 Live from Stanford University, it's theCUBE covering Global Women in Data Science Conference brought to you by SiliconANGLE Media. Welcome back to theCUBE's continuing coverage of the fourth annual Women in Data Science Conference, or WIDS. I'm Lisa Martin and we are live at Stanford University, but WIDS is going on at 150 plus regional events in more than 50 countries. In fact, there are 20,000 people expected to be engaging with their live stream today. Joining us on the program is Christina Draper, the Chief Technology Officer at Wells Fargo. Wells Fargo, one of the sponsors. Christina, welcome to theCUBE. Thank you so much, Lisa. It's a real pleasure to be here. So this is the fourth annual WIDS, and as I was mentioning some of the numbers, it's incredible the momentum that this event has generated. We like to call it a movement. Tell me a little bit about your involvement in WIDS, as well as Wells Fargo's involvement as a sponsor. Yes, so we are really honored to be able to be a part of WIDS. I was introduced through two WIDS from an employee of mine, Catherine Lee. She joined our team just about a year ago, and she's been part of WIDS since the inception. So working with Margo and the team, and we believe so strongly that in the consumer bank space, we have a tremendous opportunity and responsibility to understand how our customers interact with Wells Fargo, and that will require a discipline around data science. And so we had an opportunity at an ask this year to be an executive sponsor, and we jumped at it, and I think we'll continue to be here at that sponsor level in future years. So you've been at Wells Fargo for a long time. Tell me a little bit about your background of rising to become the chief technology officer. Sure, thank you so much for the question. It's been an interesting journey. I haven't always been at Wells, so I did a few startups here in the Silicon Valley, kind of middle of my career, and I came back to Wells Fargo. Most recently I have responsibility for the consumer bank technology space. That's the majority of the branch technology. It's all of the ATMs, the point of sale network for customers. It also is a lot of business services, so how we think about services-oriented architecture to ensure that we're always thinking about our customer and their accounts in a consistent way, regardless of how customers interact with Wells Fargo. So all channels consistently trusted. So that data set's really important. And then I also have the customer feedback and customer complaints. So the idea that from survey all the way through complaints, being able to understand how our customers are interacting with us. And data is such an interesting topic because it's so broad. And I think so many people now across generations understand data privacy to some degree. You can think of the baby boomers that were affected by the Facebook information and things being shared. From a financial perspective, tell us a little bit about the discipline of data science, not just from the technology background and understanding that your team needs to have, but also other skills such as empathy, communication, negotiation, how do all of those contribute to what your team is delivering? Yeah, I would tell you, we are in the business of trust. And three years ago, after sales practice came into Wells Fargo, it was a very interesting time for our company. We kind of lost our way. And the opportunity with data science is an opportunity to reestablish trust with our customers. And so you've seen a lot of the rebranding that Wells Fargo is doing about, we were invented in 1852, but we're reinventing ourselves now. And we have to understand our customers. We have to know our responsibilities to be that trusted advisor, to really care for our customers in every interaction. And so I would think empathy, absolutely. Trust is all about every interaction consistent every time. And so you think about even just a personal relationship and how you establish trust. It's very hard to reestablish trust. And so for us right now, the commitment to data science is about that reestablishing trust and to really thinking about every interaction with every customer and ensuring we're getting it right. You've been there a long time as I mentioned. I'd love to understand some of the things that you've seen along the way as technology changes in terms of more females becoming interested, as we know that there was, from where we were in the 80s, there's been a downward spiral. But you were recently named one of the 50 most powerful women in technology. What are some of the things as you think of how technology in Wells Fargo is re-imagining data and trust? What are some of the things that you've seen in terms of the evolution of females in technology and in leadership roles? Sure, absolutely. So thank you so much. I think about industry recognition. And I think about how important it is to recognize women's value in the industry. And so the recognition women in technology and most powerful women for me is a, it's an opportunity to really demonstrate that we should be very confident in the value that we bring as leaders. And that's confidence as a woman is hard to come by. It's often, I think about my own personal career and the way that doors were open for me along the way, often we're our own worst enemies. We second guess ourselves. We second guess our value. And we have to really work for that seat at the table. There's certainly been, I wouldn't have come back to Wells if I didn't believe that I had the right sponsors and the right mentors that were not only willing to help me kind of see the doors to walk through, but to walk through those doors. And so my coming back to Wells was really about a opportunity as a leader in technology. I had just done two startups here in the Silicon Valley. And so I was invited to come back. And it was really the leaders and the leadership that brought me back to Wells. I felt I could make a real impact. And I think that there's, when I think about the couple of jobs I've had since my second return to Wells Fargo, it's really been about impact and recognizing my voice. And starting to step into that accountability. When I think about what we can do as women leaders in technology and in data science, a lot of it is owning that accountability to leadership and to really kind of paving the way for leaders behind us. There comes a part in a career, certainly mine, where you're no longer really thinking about the next job for yourself. I'm really fortunate that I've been able to get to a CTO level, a tech division executive level. I have the recognition around what most powerful women. But I don't do that alone. I do that with a team of women and men who have helped to really create value in the space that we're in. And we're in the consumer banking space and financial services. And