the fact that I have, you know, sort of okay, so so comes back as a whole is, you know, it's a it's a large organization. I work in the New York branch, and I like the fact that I have a lot of latitude to shape the data governance program. And, you know, the I program the way, you know, I see fit, I have a lot of latitude where a small branch, you know, it's it's close knit. I have a really good, you know, relationship with the front office functions and middle and back office functions. So the fact that, you know, I have those close relationships, I think makes makes my job a little easier. Obviously we have to deal with, you know, our global colleagues, our global counterparts, which is obviously more challenging. But the fact that I have the latitude to shape the program, you know, the way I see fit. And, you know, my managers trust me and have given me that latitude, I think is is, you know, is something that I enjoy. And, you know, we're small team but and we have a lot of projects in our plate on the pipeline. There's so much to do. But I feel like I have the support and the sponsorship that I need to be successful. So that's, you know, that's, you know, one thing I like about my job, what what I find challenging, I think that was the second part of your question, if I'm not mistaken, is just sort of balancing, you know, having a small team because you also want to show the value that you're bringing to the table to justify, you know, your existence and the fact that your role is needed. So I think it's balancing, you know, the fact that we're a small team constantly reprioritizing, you know, obviously we're also faced with the challenges of regulatory requirements evolving. As you know, I evolves rapidly. And so, you know, I find sort of balancing all of that is, is very challenging. But I think it's, it's, it's, it's it's worthwhile and it's rewarding, you know. But I feel like if I had more resources, I would be able to do more and be more effective. But it is what it is. And I, you know, I, you know, I do the best that I can with the resources I have. I tell people that I, I tend to beg, borrow and steal resources from, from my colleagues in Germany, which is why it's also very good to have those relationships, you know, and being with the firm for about 12 years now, I'm tapping into those relationships that I've established, you know, along the way, doing those 12 years. And I'm calling on people who, you know, I've interacted with and thankfully have a good relationship with to to help with me, with, you know, filling with resources, whether it's, you know, trainees or, you know, resources that they may have who can help me with my projects. project. So. So it's it's a lot to sort of balance and prioritize and juggle and at the same time like show value. So if I had more resources I think I could be I could do so much more. I think I'm with you. You know, what I love about data or being in a data space is like just the ubiquitous nature of data. It's everywhere and it's ever changing. And so I love the dynamic nature of data. But I'm also with you on the on the challenges is that you can almost because of the just the sheer amount of data that exists, the sheer amount that's created. You feel like you can you can never have enough resources. Like if you you if you gave me 100, I could find things to do for 100 people. If you gave me 200, I could. You know, you'll there's always something on something to do, you know. The other challenge that I find is that despite the ubiquitous nature of data like it being everywhere, it's people. Everyone's either creating data or consuming it. I think the other challenge that I think we come across often is that there's still, I think, a lot of data literacy challenges. In many, many institutions. How do you how do you overcome that aspect of data? Like how do you go out and solve for data literacy across an enterprise like in your relationships? Yeah. So, you know, obviously we have a formalized program around AI literacy and also data literacy. And so, you know, how do I bring that back, you know, to New York? Well, one of the things that I established at the beginning of this year, you know, is the AI task force. So, as you know, and as you can imagine, there's a lot of buzz around AI technology and, you know, using AI. And, you know, most of the time when people, you know, in the business are talking about AI, they really talk about gen AI. And so there's a lot of buzz around, you know, how can this technology. Again, we're a small branch. How can I utilize this technology to increase efficiency and increase productivity. So people are excited about the possibilities of the technology. And so what I tend to do there is also which, you know, I mean, it's it's it's a known fact that, you know, without a proper and robust data governance structure and, you know, you know, good data quality. There is really no I, right? I mean, you'll come up with a solution. You know, you cannot come up with an AI solution that's that's not robust. But you need that foundational, you know, high data quality, proper data governance in order to be successful in your AI, in your AI strategy. So. So I tend to also bring in obviously leveraging the programs from a data literacy, AI literacy perspective that have been developed globally. Kind of bring those into the conversation. And because people are excited about AI, you know, I, I, I always tell them that, well, in order to, you know, be have robust AI solutions, you know, you need you know, you need good quality data, you need proper data. So, you know, you also need to enhance your knowledge around around data. And you know what it can do for you. So I tend to kind of couple those two as people are excited about AI. You know, I stressed the fact that, well, you know, data is also a dependency AI. Yeah. Great tactic, which