so there's certainly a lot of places to innovate. There's a lot of places to think about how technology can help to serve a Wells Fargo customer. And if you think about when you need your bank, you need your bank throughout your entire life. And whether you're thinking about a home purchase and auto purchase college for your children, retirement, there's so many big markers in life. And that's where I get excited about not only the leadership role that I have now, but I have the opportunity to bring a team with me to contribute real value. And so that's for me, what really brought me back was an opportunity to have that impact, to think about data science and technology in a way that there's true, visible value being added to the marketplace to the industry. It's almost like kind of you have a pay it forward attitude. I do. How are you using that to expand your team with the right skills and the right people regardless of gender, regardless of any of that, to continue this big movement, this re-imagination that Wells Fargo is a business that's undergoing? Yeah. Well, I would tell you WIDS is one way. WIDS is certainly a tremendous network opportunity if you think about the breadth and the reach across countries, across landscapes, across geographies. This is just one example of how I think about that. There's real power in relationships. There's real power in an ability to establish not only a strong industry network, a strong personal brand, but also a personal network. And even in the last couple of hours that WIDS just started today, so inspired by the keynote speakers, so inspired about how they're turning data science and really thinking about different problems, different ways that we can improve not only our lives, but the lives of future generations to come. I think part of how I think about it is finding that inspiration, because we have to inspire future generations of leaders, of women, and of men to really tackle the problems and have the right skills and confidence to be able to jump into that space. I agree with you. I think one of my favorite things, and the Cube has been covering WIDS since the beginning for four years, and I always love coming here because you walk in and you immediately feel inspired. But you also feel that sense of collaboration. You talked about how important that is, not just for people that are in academia, but in industry as well, and you said, you know, I can't do what I do. You can't be a successful CTO at anywhere. I will as far go let alone any organization without that collaborative spirit. And I think I always feel that very strongly every time I walk in the door at a WIDS event that people, they really do live up to their mission statement, which is to inspire and educate women in data science and people in data science in general. Yeah, and I would offer that there's a lot of magic in the empty space, so the space in between. And the way I would describe that is that, so you come into a WIDS data conference and certainly I come from a financial services background. That's the primary, you know, my primary professional background has been in financial services and technology. But the problems that our future generations will face can't be solved with just one lens. You can't solve problems with just a financial services expertise or just a technical expertise. You need to really look for how do you, it's the and and sometimes the space in between. And that's bringing art and science. It's an ability to bring, to think across industry and to apply solutions and innovation that have been brought forward through other industries, through other companies, through other academia and thinking about how that could apply in solving the problems that we're faced with in the financial services space. So to me, coming to a WIDS conference or spending time with the women that we'll meet in the room or the men that we'll meet in the room, it's really about listening to their stories, listening to their passions, thinking about the problems they're solving and stepping back and identifying well, gosh, if I really turn some of the problems that we're faced with upside down and thought about it with that perspective or that lens and maybe invited some people to your point, the collaboration to help solve problems with us, we might come up with a better answer. It's the space that's in between that I think makes all the difference. I like that, the space in between. And there's so much applicability. I mean, there's 2.5 quintillion dates, that's a data generated every day across every industry, whether it's personal banking information or what we eat or where we travel, we do everything through mobile these days and companies like Wells Fargo have such potential to be able to utilize that data to create solutions that help so many people. But you're right, it's how can financial services and the data that you deal with and to help customers in that sense, what's the opportunity to influence all these other disciplines? I think that's one of the things that excites me about data science is how broad and symbiotic this discipline really is. Totally agree with you. And I have a new leader, Jason Sturrell, who just came into Wells Fargo just over a year ago. And he talks about a vision where we are 100% transparent in our data with our customers. So think about that value proposition in financial services where there's 100% data symmetry. What we know, you know. What you know, we know when you want us to know it. And that can be so powerful. And that's really how we're thinking about the transformation around technology, the investment that we're gonna make in data science, the in AI and machine learning because that 100% data symmetry comes back to trust. If we're 100% transparent with every one of our customers about what we know, think about how that establishes trust. I mean, that is a rock solid foundation for trust in the future. And I think that's really something that can be very powerful if we capitalize it, but we can't do it alone. We're going to need partners. We're going to need partners like so many of the companies and the academics that are in this room today and we'll have to reach even broader because some of the solutions won't be found if we just look internal to Wells Fargo. Exactly, that diversity in so many ways is so impactful. Christina, thank you so much for stopping by theCUBE and sharing with us some of the things that you're doing, how you've ascended to the CTO at Wells Fargo and how Wells Fargo is sponsoring and contributing to this WID's movement. We appreciate your time. It's a real honor. Thank you so much, Lisa. Thank you. Pleasure. We want to thank you for watching theCUBE live at Stanford University from the fourth annual Women in Data Science Conference. I'm Lisa Martin. Stick around, my next guest will be here momentarily.