is leverage the energy and excitement around AI. Yeah. Anybody have. Yeah. And to really have effective and effective AI implementation. Having good data is a prerequisite. And hence like your like your approach or saying not to have good data. Let me let me educate you and let me help you understand what good data looks like. It's a I think it's a great way to solve sort of for a data literacy problem. Yeah. One of the things that we hear, especially in the governance space, is governance is the bottleneck, right? It's the first place to go hear the word no. It will slow you down. So, you know, recognizing that banks are a highly regulated industry. How how are you thinking about balancing innovation or speed to innovation with the need for for governance and compliance? Yeah. You know, so as you mentioned, working in a bank is is, uh, you know, we're highly regulated environment. And so, as you rightfully said, you know, balancing, you know, being innovative and also kind of making sure that we're compliance in compliance with regulatory requirements is is a must. And, you know, we need to be able to do that effectively in order to have, you know, competitive advantage at the end of the day. You know, our our goal is to generate revenue. Right. That's that's that's that's the bottom line. And I think, you know, I mean, I guess some of the challenges that we have. Around the fact that we have, you know, legacy systems. I mean, we are a bank that has existed for many years. And so we have legacy systems, and we have, you know, fragmented architecture which large global banks tend to have. Right. Resulting from decades of mergers and acquisitions. So, you know, here the goal is, you know, how do you modernize this infrastructure, you know, while ensuring, you know, continuity of services, which is also, you know, costly and resource intensive. So that's a challenge that, you know, you know, we're dealing with just like any any other banks, right. You know, another challenge is around the heightened data privacy and and data protection where global bank. Right. So we're not only subject to, you know, us us you know, regulatory requirements. We're subject to EU requirements. And, you know, the requirements of of of all jurisdictions that we operate in. So, you know, another challenge is, you know, the heightened data privacy and data protection concerns, you know, as you very well know, financial services is is a prime target for cyber threats, right. And and so we need to meet the highest standards of, you know, data governance and encryption and and and and access and access control, for example. I guess some of the, you know, I guess some of the opportunities that I see is that, you know, the vast amounts of, you know, both structured and unstructured data that, you know, banks collect, again, can really fuel, you know, establishing, implementing powerful AI solutions in many of the areas that we tend to focus in, such as, you know, fraud detection. You know, obviously these are, you know, you know, topics that are in focus, you know, for us, fraud detection, credit risk management, and etc.. So, so I think, you know, for, for, for, for for banks and and global banks having that scope across the globe I think will help, you know, fuel innovation. So for example, you can pilot an AI solution in one market and then, you know, if that's successful, if you prove it to be successful, you can then scale it, you know, to other other markets. So I think that learning and that agility at that global scale can really help create that competitive competitive advantage. So I guess I don't know if I answered your question, but I think those are some of the kind of challenges and some of the opportunities that I that I see. I think, you know, you kind of you summed it up. Really. You know, you said it really nicely, which is in financial services, you are regulated. I'm I'm Julie's train of thought and yours, which is like I sometimes feel like the regulations are a competing objective to innovation because you take the point earlier, you only have finite resources and you have finite money and you have finite time. So are you spending your resources and your budget on being the regulations, or are you trying to use those same resources for innovation or like other activities, revenue generation? I feel like it's always a hard thing, hard to talk about. You said something interesting in there is like the vast majority of our data is unstructured, like 80 to 90% of a company's data footprint is data is data that doesn't sit in a database, and that data is I would you know, I use the term lightly regulated. Regulators will have some loose regulations around it, around access controls. It's infosec, but there isn't any other any other really detailed regulation around how to mitigate risk around that. I wonder if there's if you had thoughts on how to like. Are there specific use cases that you thought would be really innovative for any given bank to say, look at all this unstructured data like, what are what are our use cases to to identify and say, let me go do something innovative with this, or drive revenue generation or some operating efficiency or some risk mitigation activity on unstructured data. Are you doing anything in that space or do you see an opportunity to do something? Yeah. So as as we as we speak of of course, you know, we're we're again, being a two person team, we're leveraging a lot of what our, you know, our global accounts, our global counterparts are doing in in constant, you know, communication with them. And in terms of harnessing all of this unstructured data that, you know, that we have I think we were just talking about this the other day, that and of course, you know, being a bank, You know, we kind of tend to, you know, not be necessarily in the forefront of everything, but I think. But I think the bank has, has done a really good job in terms of, you know, trying to keep up with the technology, but also bearing in mind all of the regulations that are out there and also self-regulating in some instance. So, I mean, one of the things that the bank is starting to explore, you know, kind of to answer the question is, and again, this is something that's been being talked about is agent AI, right. And how how do we use that. One of the use cases that, that, that, you know, we're looking into is, you know, sales leads and analyzing, you know, sales leads, you know, so that, you know, obviously relationship managers can sort of have all of this data at their fingertips and they're not browsing tons and tons of, say, annual reports, you know, to kind of really come up with innovative products for, for their, you know, for their customers. So, you know, the use of agent AI and, and, and working closely with some of our third party providers. In is one of the use cases that is being looked at as far as you know, helping our relationship managers again have that competitive advantage, if you will, and also come up with innovative, innovative, you know, products for their customers. So that's one use case that we were just talking about just the other day, because it's a solution that, you know, we would want to also leverage here in New York. And the discussion was around as we as we build this solution, factoring in our US relationship managers, relationship manager requirements into into the business requirements, I think there's a I think it's a really interesting use case and one that I you know, I think that has a lot of potential, which is when you talk about unstructured data and sales leads, you can, you know, have some unstructured data and turn on the client based on, like their emails that you might get or a video chat or like when they call into a call center. So if you can look at that unstructured data to sort of, you know, flush out a more complete client profile in addition to like, just not not just the products and services that they have, but you can deduce potentially the question by the questions that they're asking, the things that they're complaining about, either through a chatbot on the website or on the phone call with the customer service representation. I think you I think that seems like a very, a very like a very good use case, which is let us really understand the client in their own words, in their own emails. And you can not just drive or think of like, you know, selling them more products, but you can also mimic like, you know, use like client retention. Some of these if you can maybe predict when a client might leave based on the the kinds of interactions that they're having through email or through a chatbot or through a customer service. You got to come back and let us know. How that continues to work out and I. Is the right tool for it. There's no other before I there wasn't you know, like I think it's one of the reasons why unstructured has been untapped for a long time, you know, is the right to a band. Do do let us know like how it how that progresses. Yeah. No. Absolutely. Yeah. I'm excited about it too. Yeah. So Vanessa, some conversations that we had was around the role of the CDO. And you know what what is the future of the role of the CDO. So I'm just curious, how do you, as a CTO of a global bank define success in today's environment? Yeah, and I think I touched a little bit on, on this, you know, at the beginning when we were just talking about, you know, the relationships that I've established over the years and, and being in this, you know, in being in the company for 12 years, I mean, only in the role for almost three years. But I think, you know, it's it's those relationships and it's. You know, the the constant communication with stakeholders both globally and locally. So I think, you know, listening to their needs and not just kind of going off on a tangent and, and building a solution for them that, you know, you think they, they want or that you think is best for them. I mean, most of the time you're right anyways, but kind of really listening to them and, and and coming up, you know, with the best solution. So they may not really know what they want or what's best for them. But you know, it's a collaborative effort, right? I mean, that cross-functional engagement and, you know, being in a position where you're able to break down silos in order to be able to implement the best solution possible. And, you know, I also I always saw with I always I'm a fan of always starting small with that MVP, that minimum viable product to kind of gain confidence and buy in from stakeholders. So doing that proof of concept or that prototype as well before really, really scaling up. So I think, you know, that's that's you know, one thing that's that's really worked for me. You know, the constant communication and and really listening to their needs. You know, another thing that you know has worked is just kind of making sure I'm aligning my priorities with the business strategic objectives. And I think people talk about this, you know, a lot that that's the right thing to do. So again, this is where the frequent communication with the heads of the various businesses locally, you know, in the branch is important. And I think it's easier for me to do that because we're a small branch. So, you know, I feel like I have no excuse to make sure I maintain that pulse in terms of what the priorities are. You know, what's important to them. And in the ever evolving environment, dynamic environment that that we're in, things shift and making sure that when things shift and things could have shifted since I last met with them, you know that I'm also kind of adjusting, you know, my priorities based, you know, kind of based upon, you know, you know, what I what I hear, what I hear from them. So that's, you know, you know, one thing that, you know, I, I endeavor, I endeavor to to to do. You know, I think also, again, I have no choice in this, but it's something that I, I tend to do. Kind of creating that environment that encourages diversity of thought. So I'm a small team, so I want to make sure that I'm engaging all the right people from the right groups. I talked about, you know, kind of breaking down the silos, making sure we have that diversity of thought and creating that space, that environment where people are not afraid to share their perspective, I think has been really key to. Success to me being successful and I think I am anyway. And you know, because I don't have all the answers. So the more people that you bring to the table and that you create this comfortable space, that they're able to share their thoughts and opinions and, you know, know that there is no stupid question. You know, creating that, creating that environment, you know, I think is I think is is is crucial in, in terms of making sure that you, you get the best outcomes. So those are some of the things that I, I tend to yeah. Take around. I just have like really good relationships. Do do small like achievable like credible like POCs or to do establish credibility. And I like especially the last one which is really diversify the thinking on on on things. Do you have any like tips or tricks when it comes to people who might be passive in their in their support or may provide headwinds, Wins. Like how do you go about dealing with like those circumstances? So I, I tend to also have one one to ones with people who, you know, again, may be passive in terms of their, you know, in terms of their thoughts. So not everybody is comfortable, you know, operating in, in, in an environment that has a lot of people around the table. So I, I tend to also have one to ones if I sense that, you know, this particular person may have a great idea but isn't speaking up or, you know, is shy about speaking up or isn't comfortable about speaking up. So I what I tend to do is just have one to ones with that person or those individuals. And then at the next round table, you know, kind of bring that person's idea to the table, but obviously giving them credit that oh, in my conversation with person X, you know, he or she brought this up. And I think it's a great idea. What does everybody think. So that's kind of how I tend to, you know, tackle that that situation. Yeah. I think you have to work in data. You have to. It's like sometimes it's not data. That's the problem. No. The challenge. It's building those bridges. I think you're, you know, I think you offer some good advice, which is like having those sort of 1 to 1 relationships to, to advance use is a is it like an essential, I think characteristic to, to work in data. You either go everywhere. Right. It's ubiquitous. Everyone's either producing or consuming it. That means you have to be able to work with everybody. Yeah. Yeah. I think at least 50% of my job is around, like communication and stakeholder management. And you know what I mean? So it's you have to be out there. You have to be sort of, you know, kind of promoting the work that we're we're doing and constantly reminding people of the value actually, that you're bringing to the table. I mean, I think that's the other thing that I, I mean, I'm not really good about kind of marketing my successes, but I think it's important that I do. And I have to constantly remind myself of, okay, you need to kind of express the value that. You are bringing or that you can bring to the table. So that kind of people realize, you know why this is all important and and why are we doing all of this anyway to begin with? So you're operating as a chief data officer, the chief marketing officer, and the chief communications officer. If I heard you correctly, you're getting three paychecks, if only. Right. Vanessa, one of the other things that I wanted to make sure that we we touch on is the CDP, the women data professionals, and that you're part of the content team. So can you share a little bit about what the CDP does? Yeah. Of course. So WHP stands for Women Data Professionals. And it's it's a it's a global forum for men and women. So and the goal the mission of CDP is to provide, you know, support for and promote women in the field of data and assist in their development and, and promotion to more, more senior roles. So I joined I think it's about it's two and a half years ago. I was recruited by a contact, you know, who was at Credit Suisse Swiss back when I was at Credit Suisse and and and you know, she asked whether I wanted to join. I said sure. And, and so I joined and I'm now one of the co-leads for the content team. And the content team really focuses on generating content to raise, you know, global awareness and profiles for women in data. And it serves as a platform to highlight the success of accomplished leaders and and to create an environment for connecting women who are established in their careers or women who aspire, you know, to be women data leaders. So creating this environment, this forum to give them visibility. So the content team, you know, one of the initiatives that we're working on this year is really enhancing the website so that you know, the look and feel and and making sure that we are offering appropriate content so that, you know, people are drawn to the to the group and want to join and want to contribute. So in a nutshell, that's WHP and and a little bit about the content team. I have a question for you that since you bring this up, I have a niece that's graduating in data. Mhm. What's a piece of advice that you would give to somebody to come out of college as they endeavor into the data field? I guess the fact that she knows that she actually wants to be in data, that's that's amazing. You know, because as you were saying earlier, like I think you stumbled upon data. I stumbled upon data. But, you know, I think it's I think it's it's, you know, it's it's great that she knows that she really wants to pursue a career in data. But, I mean, I think one advice is just, I guess, continuous learning. That's a big one for for me anyway. I mean, I, I, I mean the, the data needs is constantly evolving so that continuous learning and that, you know, kind of making sure you're in touch with it's hard to do because there's a lot of information out there. But, you know, doing the best that you can and, you know, ensuring that whether it's from a kind of technical perspective or whether it's, you know, listening to those podcasts like how I Met Your Data, other podcast. All right. This kind of keeping. Keeping in touch and maintaining that pulse in terms of what's what's happening. So continuous learning kind of being open to, you know, I guess, you know, being being mentored I think is a is a is a, you know, is a is a good way looking for that, you know, person who can mentor you. And also as you build your career, who can also sponsor you, you know, because obviously there's a there's a difference there. But finding that, you know, one person who you can, you know, and it doesn't even have to be, you know, a formal mentoring, but, you know, kind of finding that, you know, person who's, you know, more senior that than you, that you can kind of brainstorm and, and, you know, discuss ideas about how you want to progress your career, somebody who you can just feel comfortable, you know, brainstorming different things with and also having as you as you look to advancing your career and making sure that you have, you know, those people who can vouch for you so that you continue to progress and get those promotions as well. I think, you know, those are some of the things that, you know, I would I would highlight for somebody starting being open minded, you know, being a sponge, you know. Absorbing as much as you can. I still try to be a sponge. You know, there's so much to learn. It's such a wide field. I think it's great advice, but it's like somebody just starting their career. But also very good advice for someone who's well into their career. Is that you can't be in the data space and not be learning and be something going on. Yeah. You know, maybe this is for a different podcast, but in my career, at 25 plus years of work and most of it directly or indirectly in data, I would say there's only one instance where I, you know, I work as a full time employee, as a consultant. There was only one instance where I would say, did not leave a situation where I learned something, and the one instance was where they just didn't care about data. Right. Yeah. All of it. And, you know, sort of as a ceremonial function more than anything. But to your point, to if you're working in data that you should almost on some weekly, daily basis, there's got to be, you know, just the pace of change is tremendous. So it's really good, really good advice. So yeah. And I think organizations like CDP are also like a great way to continue to learn as well, right? Connect with others, find the right mentors or at least a mentor. And they have. And the PDP also has a really great mentoring program that's that's also global in, you know, in the Americas, in, in APAC and, and in the media as well. So I've heard really positive feedback about the program. So that's that's one of the benefits there as well. Vanessa, as we wrap up, could you share with us three strategies that you keep top of mind to drive success in your role? Yeah. So I mean, I think kind of some of the strategies that I, that I keep kind of top of mind when as I continue to operate and in the challenging but exciting environment that that we operate in is and, and and to the point that Janine had brought up around, you know, AI literacy, data literacy and how, you know, how do we how you know, how do you incorporate that in the work that you do? And, you know, so it's more about like driving that culture around data and AI and not just looking to just execute on these projects. So it's not just about the one off initiatives. It's about embedding, like, you know, the data and AI driven thinking into into the into the organizations, you know, DNA. And I think. You know, again, going back to the point around, you know, balancing innovation and, you know, complying with, you know, regulatory requirements. For me, I always have to keep keep, you know, top of mind. Keep this top of mind that at the end of the day, you know, I want to make sure that we prioritize, you know, governance and and trust in the data. Right. Without trusting data quality in the security and compliance. So that's one thing that's all always top of mind for me as well as I want to make progress with with delivering those innovative solutions. But you know, for me, keeping that also at the top of my mind that without that trust in the data quality, in the security and the compliance, you know, even the most innovative solutions will will falter. Right. And then third thing that also I also try to keep top of mind is, you know, that starting small. So delivering value iteratively. I, I can't do the whole big bang approach. I think we all know we've been in this business, in this industry for, for quite a while. And these huge transformations, you know, kind of tend to fail more often than not. So again, those quick visible wins, at least for me, have helped build momentum and and credibility. Fantastic. Thank you. Vanessa, thank you so much for your time today. This was such an insightful conversation. Thank you again. Yeah. No, thank you so much for having me. And, you know, giving me an opportunity to share my experience and and, you know, the things that I'm working on and I'm passionate about.